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Author SHA1 Message Date
Matej Ferencevic
8ad84e8629 Prepare release v0.50.0
Subscribers: pullbot

Differential Revision: https://phabricator.memgraph.io/D2598
2019-12-11 17:48:11 +01:00
2021 changed files with 750721 additions and 189117 deletions

7
.arcconfig Normal file
View File

@@ -0,0 +1,7 @@
{
"project_id" : "memgraph",
"conduit_uri" : "https://phabricator.memgraph.io",
"phabricator_uri" : "https://phabricator.memgraph.io",
"git.default-relative-commit": "origin/master",
"arc.land.onto.default": "master"
}

9
.arclint Normal file
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@@ -0,0 +1,9 @@
{
"linters": {
"clang-tidy": {
"type": "script-and-regex",
"script-and-regex.script": "./tools/arc-clang-tidy",
"script-and-regex.regex": "/^(?P<file>.*):(?P<line>\\d+):(?P<char>\\d+): (?P<severity>warning|error): (?P<message>.*)$/m"
}
}
}

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@@ -1,10 +1,9 @@
---
Language: Cpp
BasedOnStyle: Google
Standard: "c++20"
Standard: "C++11"
UseTab: Never
DerivePointerAlignment: false
PointerAlignment: Right
ColumnLimit : 120
IncludeBlocks: Preserve
ColumnLimit : 80
...

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@@ -1,12 +1,7 @@
---
Checks: '*,
-abseil-string-find-str-contains,
-altera-id-dependent-backward-branch,
-altera-struct-pack-align,
-altera-unroll-loops,
-android-*,
-cert-err58-cpp,
-cert-str34-c,
-cppcoreguidelines-avoid-c-arrays,
-cppcoreguidelines-avoid-goto,
-cppcoreguidelines-avoid-magic-numbers,
@@ -31,7 +26,6 @@ Checks: '*,
-fuchsia-virtual-inheritance,
-google-explicit-constructor,
-google-readability-*,
-google-runtime-references,
-hicpp-avoid-c-arrays,
-hicpp-avoid-goto,
-hicpp-braces-around-statements,
@@ -40,17 +34,12 @@ Checks: '*,
-hicpp-no-assembler,
-hicpp-no-malloc,
-hicpp-use-equals-default,
-hicpp-use-nullptr,
-hicpp-vararg,
-llvm-header-guard,
-llvm-include-order,
-llvmlibc-callee-namespace,
-llvmlibc-implementation-in-namespace,
-llvmlibc-restrict-system-libc-headers,
-misc-non-private-member-variables-in-classes,
-misc-unused-parameters,
-modernize-avoid-c-arrays,
-modernize-concat-nested-namespaces,
-modernize-loop-convert,
-modernize-pass-by-value,
-modernize-use-equals-default,
-modernize-use-nodiscard,
@@ -58,16 +47,11 @@ Checks: '*,
-performance-unnecessary-value-param,
-readability-braces-around-statements,
-readability-else-after-return,
-readability-function-cognitive-complexity,
-readability-implicit-bool-conversion,
-readability-magic-numbers,
-readability-named-parameter,
-misc-no-recursion,
-concurrency-mt-unsafe,
-bugprone-easily-swappable-parameters'
-readability-named-parameter'
WarningsAsErrors: ''
HeaderFilterRegex: 'src/.*'
HeaderFilterRegex: ''
AnalyzeTemporaryDtors: false
FormatStyle: none
CheckOptions:
@@ -92,3 +76,4 @@ CheckOptions:
- key: modernize-use-nullptr.NullMacros
value: 'NULL'
...

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@@ -1,36 +0,0 @@
#!/bin/sh
project_folder=$(git rev-parse --show-toplevel)
if git rev-parse --verify HEAD >/dev/null 2>&1
then
against=HEAD
else
# Initial commit: diff against an empty tree object
against=$(git hash-object -t tree /dev/null)
fi
# Redirect output to stderr.
exec 1>&2
tmpdir=$(mktemp -d repo-XXXXXXXX)
trap "rm -rf $tmpdir" EXIT INT
modified_files=$(git diff --cached --name-only --diff-filter=AM $against | sed -nE "/.*\.(cpp|cc|cxx|c|h|hpp)$/p")
FAIL=0
for file in $modified_files; do
echo "Checking $file..."
cp $project_folder/.clang-format $project_folder/.clang-tidy $tmpdir
git checkout-index --prefix="$tmpdir/" -- $file
# Do not break header checker
echo "Running header checker..."
$project_folder/tools/header-checker.py $tmpdir/$file $file --amend-year
CODE=$?
if [ $CODE -ne 0 ]; then
FAIL=1
fi
done;
return ${FAIL}

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@@ -1,34 +0,0 @@
---
name: Bug report
about: Create a report to help us improve
title: "[BUG] "
labels: bug
assignees: gitbuda, antonio2368
---
**Memgraph version**
Which version did you use?
**Environment**
Some information about the environment you are using Memgraph on: operating
system, how do you connect, with or without docker, which driver etc.
**Describe the bug**
A clear and concise description of what the bug is.
**To Reproduce**
Steps to reproduce the behavior:
1. Run the following query '...'
2. Click on '....'
**Expected behavior**
A clear and concise description of what you expected to happen.
**Logs**
If applicable, add logs of Memgraph, CLI output or screenshots to help explain
your problem.
**Additional context**
Add any other context about the problem here.

View File

@@ -1,11 +0,0 @@
[master < Epic] PR
- [ ] Check, and update documentation if necessary
- [ ] Update [changelog](https://docs.memgraph.com/memgraph/changelog)
- [ ] Write E2E tests
- [ ] Compare the [benchmarking results](https://bench-graph.memgraph.com/) between the master branch and the Epic branch
- [ ] Provide the full content or a guide for the final git message
[master < Task] PR
- [ ] Check, and update documentation if necessary
- [ ] Update [changelog](https://docs.memgraph.com/memgraph/changelog)
- [ ] Provide the full content or a guide for the final git message

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@@ -1,82 +0,0 @@
name: Daily Benchmark
on:
workflow_dispatch:
schedule:
- cron: "0 1 * * *"
jobs:
release_benchmarks:
name: "Release benchmarks"
runs-on: [self-hosted, Linux, X64, Diff, Gen7]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build release binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build only memgraph release binaries.
cd build
cmake -DCMAKE_BUILD_TYPE=release ..
make -j$THREADS
- name: Run macro benchmarks
run: |
cd tests/macro_benchmark
./harness QuerySuite MemgraphRunner \
--groups aggregation 1000_create unwind_create dense_expand match \
--no-strict
- name: Get branch name (merge)
if: github.event_name != 'pull_request'
shell: bash
run: echo "BRANCH_NAME=$(echo ${GITHUB_REF#refs/heads/} | tr / -)" >> $GITHUB_ENV
- name: Get branch name (pull request)
if: github.event_name == 'pull_request'
shell: bash
run: echo "BRANCH_NAME=$(echo ${GITHUB_HEAD_REF} | tr / -)" >> $GITHUB_ENV
- name: Upload macro benchmark results
run: |
cd tools/bench-graph-client
virtualenv -p python3 ve3
source ve3/bin/activate
pip install -r requirements.txt
./main.py --benchmark-name "macro_benchmark" \
--benchmark-results-path "../../tests/macro_benchmark/.harness_summary" \
--github-run-id "${{ github.run_id }}" \
--github-run-number "${{ github.run_number }}" \
--head-branch-name "${{ env.BRANCH_NAME }}"
- name: Run mgbench
run: |
cd tests/mgbench
./benchmark.py --num-workers-for-benchmark 12 --export-results benchmark_result.json pokec/medium/*/*
- name: Upload mgbench results
run: |
cd tools/bench-graph-client
virtualenv -p python3 ve3
source ve3/bin/activate
pip install -r requirements.txt
./main.py --benchmark-name "mgbench" \
--benchmark-results-path "../../tests/mgbench/benchmark_result.json" \
--github-run-id "${{ github.run_id }}" \
--github-run-number "${{ github.run_number }}" \
--head-branch-name "${{ env.BRANCH_NAME }}"

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@@ -1,273 +0,0 @@
name: Diff
concurrency:
group: ${{ github.head_ref || github.sha }}
cancel-in-progress: true
on:
push:
branches:
- master
workflow_dispatch:
pull_request:
paths-ignore:
- "docs/**"
- "**/*.md"
- ".clang-format"
- "CODEOWNERS"
jobs:
community_build:
name: "Community build"
runs-on: [self-hosted, Linux, X64, Diff]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build community binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build community binaries.
cd build
cmake -DCMAKE_BUILD_TYPE=release -DMG_ENTERPRISE=OFF ..
make -j$THREADS
- name: Run unit tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run unit tests.
cd build
ctest -R memgraph__unit --output-on-failure -j$THREADS
code_analysis:
name: "Code analysis"
runs-on: [self-hosted, Linux, X64, Diff]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
# This is also needed if we want do to comparison against other branches
# See https://github.community/t/checkout-code-fails-when-it-runs-lerna-run-test-since-master/17920
- name: Fetch all history for all tags and branches
run: git fetch
- name: Initialize deps
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
- name: Set base branch
if: ${{ github.event_name == 'pull_request' }}
run: |
echo "BASE_BRANCH=origin/${{ github.base_ref }}" >> $GITHUB_ENV
- name: Set base branch # if we manually dispatch or push to master
if: ${{ github.event_name != 'pull_request' }}
run: |
echo "BASE_BRANCH=origin/master" >> $GITHUB_ENV
- name: Python code analysis
run: |
CHANGED_FILES=$(git diff -U0 ${{ env.BASE_BRANCH }}... --name-only)
for file in ${CHANGED_FILES}; do
echo ${file}
if [[ ${file} == *.py ]]; then
python3 -m black --check --diff ${file}
python3 -m isort --check-only --profile "black" --diff ${file}
fi
done
- name: Build combined ASAN, UBSAN and coverage binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
cd build
cmake -DTEST_COVERAGE=ON -DASAN=ON -DUBSAN=ON ..
make -j$THREADS memgraph__unit
- name: Run unit tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run unit tests. It is restricted to 2 threads intentionally, because higher concurrency makes the timing related tests unstable.
cd build
LSAN_OPTIONS=suppressions=$PWD/../tools/lsan.supp UBSAN_OPTIONS=halt_on_error=1 ctest -R memgraph__unit --output-on-failure -j2
- name: Compute code coverage
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Compute code coverage.
cd tools/github
./coverage_convert
# Package code coverage.
cd generated
tar -czf code_coverage.tar.gz coverage.json html report.json summary.rmu
- name: Save code coverage
uses: actions/upload-artifact@v3
with:
name: "Code coverage"
path: tools/github/generated/code_coverage.tar.gz
- name: Set base branch
if: ${{ github.event_name == 'pull_request' }}
run: |
echo "BASE_BRANCH=origin/${{ github.base_ref }}" >> $GITHUB_ENV
- name: Set base branch # if we manually dispatch or push to master
if: ${{ github.event_name != 'pull_request' }}
run: |
echo "BASE_BRANCH=origin/master" >> $GITHUB_ENV
- name: Run clang-tidy
run: |
source /opt/toolchain-v4/activate
# Restrict clang-tidy results only to the modified parts
git diff -U0 ${{ env.BASE_BRANCH }}... -- src | ./tools/github/clang-tidy/clang-tidy-diff.py -p 1 -j $THREADS -extra-arg="-DMG_CLANG_TIDY_CHECK" -path build | tee ./build/clang_tidy_output.txt
# Fail if any warning is reported
! cat ./build/clang_tidy_output.txt | ./tools/github/clang-tidy/grep_error_lines.sh > /dev/null
debug_build:
name: "Debug build"
runs-on: [self-hosted, Linux, X64, Diff]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build debug binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build debug binaries.
cd build
cmake ..
make -j$THREADS
- name: Run simulation tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run simulation tests.
cd build
ctest -R memgraph__simulation --output-on-failure -j$THREADS
- name: Run single benchmark test
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run simulation tests.
cd tests/mgbench
./benchmark.py accesscontrol/small --num-workers-for-import 1 --test-system-arg "split-file splitfiles/accesscontrol_small.shard_configuration bolt-num-workers 1"
release_build:
name: "Release build"
runs-on: [self-hosted, Linux, X64, Diff]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build release binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build release binaries.
cd build
cmake -DCMAKE_BUILD_TYPE=release ..
make -j$THREADS
- name: Run unit tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run unit tests.
cd build
ctest -R memgraph__unit --output-on-failure -j$THREADS
- name: Run simulation tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run simulation tests.
cd build
ctest -R memgraph__simulation --output-on-failure -j$THREADS
- name: Run single benchmark test
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run simulation tests.
cd tests/mgbench
./benchmark.py accesscontrol/small --num-workers-for-import 1 --test-system-arg "split-file splitfiles/accesscontrol_small.shard_configuration bolt-num-workers 1"
- name: Run e2e tests
run: |
# TODO(gitbuda): Setup mgclient and pymgclient properly.
cd tests
./setup.sh
source ve3/bin/activate
cd e2e
LD_LIBRARY_PATH=$LD_LIBRARY_PATH:../../libs/mgclient/lib python runner.py --workloads-root-directory ./distributed_queries

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@@ -1,46 +0,0 @@
name: Run clang-tidy on the full codebase
on:
workflow_dispatch:
jobs:
clang_tidy_check:
name: "Clang-tidy check"
runs-on: [self-hosted, Linux, X64, Ubuntu20.04]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build debug binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build debug binaries.
cd build
cmake ..
make -j$THREADS
- name: Run clang-tidy
run: |
source /opt/toolchain-v4/activate
# The results are also written to standard output in order to retain them in the logs
./tools/github/clang-tidy/run-clang-tidy.py -p build -j $THREADS -extra-arg="-DMG_CLANG_TIDY_CHECK" -clang-tidy-binary=/opt/toolchain-v4/bin/clang-tidy "$PWD/src/*" |
tee ./build/full_clang_tidy_output.txt
- name: Summarize clang-tidy results
run: cat ./build/full_clang_tidy_output.txt | ./tools/github/clang-tidy/count_errors.sh

View File

@@ -1,178 +0,0 @@
name: Package All
# TODO(gitbuda): Cleanup docker container if GHA job was canceled.
on: workflow_dispatch
jobs:
centos-7:
runs-on: [self-hosted, DockerMgBuild, X64]
timeout-minutes: 60
steps:
- name: "Set up repository"
uses: actions/checkout@v3
with:
fetch-depth: 0 # Required because of release/get_version.py
- name: "Build package"
run: |
./release/package/run.sh package centos-7
- name: "Upload package"
uses: actions/upload-artifact@v3
with:
name: centos-7
path: build/output/centos-7/memgraph*.rpm
centos-9:
runs-on: [self-hosted, DockerMgBuild, X64]
timeout-minutes: 60
steps:
- name: "Set up repository"
uses: actions/checkout@v3
with:
fetch-depth: 0 # Required because of release/get_version.py
- name: "Build package"
run: |
./release/package/run.sh package centos-9
- name: "Upload package"
uses: actions/upload-artifact@v3
with:
name: centos-9
path: build/output/centos-9/memgraph*.rpm
debian-10:
runs-on: [self-hosted, DockerMgBuild, X64]
timeout-minutes: 60
steps:
- name: "Set up repository"
uses: actions/checkout@v3
with:
fetch-depth: 0 # Required because of release/get_version.py
- name: "Build package"
run: |
./release/package/run.sh package debian-10
- name: "Upload package"
uses: actions/upload-artifact@v3
with:
name: debian-10
path: build/output/debian-10/memgraph*.deb
debian-11:
runs-on: [self-hosted, DockerMgBuild, X64]
timeout-minutes: 60
steps:
- name: "Set up repository"
uses: actions/checkout@v3
with:
fetch-depth: 0 # Required because of release/get_version.py
- name: "Build package"
run: |
./release/package/run.sh package debian-11
- name: "Upload package"
uses: actions/upload-artifact@v3
with:
name: debian-11
path: build/output/debian-11/memgraph*.deb
docker:
runs-on: [self-hosted, DockerMgBuild, X64]
timeout-minutes: 60
steps:
- name: "Set up repository"
uses: actions/checkout@v3
with:
fetch-depth: 0 # Required because of release/get_version.py
- name: "Build package"
run: |
cd release/package
./run.sh package debian-11 --for-docker
./run.sh docker
- name: "Upload package"
uses: actions/upload-artifact@v3
with:
name: docker
path: build/output/docker/memgraph*.tar.gz
ubuntu-1804:
runs-on: [self-hosted, DockerMgBuild, X64]
timeout-minutes: 60
steps:
- name: "Set up repository"
uses: actions/checkout@v3
with:
fetch-depth: 0 # Required because of release/get_version.py
- name: "Build package"
run: |
./release/package/run.sh package ubuntu-18.04
- name: "Upload package"
uses: actions/upload-artifact@v3
with:
name: ubuntu-1804
path: build/output/ubuntu-18.04/memgraph*.deb
ubuntu-2004:
runs-on: [self-hosted, DockerMgBuild, X64]
timeout-minutes: 60
steps:
- name: "Set up repository"
uses: actions/checkout@v3
with:
fetch-depth: 0 # Required because of release/get_version.py
- name: "Build package"
run: |
./release/package/run.sh package ubuntu-20.04
- name: "Upload package"
uses: actions/upload-artifact@v3
with:
name: ubuntu-2004
path: build/output/ubuntu-20.04/memgraph*.deb
ubuntu-2204:
runs-on: [self-hosted, DockerMgBuild, X64]
timeout-minutes: 60
steps:
- name: "Set up repository"
uses: actions/checkout@v3
with:
fetch-depth: 0 # Required because of release/get_version.py
- name: "Build package"
run: |
./release/package/run.sh package ubuntu-22.04
- name: "Upload package"
uses: actions/upload-artifact@v3
with:
name: ubuntu-2204
path: build/output/ubuntu-22.04/memgraph*.deb
debian-11-platform:
runs-on: [self-hosted, DockerMgBuild, X64]
timeout-minutes: 60
steps:
- name: "Set up repository"
uses: actions/checkout@v3
with:
fetch-depth: 0 # Required because of release/get_version.py
- name: "Build package"
run: |
./release/package/run.sh package debian-11 --for-platform
- name: "Upload package"
uses: actions/upload-artifact@v3
with:
name: debian-11-platform
path: build/output/debian-11/memgraph*.deb
debian-11-arm:
runs-on: [self-hosted, DockerMgBuild, ARM64, strange]
timeout-minutes: 60
steps:
- name: "Set up repository"
uses: actions/checkout@v3
with:
fetch-depth: 0 # Required because of release/get_version.py
- name: "Build package"
run: |
./release/package/run.sh package debian-11-arm
- name: "Upload package"
uses: actions/upload-artifact@v3
with:
name: debian-11-arm
path: build/output/debian-11-arm/memgraph*.deb

View File

@@ -1,315 +0,0 @@
name: Release CentOS 8
on:
workflow_dispatch:
schedule:
- cron: "0 1 * * *"
jobs:
community_build:
name: "Community build"
runs-on: [self-hosted, Linux, X64, CentOS8]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
timeout-minutes: 960
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build community binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build community binaries.
cd build
cmake -DCMAKE_BUILD_TYPE=release -DMG_ENTERPRISE=OFF ..
make -j$THREADS
- name: Run unit tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run unit tests.
cd build
ctest -R memgraph__unit --output-on-failure
coverage_build:
name: "Coverage build"
runs-on: [self-hosted, Linux, X64, CentOS8]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build coverage binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build coverage binaries.
cd build
cmake -DTEST_COVERAGE=ON ..
make -j$THREADS memgraph__unit
- name: Run unit tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run unit tests.
cd build
ctest -R memgraph__unit --output-on-failure
- name: Compute code coverage
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Compute code coverage.
cd tools/github
./coverage_convert
# Package code coverage.
cd generated
tar -czf code_coverage.tar.gz coverage.json html report.json summary.rmu
- name: Save code coverage
uses: actions/upload-artifact@v3
with:
name: "Code coverage"
path: tools/github/generated/code_coverage.tar.gz
debug_build:
name: "Debug build"
runs-on: [self-hosted, Linux, X64, CentOS8]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build debug binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build debug binaries.
cd build
cmake ..
make -j$THREADS
- name: Run leftover CTest tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run leftover CTest tests (all except unit and benchmark tests).
cd build
ctest -E "(memgraph__unit|memgraph__benchmark)" --output-on-failure
- name: Run drivers tests
run: |
./tests/drivers/run.sh
- name: Run integration tests
run: |
cd tests/integration
for name in *; do
if [ ! -d $name ]; then continue; fi
pushd $name >/dev/null
echo "Running: $name"
if [ -x prepare.sh ]; then
./prepare.sh
fi
if [ -x runner.py ]; then
./runner.py
elif [ -x runner.sh ]; then
./runner.sh
fi
echo
popd >/dev/null
done
- name: Run cppcheck and clang-format
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run cppcheck and clang-format.
cd tools/github
./cppcheck_and_clang_format diff
- name: Save cppcheck and clang-format errors
uses: actions/upload-artifact@v3
with:
name: "Code coverage"
path: tools/github/cppcheck_and_clang_format.txt
release_build:
name: "Release build"
runs-on: [self-hosted, Linux, X64, CentOS8]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
timeout-minutes: 960
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build release binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build release binaries.
cd build
cmake -DCMAKE_BUILD_TYPE=release ..
make -j$THREADS
- name: Create enterprise RPM package
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
cd build
# create mgconsole
# we use the -B to force the build
make -j$THREADS -B mgconsole
# Create enterprise RPM package.
mkdir output && cd output
cpack -G RPM --config ../CPackConfig.cmake
rpmlint memgraph*.rpm
- name: Save enterprise RPM package
uses: actions/upload-artifact@v3
with:
name: "Enterprise RPM package"
path: build/output/memgraph*.rpm
- name: Run micro benchmark tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run micro benchmark tests.
cd build
# The `eval` benchmark needs a large stack limit.
ulimit -s 262144
ctest -R memgraph__benchmark -V
- name: Run macro benchmark tests
run: |
cd tests/macro_benchmark
./harness QuerySuite MemgraphRunner \
--groups aggregation 1000_create unwind_create dense_expand match \
--no-strict
- name: Run parallel macro benchmark tests
run: |
cd tests/macro_benchmark
./harness QueryParallelSuite MemgraphRunner \
--groups aggregation_parallel create_parallel bfs_parallel \
--num-database-workers 9 --num-clients-workers 30 \
--no-strict
- name: Run GQL Behave tests
run: |
cd tests/gql_behave
./continuous_integration
- name: Save quality assurance status
uses: actions/upload-artifact@v3
with:
name: "GQL Behave Status"
path: |
tests/gql_behave/gql_behave_status.csv
tests/gql_behave/gql_behave_status.html
- name: Run unit tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run unit tests.
cd build
ctest -R memgraph__unit --output-on-failure
- name: Run e2e tests
run: |
# TODO(gitbuda): Setup mgclient and pymgclient properly.
cd tests
./setup.sh
source ve3/bin/activate
cd e2e
LD_LIBRARY_PATH=$LD_LIBRARY_PATH:../../libs/mgclient/lib python runner.py --workloads-root-directory .
- name: Run stress test (plain)
run: |
cd tests/stress
./continuous_integration
- name: Run stress test (SSL)
run: |
cd tests/stress
./continuous_integration --use-ssl
- name: Run stress test (large)
run: |
cd tests/stress
./continuous_integration --large-dataset
- name: Run durability test (plain)
run: |
cd tests/stress
source ve3/bin/activate
python3 durability --num-steps 5
- name: Run durability test (large)
run: |
cd tests/stress
source ve3/bin/activate
python3 durability --num-steps 20

View File

@@ -1,356 +0,0 @@
name: Release Debian 10
on:
workflow_dispatch:
schedule:
- cron: "0 1 * * *"
jobs:
community_build:
name: "Community build"
runs-on: [self-hosted, Linux, X64, Debian10]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
timeout-minutes: 960
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build community binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build community binaries.
cd build
cmake -DCMAKE_BUILD_TYPE=release -DMG_ENTERPRISE=OFF ..
make -j$THREADS
- name: Run unit tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run unit tests.
cd build
ctest -R memgraph__unit --output-on-failure
coverage_build:
name: "Coverage build"
runs-on: [self-hosted, Linux, X64, Debian10]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build coverage binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build coverage binaries.
cd build
cmake -DTEST_COVERAGE=ON ..
make -j$THREADS memgraph__unit
- name: Run unit tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run unit tests.
cd build
ctest -R memgraph__unit --output-on-failure
- name: Compute code coverage
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Compute code coverage.
cd tools/github
./coverage_convert
# Package code coverage.
cd generated
tar -czf code_coverage.tar.gz coverage.json html report.json summary.rmu
- name: Save code coverage
uses: actions/upload-artifact@v3
with:
name: "Code coverage"
path: tools/github/generated/code_coverage.tar.gz
debug_build:
name: "Debug build"
runs-on: [self-hosted, Linux, X64, Debian10]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build debug binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build debug binaries.
cd build
cmake ..
make -j$THREADS
- name: Run leftover CTest tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run leftover CTest tests (all except unit and benchmark tests).
cd build
ctest -E "(memgraph__unit|memgraph__benchmark)" --output-on-failure
- name: Run drivers tests
run: |
./tests/drivers/run.sh
- name: Run integration tests
run: |
cd tests/integration
for name in *; do
if [ ! -d $name ]; then continue; fi
pushd $name >/dev/null
echo "Running: $name"
if [ -x prepare.sh ]; then
./prepare.sh
fi
if [ -x runner.py ]; then
./runner.py
elif [ -x runner.sh ]; then
./runner.sh
fi
echo
popd >/dev/null
done
- name: Run cppcheck and clang-format
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run cppcheck and clang-format.
cd tools/github
./cppcheck_and_clang_format diff
- name: Save cppcheck and clang-format errors
uses: actions/upload-artifact@v3
with:
name: "Code coverage"
path: tools/github/cppcheck_and_clang_format.txt
release_build:
name: "Release build"
runs-on: [self-hosted, Linux, X64, Debian10]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
timeout-minutes: 960
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build release binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build release binaries.
cd build
cmake -DCMAKE_BUILD_TYPE=release ..
make -j$THREADS
- name: Create enterprise DEB package
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
cd build
# create mgconsole
# we use the -B to force the build
make -j$THREADS -B mgconsole
# Create enterprise DEB package.
mkdir output && cd output
cpack -G DEB --config ../CPackConfig.cmake
- name: Save enterprise DEB package
uses: actions/upload-artifact@v3
with:
name: "Enterprise DEB package"
path: build/output/memgraph*.deb
- name: Run micro benchmark tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run micro benchmark tests.
cd build
# The `eval` benchmark needs a large stack limit.
ulimit -s 262144
ctest -R memgraph__benchmark -V
- name: Run macro benchmark tests
run: |
cd tests/macro_benchmark
./harness QuerySuite MemgraphRunner \
--groups aggregation 1000_create unwind_create dense_expand match \
--no-strict
- name: Run parallel macro benchmark tests
run: |
cd tests/macro_benchmark
./harness QueryParallelSuite MemgraphRunner \
--groups aggregation_parallel create_parallel bfs_parallel \
--num-database-workers 9 --num-clients-workers 30 \
--no-strict
- name: Run GQL Behave tests
run: |
cd tests/gql_behave
./continuous_integration
- name: Save quality assurance status
uses: actions/upload-artifact@v3
with:
name: "GQL Behave Status"
path: |
tests/gql_behave/gql_behave_status.csv
tests/gql_behave/gql_behave_status.html
- name: Run unit tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run unit tests.
cd build
ctest -R memgraph__unit --output-on-failure
- name: Run e2e tests
run: |
# TODO(gitbuda): Setup mgclient and pymgclient properly.
cd tests
./setup.sh
source ve3/bin/activate
cd e2e
LD_LIBRARY_PATH=$LD_LIBRARY_PATH:../../libs/mgclient/lib python runner.py --workloads-root-directory .
- name: Run stress test (plain)
run: |
cd tests/stress
./continuous_integration
- name: Run stress test (SSL)
run: |
cd tests/stress
./continuous_integration --use-ssl
- name: Run stress test (large)
run: |
cd tests/stress
./continuous_integration --large-dataset
- name: Run durability test (plain)
run: |
cd tests/stress
source ve3/bin/activate
python3 durability --num-steps 5
- name: Run durability test (large)
run: |
cd tests/stress
source ve3/bin/activate
python3 durability --num-steps 20
release_jepsen_test:
name: "Release Jepsen Test"
runs-on: [self-hosted, Linux, X64, Debian10, JepsenControl]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
timeout-minutes: 60
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build release binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build only memgraph release binary.
cd build
cmake -DCMAKE_BUILD_TYPE=release ..
make -j$THREADS memgraph
- name: Run Jepsen tests
run: |
cd tests/jepsen
./run.sh test --binary ../../build/memgraph --run-args "test-all --node-configs resources/node-config.edn" --ignore-run-stdout-logs --ignore-run-stderr-logs
- name: Save Jepsen report
uses: actions/upload-artifact@v3
if: ${{ always() }}
with:
name: "Jepsen Report"
path: tests/jepsen/Jepsen.tar.gz

View File

@@ -1,69 +0,0 @@
name: Publish Docker images
on:
workflow_dispatch:
inputs:
version:
description: "Memgraph binary version to publish on DockerHub."
required: true
force_release:
type: boolean
required: false
default: false
jobs:
docker_publish:
runs-on: ubuntu-latest
env:
DOCKER_ORGANIZATION_NAME: memgraph
DOCKER_REPOSITORY_NAME: memgraph
steps:
- name: Checkout
uses: actions/checkout@v3
- name: Set up QEMU
uses: docker/setup-qemu-action@v1
- name: Set up Docker Buildx
id: buildx
uses: docker/setup-buildx-action@v1
- name: Log in to Docker Hub
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_PASSWORD }}
- name: Download memgraph binary
run: |
cd release/docker
curl -L https://download.memgraph.com/memgraph/v${{ github.event.inputs.version }}/debian-11/memgraph_${{ github.event.inputs.version }}-1_amd64.deb > memgraph-amd64.deb
curl -L https://download.memgraph.com/memgraph/v${{ github.event.inputs.version }}/debian-11-aarch64/memgraph_${{ github.event.inputs.version }}-1_arm64.deb > memgraph-arm64.deb
- name: Check if specified version is already pushed
run: |
EXISTS=$(docker manifest inspect $DOCKER_ORGANIZATION_NAME/$DOCKER_REPOSITORY_NAME:${{ github.event.inputs.version }} > /dev/null; echo $?)
echo $EXISTS
if [[ ${EXISTS} -eq 0 ]]; then
echo 'The specified version has been already released to DockerHub.'
if [[ ${{ github.event.inputs.force_release }} = true ]]; then
echo 'Forcing the release!'
else
echo 'Stopping the release!'
exit 1
fi
else
echo 'All good the specified version has not been release to DockerHub.'
fi
- name: Build & push docker images
run: |
cd release/docker
docker buildx build \
--build-arg BINARY_NAME="memgraph-" \
--build-arg EXTENSION="deb" \
--platform linux/amd64,linux/arm64 \
--tag $DOCKER_ORGANIZATION_NAME/$DOCKER_REPOSITORY_NAME:${{ github.event.inputs.version }} \
--tag $DOCKER_ORGANIZATION_NAME/$DOCKER_REPOSITORY_NAME:latest \
--file memgraph_deb.dockerfile \
--push .

View File

@@ -1,314 +0,0 @@
name: Release Ubuntu 20.04
on:
workflow_dispatch:
schedule:
- cron: "0 1 * * *"
jobs:
community_build:
name: "Community build"
runs-on: [self-hosted, Linux, X64, Ubuntu20.04]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
timeout-minutes: 960
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build community binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build community binaries.
cd build
cmake -DCMAKE_BUILD_TYPE=release -DMG_ENTERPRISE=OFF ..
make -j$THREADS
- name: Run unit tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run unit tests.
cd build
ctest -R memgraph__unit --output-on-failure
coverage_build:
name: "Coverage build"
runs-on: [self-hosted, Linux, X64, Ubuntu20.04]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build coverage binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build coverage binaries.
cd build
cmake -DTEST_COVERAGE=ON ..
make -j$THREADS memgraph__unit
- name: Run unit tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run unit tests.
cd build
ctest -R memgraph__unit --output-on-failure
- name: Compute code coverage
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Compute code coverage.
cd tools/github
./coverage_convert
# Package code coverage.
cd generated
tar -czf code_coverage.tar.gz coverage.json html report.json summary.rmu
- name: Save code coverage
uses: actions/upload-artifact@v3
with:
name: "Code coverage"
path: tools/github/generated/code_coverage.tar.gz
debug_build:
name: "Debug build"
runs-on: [self-hosted, Linux, X64, Ubuntu20.04]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build debug binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build debug binaries.
cd build
cmake ..
make -j$THREADS
- name: Run leftover CTest tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run leftover CTest tests (all except unit and benchmark tests).
cd build
ctest -E "(memgraph__unit|memgraph__benchmark)" --output-on-failure
- name: Run drivers tests
run: |
./tests/drivers/run.sh
- name: Run integration tests
run: |
cd tests/integration
for name in *; do
if [ ! -d $name ]; then continue; fi
pushd $name >/dev/null
echo "Running: $name"
if [ -x prepare.sh ]; then
./prepare.sh
fi
if [ -x runner.py ]; then
./runner.py
elif [ -x runner.sh ]; then
./runner.sh
fi
echo
popd >/dev/null
done
- name: Run cppcheck and clang-format
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run cppcheck and clang-format.
cd tools/github
./cppcheck_and_clang_format diff
- name: Save cppcheck and clang-format errors
uses: actions/upload-artifact@v3
with:
name: "Code coverage"
path: tools/github/cppcheck_and_clang_format.txt
release_build:
name: "Release build"
runs-on: [self-hosted, Linux, X64, Ubuntu20.04]
env:
THREADS: 24
MEMGRAPH_ENTERPRISE_LICENSE: ${{ secrets.MEMGRAPH_ENTERPRISE_LICENSE }}
MEMGRAPH_ORGANIZATION_NAME: ${{ secrets.MEMGRAPH_ORGANIZATION_NAME }}
timeout-minutes: 960
steps:
- name: Set up repository
uses: actions/checkout@v3
with:
# Number of commits to fetch. `0` indicates all history for all
# branches and tags. (default: 1)
fetch-depth: 0
- name: Build release binaries
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Initialize dependencies.
./init
# Build release binaries.
cd build
cmake -DCMAKE_BUILD_TYPE=release ..
make -j$THREADS
- name: Create enterprise DEB package
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
cd build
# create mgconsole
# we use the -B to force the build
make -j$THREADS -B mgconsole
# Create enterprise DEB package.
mkdir output && cd output
cpack -G DEB --config ../CPackConfig.cmake
- name: Save enterprise DEB package
uses: actions/upload-artifact@v3
with:
name: "Enterprise DEB package"
path: build/output/memgraph*.deb
- name: Run micro benchmark tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run micro benchmark tests.
cd build
# The `eval` benchmark needs a large stack limit.
ulimit -s 262144
ctest -R memgraph__benchmark -V
- name: Run macro benchmark tests
run: |
cd tests/macro_benchmark
./harness QuerySuite MemgraphRunner \
--groups aggregation 1000_create unwind_create dense_expand match \
--no-strict
- name: Run parallel macro benchmark tests
run: |
cd tests/macro_benchmark
./harness QueryParallelSuite MemgraphRunner \
--groups aggregation_parallel create_parallel bfs_parallel \
--num-database-workers 9 --num-clients-workers 30 \
--no-strict
- name: Run GQL Behave tests
run: |
cd tests/gql_behave
./continuous_integration
- name: Save quality assurance status
uses: actions/upload-artifact@v3
with:
name: "GQL Behave Status"
path: |
tests/gql_behave/gql_behave_status.csv
tests/gql_behave/gql_behave_status.html
- name: Run unit tests
run: |
# Activate toolchain.
source /opt/toolchain-v4/activate
# Run unit tests.
cd build
ctest -R memgraph__unit --output-on-failure
- name: Run e2e tests
run: |
# TODO(gitbuda): Setup mgclient and pymgclient properly.
cd tests
./setup.sh
source ve3/bin/activate
cd e2e
LD_LIBRARY_PATH=$LD_LIBRARY_PATH:../../libs/mgclient/lib python runner.py --workloads-root-directory .
- name: Run stress test (plain)
run: |
cd tests/stress
./continuous_integration
- name: Run stress test (SSL)
run: |
cd tests/stress
./continuous_integration --use-ssl
- name: Run stress test (large)
run: |
cd tests/stress
./continuous_integration --large-dataset
- name: Run durability test (plain)
run: |
cd tests/stress
source ve3/bin/activate
python3 durability --num-steps 5
- name: Run durability test (large)
run: |
cd tests/stress
source ve3/bin/activate
python3 durability --num-steps 20

12
.gitignore vendored
View File

@@ -23,8 +23,6 @@ cmake-build-*
cmake/DownloadProject/
dist/
src/query/frontend/opencypher/generated/
src/query/v2/frontend/opencypher/generated/
src/parser/opencypher/generated
tags
ve/
ve3/
@@ -52,25 +50,15 @@ src/distributed/pull_produce_rpc_messages.hpp
src/distributed/storage_gc_rpc_messages.hpp
src/distributed/token_sharing_rpc_messages.hpp
src/distributed/updates_rpc_messages.hpp
src/query/v2/frontend/ast/ast.hpp
src/query/frontend/ast/ast.hpp
src/storage/v3/bindings/ast/ast.hpp
src/query/distributed/frontend/ast/ast_serialization.hpp
src/query/v2/distributed/frontend/ast/ast_serialization.hpp
src/durability/distributed/state_delta.hpp
src/durability/single_node/state_delta.hpp
src/durability/single_node_ha/state_delta.hpp
src/query/frontend/semantic/symbol.hpp
src/query/v2/frontend/semantic/symbol.hpp
src/expr/semantic/symbol.hpp
src/query/distributed/frontend/semantic/symbol_serialization.hpp
src/query/v2/distributed/frontend/semantic/symbol_serialization.hpp
src/query/distributed/plan/ops.hpp
src/query/v2/distributed/plan/ops.hpp
src/query/plan/operator.hpp
src/query/v2/plan/operator.hpp
src/parser/opencypher/generated
src/expr/semantic/symbol.hpp
src/raft/log_entry.hpp
src/raft/raft_rpc_messages.hpp
src/raft/snapshot_metadata.hpp

View File

@@ -1,21 +0,0 @@
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v2.3.0
hooks:
- id: check-yaml
- id: end-of-file-fixer
- id: trailing-whitespace
- repo: https://github.com/psf/black
rev: 22.10.0
hooks:
- id: black
- repo: https://github.com/pycqa/isort
rev: 5.10.1
hooks:
- id: isort
name: isort (python)
args: ["--profile", "black"]
- repo: https://github.com/pre-commit/mirrors-clang-format
rev: v13.0.0
hooks:
- id: clang-format

172
.ycm_extra_conf.py Normal file
View File

@@ -0,0 +1,172 @@
import os
import os.path
import fnmatch
import logging
import ycm_core
BASE_FLAGS = [
'-Wall',
'-Wextra',
'-Werror',
'-Wno-long-long',
'-Wno-variadic-macros',
'-fexceptions',
'-ferror-limit=10000',
'-std=c++1z',
'-xc++',
'-I/usr/lib/',
'-I/usr/include/',
'-I./src',
'-I./include',
'-I./libs/fmt',
'-I./libs/yaml-cpp',
'-I./libs/glog/include',
'-I./libs/googletest/googletest/include',
'-I./libs/googletest/googlemock/include',
'-I./libs/benchmark/include',
'-I./libs/cereal/include',
# We include cppitertools headers directly from libs directory.
'-I./libs',
'-I./libs/rapidcheck/include',
'-I./libs/antlr4/runtime/Cpp/runtime/src',
'-I./libs/gflags/include',
'-I./experimental/distributed/src',
'-I./libs/postgresql/include',
'-I./libs/bzip2',
'-I./libs/zlib',
'-I./libs/rocksdb/include',
'-I./libs/librdkafka/include/librdkafka',
'-I./build/include'
]
SOURCE_EXTENSIONS = [
'.cpp',
'.cxx',
'.cc',
'.c',
'.m',
'.mm'
]
HEADER_EXTENSIONS = [
'.h',
'.hxx',
'.hpp',
'.hh'
]
# set the working directory of YCMD to be this file
os.chdir(os.path.dirname(os.path.realpath(__file__)))
def IsHeaderFile(filename):
extension = os.path.splitext(filename)[1]
return extension in HEADER_EXTENSIONS
def GetCompilationInfoForFile(database, filename):
if IsHeaderFile(filename):
basename = os.path.splitext(filename)[0]
for extension in SOURCE_EXTENSIONS:
replacement_file = basename + extension
if os.path.exists(replacement_file):
compilation_info = database.GetCompilationInfoForFile(replacement_file)
if compilation_info.compiler_flags_:
return compilation_info
return None
return database.GetCompilationInfoForFile(filename)
def FindNearest(path, target):
candidate = os.path.join(path, target)
if(os.path.isfile(candidate) or os.path.isdir(candidate)):
logging.info("Found nearest " + target + " at " + candidate)
return candidate;
else:
parent = os.path.dirname(os.path.abspath(path));
if(parent == path):
raise RuntimeError("Could not find " + target);
return FindNearest(parent, target)
def MakeRelativePathsInFlagsAbsolute(flags, working_directory):
if not working_directory:
return list(flags)
new_flags = []
make_next_absolute = False
path_flags = [ '-isystem', '-I', '-iquote', '--sysroot=' ]
for flag in flags:
new_flag = flag
if make_next_absolute:
make_next_absolute = False
if not flag.startswith('/'):
new_flag = os.path.join(working_directory, flag)
for path_flag in path_flags:
if flag == path_flag:
make_next_absolute = True
break
if flag.startswith(path_flag):
path = flag[ len(path_flag): ]
new_flag = path_flag + os.path.join(working_directory, path)
break
if new_flag:
new_flags.append(new_flag)
return new_flags
def FlagsForClangComplete(root):
try:
clang_complete_path = FindNearest(root, '.clang_complete')
clang_complete_flags = open(clang_complete_path, 'r').read().splitlines()
return clang_complete_flags
except:
return None
def FlagsForInclude(root):
try:
include_path = FindNearest(root, 'include')
flags = []
for dirroot, dirnames, filenames in os.walk(include_path):
for dir_path in dirnames:
real_path = os.path.join(dirroot, dir_path)
flags = flags + ["-I" + real_path]
return flags
except:
return None
def FlagsForCompilationDatabase(root, filename):
try:
compilation_db_path = FindNearest(root, 'compile_commands.json')
compilation_db_dir = os.path.dirname(compilation_db_path)
logging.info("Set compilation database directory to " + compilation_db_dir)
compilation_db = ycm_core.CompilationDatabase(compilation_db_dir)
if not compilation_db:
logging.info("Compilation database file found but unable to load")
return None
compilation_info = GetCompilationInfoForFile(compilation_db, filename)
if not compilation_info:
logging.info("No compilation info for " + filename + " in compilation database")
return None
return MakeRelativePathsInFlagsAbsolute(
compilation_info.compiler_flags_,
compilation_info.compiler_working_dir_)
except:
return None
def FlagsForFile(filename):
root = os.path.realpath(filename);
compilation_db_flags = FlagsForCompilationDatabase(root, filename)
if compilation_db_flags:
final_flags = compilation_db_flags
else:
final_flags = BASE_FLAGS
clang_flags = FlagsForClangComplete(root)
if clang_flags:
final_flags = final_flags + clang_flags
include_flags = FlagsForInclude(root)
if include_flags:
final_flags = final_flags + include_flags
return {
'flags': final_flags,
'do_cache': True
}

View File

@@ -1,5 +1,298 @@
Change Log for all versions of Memgraph can be found on-line at
https://docs.memgraph.com/memgraph/changelog
# Change Log
All the updates to the Change Log can be made in the following repository:
https://github.com/memgraph/docs
## v0.50.0
### Breaking Changes
* [Enterprise Ed.] Remove support for Kafka streams.
* Snapshot and write-ahead log format changed (not backward compatible).
* Removed support for unique constraints.
* Label indices aren't created automatically, create them explicitly instead.
* Renamed several database flags. Please see the configuration file for a list of current flags.
### Major Features and Improvements
* [Enterprise Ed.] Add support for auth module.
* [Enterprise Ed.] LDAP support migrated to auth module.
* Implemented new graph storage engine.
* Add support for disabling properties on edges.
* Add support for existence constraints.
* Add support for custom openCypher procedures using a C API.
* Support loading query modules implementing read-only procedures.
* Add `CALL <procedure> YIELD <result>` syntax for invoking loaded procedures.
* Add `CREATE INDEX ON :Label` for creating label indices.
* Add `DROP INDEX ON :Label` for dropping label indices.
* Add `DUMP DATABASE` clause to openCypher.
* Add functions for treating character strings as byte strings.
### Bug Fixes and Other Changes
* Fix several memory management bugs.
* Reduce memory usage in query execution.
* Fix bug that crashes the database when `EXPLAIN` is used.
## v0.15.0
### Breaking Changes
* Snapshot and write-ahead log format changed (not backward compatible).
* `indexInfo()` function replaced with `SHOW INDEX INFO` syntax.
* Removed support for unique index. Use unique constraints instead.
* `CREATE UNIQUE INDEX ON :label (property)` replaced with `CREATE CONSTRAINT ON (n:label) ASSERT n.property IS UNIQUE`.
* Changed semantics for `COUNTER` openCypher function.
### Major Features and Improvements
* [Enterprise Ed.] Add new privilege, `STATS` for accessing storage info.
* [Enterprise Ed.] LDAP authentication and authorization support.
* [Enterprise Ed.] Add audit logging feature.
* Add multiple properties unique constraint which replace unique indices.
* Add `SHOW STORAGE INFO` feature.
* Add `PROFILE` clause to openCypher.
* Add `CREATE CONSTRAINT` clause to openCypher.
* Add `DROP CONSTRAINT` clause to openCypher.
* Add `SHOW CONSTRAINT INFO` feature.
* Add `uniformSample` function to openCypher.
* Add regex matching to openCypher.
### Bug Fixes and Other Changes
* Fix bug in explicit transaction handling.
* Fix bug in edge filtering by edge type and destination.
* Fix bug in query comment parsing.
* Fix bug in query symbol table.
* Fix OpenSSL memory leaks.
* Make authentication case insensitive.
* Remove `COALESCE` function.
* Add movie tutorial.
* Add backpacking tutorial.
## v0.14.0
### Breaking Changes
* Write-ahead log format changed (not backward compatible).
### Major Features and Improvements
* [Enterprise Ed.] Reduce memory usage in distributed usage.
* Add `DROP INDEX` feature.
* Improve SSL error messages.
### Bug Fixes and Other Changes
* [Enterprise Ed.] Fix issues with reading and writing in a distributed query.
* Correctly handle an edge case with unique constraint checks.
* Fix a minor issue with `mg_import_csv`.
* Fix an issue with `EXPLAIN`.
## v0.13.0
### Breaking Changes
* Write-ahead log format changed (not backward compatible).
* Snapshot format changed (not backward compatible).
### Major Features and Improvements
* [Enterprise Ed.] Authentication and authorization support.
* [Enterprise Ed.] Kafka integration.
* [Enterprise Ed.] Support dynamic worker addition in distributed.
* Reduce memory usage and improve overall performance.
* Add `CREATE UNIQUE INDEX` clause to openCypher.
* Add `EXPLAIN` clause to openCypher.
* Add `inDegree` and `outDegree` functions to openCypher.
* Improve BFS performance when both endpoints are known.
* Add new `node-label`, `relationship-type` and `quote` options to
`mg_import_csv` tool.
* Reduce memory usage of `mg_import_csv`.
### Bug Fixes and Other Changes
* [Enterprise Ed.] Fix an edge case in distributed index creation.
* [Enterprise Ed.] Fix issues with Cartesian in distributed queries.
* Correctly handle large messages in Bolt protocol.
* Fix issues when handling explicitly started transactions in queries.
* Allow openCypher keywords to be used as variable names.
* Revise and make user visible error messages consistent.
* Improve aborting time consuming execution.
## v0.12.0
### Breaking Changes
* Snapshot format changed (not backward compatible).
### Major Features and Improvements
* Improved Id Cypher function.
* Added string functions to openCypher (`lTrim`, `left`, `rTrim`, `replace`,
`reverse`, `right`, `split`, `substring`, `toLower`, `toUpper`, `trim`).
* Added `timestamp` function to openCypher.
* Added support for dynamic property access with `[]` operator.
## v0.11.0
### Major Features and Improvements
* [Enterprise Ed.] Improve Cartesian support in distributed queries.
* [Enterprise Ed.] Improve distributed execution of BFS.
* [Enterprise Ed.] Dynamic graph partitioner added.
* Static nodes/edges id generators exposed through the Id Cypher function.
* Properties on disk added.
* Telemetry added.
* SSL support added.
* `toString` function added.
### Bug Fixes and Other Changes
* Document issues with Docker on OS X.
* Add BFS and Dijkstra's algorithm examples to documentation.
## v0.10.0
### Breaking Changes
* Snapshot format changed (not backward compatible).
### Major Features and Improvements
* [Enterprise Ed.] Distributed storage and execution.
* `reduce` and `single` functions added to openCypher.
* `wShortest` edge expansion added to openCypher.
* Support packaging RPM on CentOS 7.
### Bug Fixes and Other Changes
* Report an error if updating a deleted element.
* Log an error if reading info on available memory fails.
* Fix a bug when `MATCH` would stop matching if a result was empty, but later
results still contain data to be matched. The simplest case of this was the
query: `UNWIND [1,2,3] AS x MATCH (n :Label {prop: x}) RETURN n`. If there
was no node `(:Label {prop: 1})`, then the `MATCH` wouldn't even try to find
for `x` being 2 or 3.
* Report an error if trying to compare a property value with something that
cannot be stored in a property.
* Fix crashes in some obscure cases.
* Commit log automatically garbage collected.
* Add minor performance improvements.
## v0.9.0
### Breaking Changes
* Snapshot format changed (not backward compatible).
* Snapshot configuration flags changed, general durability flags added.
### Major Features and Improvements
* Write-ahead log added.
* `nodes` and `relationships` functions added.
* `UNION` and `UNION ALL` is implemented.
* Concurrent index creation is now enabled.
### Bug Fixes and Other Changes
## v0.8.0
### Major Features and Improvements
* CASE construct (without aggregations).
* Named path support added.
* Maps can now be stored as node/edge properties.
* Map indexing supported.
* `rand` function added.
* `assert` function added.
* `counter` and `counterSet` functions added.
* `indexInfo` function added.
* `collect` aggregation now supports Map collection.
* Changed the BFS syntax.
### Bug Fixes and Other Changes
* Use \u to specify 4 digit codepoint and \U for 8 digit
* Keywords appearing in header (named expressions) keep original case.
* Our Bolt protocol implementation is now completely compatible with the protocol version 1 specification. (https://boltprotocol.org/v1/)
* Added a log warning when running out of memory and the `memory_warning_threshold` flag
* Edges are no longer additionally filtered after expansion.
## v0.7.0
### Major Features and Improvements
* Variable length path `MATCH`.
* Explicitly started transactions (multi-query transactions).
* Map literal.
* Query parameters (except for parameters in place of property maps).
* `all` function in openCypher.
* `degree` function in openCypher.
* User specified transaction execution timeout.
### Bug Fixes and Other Changes
* Concurrent `BUILD INDEX` deadlock now returns an error to the client.
* A `MATCH` preceeded by `OPTIONAL MATCH` expansion inconsistencies.
* High concurrency Antlr parsing bug.
* Indexing improvements.
* Query stripping and caching speedups.
## v0.6.0
### Major Features and Improvements
* AST caching.
* Label + property index support.
* Different logging setup & format.
## v0.5.0
### Major Features and Improvements
* Use label indexes to speed up querying.
* Generate multiple query plans and use the cost estimator to select the best.
* Snapshots & Recovery.
* Abandon old yaml configuration and migrate to gflags.
* Query stripping & AST caching support.
### Bug Fixes and Other Changes
* Fixed race condition in MVCC. Hints exp+aborted race condition prevented.
* Fixed conceptual bug in MVCC GC. Evaluate old records w.r.t. the oldest.
transaction's id AND snapshot.
* User friendly error messages thrown from the query engine.
## Build 837
### Bug Fixes and Other Changes
* List indexing supported with preceeding IN (for example in query `RETURN 1 IN [[1,2]][0]`).
## Build 825
### Major Features and Improvements
* RETURN *, count(*), OPTIONAL MATCH, UNWIND, DISTINCT (except DISTINCT in aggregate functions), list indexing and slicing, escaped labels, IN LIST operator, range function.
### Bug Fixes and Other Changes
* TCP_NODELAY -> import should be faster.
* Clear hint bits.
## Build 783
### Major Features and Improvements
* SKIP, LIMIT, ORDER BY.
* Math functions.
* Initial support for MERGE clause.
### Bug Fixes and Other Changes
* Unhandled Lock Timeout Exception.
## Build 755
### Major Features and Improvements
* MATCH, CREATE, WHERE, SET, REMOVE, DELETE.

View File

@@ -35,125 +35,16 @@ else()
message(FATAL_ERROR "Couldn't find clang and/or clang++!")
endif()
# Get current commit hash.
execute_process(
OUTPUT_VARIABLE COMMIT_HASH
COMMAND git rev-parse --short HEAD
)
string(STRIP ${COMMIT_HASH} COMMIT_HASH)
# -----------------------------------------------------------------------------
project(memgraph)
# Install licenses.
install(DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/licenses/
DESTINATION share/doc/memgraph)
# For more information about how to release a new version of Memgraph, see
# `release/README.md`.
# Option that is used to specify which version of Memgraph should be built. The
# default is `ON` which causes the build system to build Memgraph Enterprise.
# Memgraph Community is built if explicitly set to `OFF`.
option(MG_ENTERPRISE "Build Memgraph Enterprise Edition" ON)
# Set the current version here to override the automatic version detection. The
# version must be specified as `X.Y.Z`. Primarily used when building new patch
# versions.
set(MEMGRAPH_OVERRIDE_VERSION "")
# Custom suffix that this version should have. The suffix can be any arbitrary
# string. Primarily used when building a version for a specific customer.
set(MEMGRAPH_OVERRIDE_VERSION_SUFFIX "")
# Variables used to generate the versions.
if (MG_ENTERPRISE)
set(get_version_offering "")
else()
set(get_version_offering "--open-source")
endif()
set(get_version_script "${CMAKE_CURRENT_SOURCE_DIR}/release/get_version.py")
# Get version that should be used in the binary.
execute_process(
OUTPUT_VARIABLE MEMGRAPH_VERSION
RESULT_VARIABLE MEMGRAPH_VERSION_RESULT
COMMAND "${get_version_script}" ${get_version_offering}
"${MEMGRAPH_OVERRIDE_VERSION}"
"${MEMGRAPH_OVERRIDE_VERSION_SUFFIX}"
"--memgraph-root-dir"
"${CMAKE_CURRENT_SOURCE_DIR}"
)
if(MEMGRAPH_VERSION_RESULT AND NOT MEMGRAPH_VERSION_RESULT EQUAL 0)
message(FATAL_ERROR "Unable to get Memgraph version.")
else()
MESSAGE(STATUS "Memgraph version: ${MEMGRAPH_VERSION}")
endif()
# Get version that should be used in the DEB package.
execute_process(
OUTPUT_VARIABLE MEMGRAPH_VERSION_DEB
RESULT_VARIABLE MEMGRAPH_VERSION_DEB_RESULT
COMMAND "${get_version_script}" ${get_version_offering}
--variant deb
"${MEMGRAPH_OVERRIDE_VERSION}"
"${MEMGRAPH_OVERRIDE_VERSION_SUFFIX}"
"--memgraph-root-dir"
"${CMAKE_CURRENT_SOURCE_DIR}"
)
if(MEMGRAPH_VERSION_DEB_RESULT AND NOT MEMGRAPH_VERSION_DEB_RESULT EQUAL 0)
message(FATAL_ERROR "Unable to get Memgraph DEB version.")
else()
MESSAGE(STATUS "Memgraph DEB version: ${MEMGRAPH_VERSION_DEB}")
endif()
# Get version that should be used in the RPM package.
execute_process(
OUTPUT_VARIABLE MEMGRAPH_VERSION_RPM
RESULT_VARIABLE MEMGRAPH_VERSION_RPM_RESULT
COMMAND "${get_version_script}" ${get_version_offering}
--variant rpm
"${MEMGRAPH_OVERRIDE_VERSION}"
"${MEMGRAPH_OVERRIDE_VERSION_SUFFIX}"
"--memgraph-root-dir"
"${CMAKE_CURRENT_SOURCE_DIR}"
)
if(MEMGRAPH_VERSION_RPM_RESULT AND NOT MEMGRAPH_VERSION_RPM_RESULT EQUAL 0)
message(FATAL_ERROR "Unable to get Memgraph RPM version.")
else()
MESSAGE(STATUS "Memgraph RPM version: ${MEMGRAPH_VERSION_RPM}")
endif()
# We want the above variables to be updated each time something is committed to
# the repository. That is why we include a dependency on the current git HEAD
# to trigger a new CMake run when the git repository state changes. This is a
# hack, as CMake doesn't have a mechanism to regenerate variables when
# something changes (only files can be regenerated).
# https://cmake.org/pipermail/cmake/2018-October/068389.html
#
# The hack in the above link is nearly correct but it has a fatal flaw. The
# `CMAKE_CONFIGURE_DEPENDS` isn't a `GLOBAL` property, it is instead a
# `DIRECTORY` property and as such must be set in the `DIRECTORY` scope.
# https://cmake.org/cmake/help/v3.14/manual/cmake-properties.7.html
#
# Unlike the above mentioned hack, we don't use the `.git/index` file. That
# file changes on every `git add` (even on `git status`) so it triggers
# unnecessary recalculations of the release version. The release version only
# changes on every `git commit` or `git checkout`. That is why we watch the
# following files for changes:
# - `.git/HEAD` -> changes each time a `git checkout` is issued
# - `.git/refs/heads/...` -> the value in `.git/HEAD` is a branch name (when
# you are on a branch) and you have to monitor the file of the specific
# branch to detect when a `git commit` was issued
# More details about the contents of the `.git` directory and the specific
# files used can be seen here:
# https://git-scm.com/book/en/v2/Git-Internals-Git-References
set(git_directory "${CMAKE_SOURCE_DIR}/.git")
if (EXISTS "${git_directory}")
set_property(DIRECTORY APPEND PROPERTY
CMAKE_CONFIGURE_DEPENDS "${git_directory}/HEAD")
file(STRINGS "${git_directory}/HEAD" git_head_data)
if (git_head_data MATCHES "^ref: ")
string(SUBSTRING "${git_head_data}" 5 -1 git_head_ref)
set_property(DIRECTORY APPEND PROPERTY
CMAKE_CONFIGURE_DEPENDS "${git_directory}/${git_head_ref}")
endif()
endif()
project(memgraph VERSION 0.50.0)
# -----------------------------------------------------------------------------
# setup CMake module path, defines path for include() and find_package()
@@ -177,25 +68,20 @@ add_custom_target(clean_all
# is easier debugging of compilation and linker flags.
set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
set(CMAKE_CXX_STANDARD 20)
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
# c99-designator is disabled because of required mixture of designated and
# non-designated initializers in Python Query Module code (`py_module.cpp`).
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wall \
-Werror=switch -Werror=switch-bool -Werror=implicit-fallthrough \
-Werror=return-type \
-Werror=return-stack-address \
-Wno-c99-designator \
-DBOOST_ASIO_USE_TS_EXECUTOR_AS_DEFAULT")
-Werror=switch -Werror=switch-bool -Werror=return-type \
-Werror=return-stack-address")
# Don't omit frame pointer in RelWithDebInfo, for additional callchain debug.
set(CMAKE_CXX_FLAGS_RELWITHDEBINFO
"${CMAKE_CXX_FLAGS_RELWITHDEBINFO} -fno-omit-frame-pointer")
# Statically link libgcc and libstdc++, the GCC allows this according to:
# https://gcc.gnu.org/onlinedocs/gcc-10.2.0/libstdc++/manual/manual/license.html
# https://gcc.gnu.org/onlinedocs/gcc-8.3.0/libstdc++/manual/manual/license.html
# https://www.gnu.org/licenses/gcc-exception-faq.html
# Last checked for gcc-10.2 which we are using on the build machines.
# Last checked for gcc-8.3 which we are using on the build machines.
# ** If we change versions, recheck this! **
# ** Static linking is allowed only for executables! **
set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -static-libgcc -static-libstdc++")
@@ -206,8 +92,6 @@ set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -fuse-ld=gold")
# release flags
set(CMAKE_CXX_FLAGS_RELEASE "-O2 -DNDEBUG")
SET(CMAKE_CXX_LINK_FLAGS "${CMAKE_CXX_LINK_FLAGS} -pthread")
#debug flags
set(PREFERRED_DEBUGGER "gdb" CACHE STRING
"Tunes the debug output for your preferred debugger (gdb or lldb).")
@@ -223,6 +107,13 @@ else()
set(CMAKE_CXX_FLAGS_DEBUG "-g")
endif()
# ndebug
option(NDEBUG "No debug" OFF)
message(STATUS "NDEBUG: ${NDEBUG} (be careful CMAKE_BUILD_TYPE can also \
append this flag)")
if(NDEBUG)
add_definitions( -DNDEBUG )
endif()
# -----------------------------------------------------------------------------
# default build type is debug
@@ -232,12 +123,15 @@ endif()
message(STATUS "CMake build type: ${CMAKE_BUILD_TYPE}")
# -----------------------------------------------------------------------------
set(MG_ARCH "x86_64" CACHE STRING "Host architecture to build Memgraph on. Supported values are x86_64 (default), ARM64.")
# setup external dependencies -------------------------------------------------
# threading
find_package(Threads REQUIRED)
# optional Ltalloc
option(USE_LTALLOC "Use Ltalloc instead of default allocator (default OFF). \
Set this to ON to link with Ltalloc." OFF)
# optional readline
option(USE_READLINE "Use GNU Readline library if available (default ON). \
Set this to OFF to prevent linking with Readline even if it is available." ON)
@@ -248,16 +142,68 @@ if (USE_READLINE)
endif()
endif()
# OpenSSL
find_package(OpenSSL REQUIRED)
set(libs_dir ${CMAKE_SOURCE_DIR}/libs)
add_subdirectory(libs EXCLUDE_FROM_ALL)
include_directories(SYSTEM ${GFLAGS_INCLUDE_DIR})
include_directories(SYSTEM ${GLOG_INCLUDE_DIR})
include_directories(SYSTEM ${FMT_INCLUDE_DIR})
include_directories(SYSTEM ${ANTLR4_INCLUDE_DIR})
include_directories(SYSTEM ${BZIP2_INCLUDE_DIR})
include_directories(SYSTEM ${ZLIB_INCLUDE_DIR})
include_directories(SYSTEM ${ROCKSDB_INCLUDE_DIR})
include_directories(SYSTEM ${LIBRDKAFKA_INCLUDE_DIR})
# -----------------------------------------------------------------------------
# openCypher parser -----------------------------------------------------------
set(opencypher_frontend ${CMAKE_SOURCE_DIR}/src/query/frontend/opencypher)
set(opencypher_generated ${opencypher_frontend}/generated)
set(opencypher_lexer_grammar ${opencypher_frontend}/grammar/MemgraphCypherLexer.g4)
set(opencypher_parser_grammar ${opencypher_frontend}/grammar/MemgraphCypher.g4)
# enumerate all files that are generated from antlr
set(antlr_opencypher_generated_src
${opencypher_generated}/MemgraphCypherLexer.cpp
${opencypher_generated}/MemgraphCypher.cpp
${opencypher_generated}/MemgraphCypherBaseVisitor.cpp
${opencypher_generated}/MemgraphCypherVisitor.cpp
)
# Provide a command to generate sources if missing. If this were a
# custom_target, it would always run and we don't want that.
add_custom_command(OUTPUT ${antlr_opencypher_generated_src}
COMMAND
${CMAKE_COMMAND} -E make_directory ${opencypher_generated}
COMMAND
java -jar ${CMAKE_SOURCE_DIR}/libs/antlr-4.6-complete.jar -Dlanguage=Cpp -visitor -o ${opencypher_generated} -package antlropencypher ${opencypher_lexer_grammar} ${opencypher_parser_grammar}
WORKING_DIRECTORY "${CMAKE_BINARY_DIR}"
DEPENDS ${opencypher_lexer_grammar} ${opencypher_parser_grammar}
${opencypher_frontend}/grammar/CypherLexer.g4
${opencypher_frontend}/grammar/Cypher.g4)
# add custom target for generation
add_custom_target(generate_opencypher_parser
DEPENDS ${antlr_opencypher_generated_src})
add_library(antlr_opencypher_parser_lib STATIC ${antlr_opencypher_generated_src})
target_link_libraries(antlr_opencypher_parser_lib antlr4)
# -----------------------------------------------------------------------------
# Optional subproject configuration -------------------------------------------
option(POC "Build proof of concept binaries" OFF)
option(EXPERIMENTAL "Build experimental binaries" OFF)
option(CUSTOMERS "Build customer binaries" OFF)
option(TEST_COVERAGE "Generate coverage reports from running memgraph" OFF)
option(TOOLS "Build tools binaries" ON)
option(QUERY_MODULES "Build query modules containing custom procedures" ON)
option(MG_COMMUNITY "Build Memgraph Community Edition" OFF)
option(ASAN "Build with Address Sanitizer. To get a reasonable performance option should be used only in Release or RelWithDebInfo build " OFF)
option(TSAN "Build with Thread Sanitizer. To get a reasonable performance option should be used only in Release or RelWithDebInfo build " OFF)
option(UBSAN "Build with Undefined Behaviour Sanitizer" OFF)
option(THIN_LTO "Build with link time optimization" OFF)
if (TEST_COVERAGE)
string(TOLOWER ${CMAKE_BUILD_TYPE} lower_build_type)
@@ -268,15 +214,11 @@ if (TEST_COVERAGE)
set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -fprofile-instr-generate -fcoverage-mapping")
endif()
if (MG_ENTERPRISE)
add_definitions(-DMG_ENTERPRISE)
if (MG_COMMUNITY)
add_definitions(-DMG_COMMUNITY)
endif()
set(ENABLE_JEMALLOC ON)
if (ASAN)
message(WARNING "Disabling jemalloc as it doesn't work well with ASAN")
set(ENABLE_JEMALLOC OFF)
# Enable Addres sanitizer and get nicer stack traces in error messages.
# NOTE: AddressSanitizer uses llvm-symbolizer binary from the Clang
# distribution to symbolize the stack traces (note that ideally the
@@ -323,29 +265,34 @@ if (UBSAN)
# runtime library and c++ standard libraries are present.
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsanitize=undefined -fno-omit-frame-pointer -fno-sanitize=vptr")
set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -fsanitize=undefined -fno-sanitize=vptr")
# Run program with environment variable UBSAN_OPTIONS=print_stacktrace=1.
# Make sure llvm-symbolizer binary is in path.
# To make the program abort on undefined behavior, use UBSAN_OPTIONS=halt_on_error=1.
# Run program with environment variable UBSAN_OPTIONS=print_stacktrace=1
# Make sure llvm-symbolizer binary is in path
endif()
set(MG_PYTHON_VERSION "" CACHE STRING "Specify the exact Python version used by the query modules")
set(MG_PYTHON_PATH "" CACHE STRING "Specify the exact Python path used by the query modules")
if (THIN_LTO)
set(CMAKE_CXX_FLAGS"${CMAKE_CXX_FLAGS} -flto=thin")
set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -flto=thin")
endif()
# Add subprojects
include_directories(src)
add_subdirectory(src)
# Release configuration
add_subdirectory(release)
option(MG_ENABLE_TESTING "Set this to OFF to disable building test binaries" ON)
message(STATUS "MG_ENABLE_TESTING: ${MG_ENABLE_TESTING}")
if (MG_ENABLE_TESTING)
enable_testing()
add_subdirectory(tests)
if(POC)
add_subdirectory(poc)
endif()
if(EXPERIMENTAL)
add_subdirectory(experimental)
endif()
if(CUSTOMERS)
add_subdirectory(customers)
endif()
enable_testing()
add_subdirectory(tests)
if(TOOLS)
add_subdirectory(tools)
endif()
@@ -354,6 +301,58 @@ if(QUERY_MODULES)
add_subdirectory(query_modules)
endif()
install(FILES ${CMAKE_BINARY_DIR}/bin/mgconsole
PERMISSIONS OWNER_EXECUTE OWNER_READ OWNER_WRITE GROUP_READ GROUP_EXECUTE WORLD_READ WORLD_EXECUTE
TYPE BIN)
# -----------------------------------------------------------------------------
# ---- Setup CPack --------
# General setup
set(CPACK_PACKAGE_NAME memgraph)
set(CPACK_PACKAGE_VENDOR "Memgraph Ltd.")
set(CPACK_PACKAGE_DESCRIPTION_SUMMARY
"High performance, in-memory, transactional graph database")
set(CPACK_PACKAGE_VERSION_MAJOR ${memgraph_VERSION_MAJOR})
set(CPACK_PACKAGE_VERSION_MINOR ${memgraph_VERSION_MINOR})
set(CPACK_PACKAGE_VERSION_PATCH ${memgraph_VERSION_PATCH})
set(CPACK_PACKAGE_VERSION_TWEAK ${memgraph_VERSION_TWEAK})
set(CPACK_PACKAGE_FILE_NAME ${CPACK_PACKAGE_NAME}-${memgraph_VERSION}-${COMMIT_HASH}${CPACK_SYSTEM_NAME})
# DEB specific
# Instead of using "name <email>" format, we use "email (name)" to prevent
# errors due to full stop, '.' at the end of "Ltd". (See: RFC 822)
set(CPACK_DEBIAN_PACKAGE_MAINTAINER "tech@memgraph.com (Memgraph Ltd.)")
set(CPACK_DEBIAN_PACKAGE_SECTION non-free/database)
set(CPACK_DEBIAN_PACKAGE_HOMEPAGE https://memgraph.com)
set(CPACK_DEBIAN_PACKAGE_CONTROL_EXTRA
"${CMAKE_SOURCE_DIR}/release/debian/conffiles;"
"${CMAKE_SOURCE_DIR}/release/debian/copyright;"
"${CMAKE_SOURCE_DIR}/release/debian/prerm;"
"${CMAKE_SOURCE_DIR}/release/debian/postrm;"
"${CMAKE_SOURCE_DIR}/release/debian/postinst;")
set(CPACK_DEBIAN_PACKAGE_SHLIBDEPS ON)
# Description formatting is important, summary must be followed with a newline and 1 space.
set(CPACK_DEBIAN_PACKAGE_DESCRIPTION "${CPACK_PACKAGE_DESCRIPTION_SUMMARY}
Contains Memgraph, the graph database. It aims to deliver developers the
speed, simplicity and scale required to build the next generation of
applications driver by real-time connected data.")
# Add `openssl` package to dependencies list. Used to generate SSL certificates.
set(CPACK_DEBIAN_PACKAGE_DEPENDS "openssl (>= 1.1.0)")
# RPM specific
set(CPACK_RPM_PACKAGE_URL https://memgraph.com)
set(CPACK_RPM_EXCLUDE_FROM_AUTO_FILELIST_ADDITION
/var /var/lib /var/log /etc/logrotate.d
/lib /lib/systemd /lib/systemd/system /lib/systemd/system/memgraph.service)
set(CPACK_RPM_PACKAGE_REQUIRES_PRE "shadow-utils")
# NOTE: user specfile has a bug in cmake 3.7.2, this needs to be patched
# manually in: ~/cmake/share/cmake-3.7/Modules/CPackRPM.cmake line 2273
# Or newer cmake version used
set(CPACK_RPM_USER_BINARY_SPECFILE "${CMAKE_SOURCE_DIR}/release/rpm/memgraph.spec.in")
# Description formatting is important, no line must be greater than 80 characters.
set(CPACK_RPM_PACKAGE_DESCRIPTION "Contains Memgraph, the graph database.
It aims to deliver developers the speed, simplicity and scale required to build
the next generation of applications driver by real-time connected data.")
# Add `openssl` package to dependencies list. Used to generate SSL certificates.
set(CPACK_RPM_PACKAGE_REQUIRES "openssl >= 1.0.0, curl >= 7.29.0")
# All variables must be set before including.
include(CPack)
# ---- End Setup CPack ----

View File

@@ -1,127 +0,0 @@
# Contributor Covenant Code of Conduct
## Our Pledge
We as members, contributors, and leaders pledge to make participation in our
community a harassment-free experience for everyone, regardless of age, body
size, visible or invisible disability, ethnicity, sex characteristics, gender
identity and expression, level of experience, education, socio-economic status,
nationality, personal appearance, race, caste, color, religion, or sexual
identity and orientation.
We pledge to act and interact in ways that contribute to an open, welcoming,
diverse, inclusive, and healthy community.
## Our Standards
Examples of behavior that contributes to a positive environment for our
community include:
- Demonstrating empathy and kindness toward other people
- Being respectful of differing opinions, viewpoints, and experiences
- Giving and gracefully accepting constructive feedback
- Accepting responsibility and apologizing to those affected by our mistakes,
and learning from the experience
- Focusing on what is best not just for us as individuals, but for the overall
community
Examples of unacceptable behavior include:
- The use of sexualized language or imagery, and sexual attention or advances of
any kind
- Trolling, insulting or derogatory comments, and personal or political attacks
- Public or private harassment
- Publishing other's private information, such as a physical or email address,
without their explicit permission
- Other conduct which could reasonably be considered inappropriate in a
professional setting
## Enforcement Responsibilities
Community leaders are responsible for clarifying and enforcing our standards of
acceptable behavior and will take appropriate and fair corrective action in
response to any behavior that they deem inappropriate, threatening, offensive,
or harmful.
Community leaders have the right and responsibility to remove, edit, or reject
comments, commits, code, wiki edits, issues, and other contributions that are
not aligned to this Code of Conduct, and will communicate reasons for moderation
decisions when appropriate.
## Scope
This Code of Conduct applies within all community spaces, and also applies when
an individual is officially representing the community in public spaces.
Examples of representing our community include using an official e-mail address,
posting via an official social media account, or acting as an appointed
representative at an online or offline event.
## Enforcement
Instances of abusive, harassing, or otherwise unacceptable behavior may be
reported to the community leaders responsible for enforcement at
[contact@memgraph.com](contact@memgraph.com). All complaints will be reviewed
and investigated promptly and fairly.
All community leaders are obligated to respect the privacy and security of the
reporter of any incident.
## Enforcement Guidelines
Community leaders will follow these Community Impact Guidelines in determining
the consequences for any action they deem in violation of this Code of Conduct:
### 1. Correction
**Community Impact**: Use of inappropriate language or other behavior deemed
unprofessional or unwelcome in the community.
**Consequence**: A private, written warning from community leaders, providing
clarity around the nature of the violation and an explanation of why the
behavior was inappropriate. A public apology may be requested.
### 2. Warning
**Community Impact**: A violation through a single incident or series of
actions.
**Consequence**: A warning with consequences for continued behavior. No
interaction with the people involved, including unsolicited interaction with
those enforcing the Code of Conduct, for a specified period of time. This
includes avoiding interactions in community spaces as well as external channels
like social media. Violating these terms may lead to a temporary or permanent
ban.
### 3. Temporary Ban
**Community Impact**: A serious violation of community standards, including
sustained inappropriate behavior.
**Consequence**: A temporary ban from any sort of interaction or public
communication with the community for a specified period of time. No public or
private interaction with the people involved, including unsolicited interaction
with those enforcing the Code of Conduct, is allowed during this period.
Violating these terms may lead to a permanent ban.
### 4. Permanent Ban
**Community Impact**: Demonstrating a pattern of violation of community
standards, including sustained inappropriate behavior, harassment of an
individual, or aggression toward or disparagement of classes of individuals.
**Consequence**: A permanent ban from any sort of public interaction within the
community.
## Attribution
This Code of Conduct is adapted from the Contributor Covenant, version 2.1,
available at
[https://www.contributor-covenant.org/version/2/1/code_of_conduct.html](https://www.contributor-covenant.org/version/2/1/code_of_conduct.html).
Community Impact Guidelines were inspired by [Mozilla's code of conduct
enforcement ladder][mozilla coc].
For answers to common questions about this code of conduct, see the FAQ at
[https://www.contributor-covenant.org/faq](https://www.contributor-covenant.org/faq).
Translations are available at
[https://www.contributor-covenant.org/translations](https://www.contributor-covenant.org/translations).

View File

@@ -1,121 +0,0 @@
# How to contribute?
This is a general purpose guide for contributing to Memgraph. We're still
working out the kinks to make contributing to this project as easy and
transparent as possible, but we're not quite there yet. Hopefully, this document
makes the process for contributing clear and answers some questions that you may
have.
- [How to contribute?](#how-to-contribute)
- [Open development](#open-development)
- [Branch organization](#branch-organization)
- [Bugs & changes](#bugs--changes)
- [Where to find known issues?](#where-to-find-known-issues)
- [Proposing a change](#proposing-a-change)
- [Your first pull request](#your-first-pull-request)
- [Sending a pull request](#sending-a-pull-request)
- [Style guide](#style-guide)
- [How to get in touch?](#how-to-get-in-touch)
- [Code of Conduct](#code-of-conduct)
- [License](#license)
- [Attribution](#attribution)
## Open development
All work on Memgraph is done via [GitHub](https://github.com/memgraph/memgraph).
Both core team members and external contributors send pull requests which go
through the same review process.
## Branch organization
Most pull requests should target the [`master
branch`](https://github.com/memgraph/memgraph/tree/master). We only use separate
branches for developing new features and fixing bugs before they are merged with
`master`. We do our best to keep `master` in good shape, with all tests passing.
Code that lands in `master` must be compatible with the latest stable release.
It may contain additional features but no breaking changes if it's not
absolutely necessary. We should be able to release a new minor version from the
tip of `master` at any time.
## Bugs & changes
### Where to find known issues?
We are using [GitHub Issues](https://github.com/memgraph/memgraph/issues) for
our public bugs. We keep a close eye on this and try to make it clear when we
have an internal fix in progress. Before filing a new task, try to make sure
your problem doesn't already exist.
### Proposing a change
If you intend to change the public API, or make any non-trivial changes to the
implementation, we recommend [filing an
issue](https://github.com/memgraph/memgraph/issues/new). This lets us reach an
agreement on your proposal before you put significant effort into it.
If you're only fixing a bug, it's fine to submit a pull request right away but
we still recommend to file an issue detailing what you're fixing. This is
helpful in case we don't accept that specific fix but want to keep track of the
issue.
### Your first pull request
Working on your first Pull Request? You can learn how from this free video
series:
**[How to Contribute to an Open Source Project on
GitHub](https://app.egghead.io/courses/how-to-contribute-to-an-open-source-project-on-github)**
If you decide to fix an issue, please be sure to check the comment thread in
case somebody is already working on a fix. If nobody is working on it at the
moment, please leave a comment stating that you intend to work on it so other
people don't accidentally duplicate your effort.
If somebody claims an issue but doesn't follow up for more than two weeks, it's
fine to take it over but you should still leave a comment.
### Sending a pull request
The core team is monitoring for pull requests. We will review your pull request
and either merge it, request changes to it, or close it with an explanation.
**Before submitting a pull request,** please make sure the following is done:
1. Fork [the repository](https://github.com/memgraph/memgraph) and create your
branch from `master`.
2. If you've fixed a bug or added code that should be tested, add tests!
3. Use the formatter `clang-format` for C/C++ code and `flake8` for Python code.
`clang-format` will automatically detect the `.clang-format` file in the root
directory while `flake8` can be used with the default configuration.
### Style guide
Memgraph uses the [Google Style
Guide](https://google.github.io/styleguide/cppguide.html) for C++ in most of its
code. You should follow them whenever writing new code.
## How to get in touch?
Aside from communicating directly via Pull Requests and Issues, the Memgraph
Community [Discord Server](https://discord.gg/memgraph) is the best place for
conversing with project maintainers and other community members.
## [Code of Conduct](https://github.com/memgraph/memgraph/blob/master/CODE_OF_CONDUCT.md)
Memgraph has adopted the [Contributor
Covenant](https://www.contributor-covenant.org/) as its Code of Conduct, and we
expect project participants to adhere to it. Please read [the full
text](https://github.com/memgraph/memgraph/blob/master/CODE_OF_CONDUCT.md) so
that you can understand what actions will and will not be tolerated.
## License
By contributing to Memgraph, you agree that your contributions will be licensed
under the [Memgraph licensing
scheme](https://github.com/memgraph/memgraph/blob/master/LICENSE).
## Attribution
This Contributing guide is adapted from the **React.js Contributing guide**
available at
[https://reactjs.org/docs/how-to-contribute.html](https://reactjs.org/docs/how-to-contribute.html).

View File

@@ -51,7 +51,7 @@ PROJECT_BRIEF = "The World's Most Powerful Graph Database"
# pixels and the maximum width should not exceed 200 pixels. Doxygen will copy
# the logo to the output directory.
PROJECT_LOGO = docs/doxygen/memgraph_logo.png
PROJECT_LOGO = Doxylogo.png
# The OUTPUT_DIRECTORY tag is used to specify the (relative or absolute) path
# into which the generated documentation will be written. If a relative path is
@@ -839,6 +839,7 @@ EXCLUDE_PATTERNS += */Testing/*
EXCLUDE_PATTERNS += */tests/*
EXCLUDE_PATTERNS += */dist/*
EXCLUDE_PATTERNS += */tools/*
EXCLUDE_PATTERNS += */customers/*
# The EXCLUDE_SYMBOLS tag can be used to specify one or more symbol names
# (namespaces, classes, functions, etc.) that should be excluded from the

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Before

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After

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@@ -1,5 +0,0 @@
Source code in this repository is variously licensed under the Business Source
License 1.1 (BSL), the Memgraph Enterprise License (MEL). A copy of each licence
can be found in the licences directory. Source code in a given file is licensed
under the BSL and the copyright belongs to The Memgraph Authors unless
otherwise noted at th beginning of the file.

162
README.md
View File

@@ -1,148 +1,24 @@
<p align="center">
<img width="400px" src="https://uploads-ssl.webflow.com/5e7ceb09657a69bdab054b3a/5e7ceb09657a6937ab054bba_Black_Original%20_Logo.png">
</p>
# memgraph
---
Memgraph is an ACID compliant high performance transactional distributed
in-memory graph database featuring runtime native query compiling, lock free
data structures, multi-version concurrency control and asynchronous IO.
<p align="center">
Build modern, graph-based applications on top of your streaming data in minutes.
</p>
## dependencies
<p align="center">
<a href="https://github.com/memgraph/memgraph/blob/master/licenses/APL.txt">
<img src="https://img.shields.io/badge/license-APL-green" alt="license" title="license"/>
</a>
<a href="https://github.com/memgraph/memgraph/blob/master/licenses/BSL.txt">
<img src="https://img.shields.io/badge/license-BSL-yellowgreen" alt="license" title="license"/>
</a>
<a href="https://github.com/memgraph/memgraph/blob/master/licenses/MEL.txt" alt="Documentation">
<img src="https://img.shields.io/badge/license-MEL-yellow" alt="license" title="license"/>
</a>
</p>
Memgraph can be compiled using any modern c++ compiler. It mostly relies on
the standard template library, however, some things do require external
libraries.
<p align="center">
<a href="https://github.com/memgraph/memgraph">
<img src="https://img.shields.io/github/workflow/status/memgraph/memgraph/Release%20Ubuntu%2020.04/master" alt="build" title="build"/>
</a>
<a href="https://memgraph.com/docs/" alt="Documentation">
<img src="https://img.shields.io/badge/documentation-Memgraph-orange" />
</a>
</p>
Some code contains linux-specific libraries and the build is only supported
on a 64 bit linux kernel.
<p align="center">
<a href="https://memgr.ph/join-discord">
<img src="https://img.shields.io/badge/Discord-7289DA?style=for-the-badge&logo=discord&logoColor=white" alt="Discord"/>
</a>
</p>
## :clipboard: Description
Memgraph is a streaming graph application platform that helps you wrangle your
streaming data, build sophisticated models that you can query in real-time, and
develop graph applications.
Memgraph directly connects to your streaming infrastructure. You can ingest data
from sources like Kafka, SQL, or plain CSV files. Memgraph provides a standard
interface to query your data with Cypher, a widely-used and declarative query
language that is easy to write, understand and optimize for performance. This is
achieved by using the property graph data model, which stores data in terms of
objects, their attributes, and the relationships that connect them. This is a
natural and effective way to model many real-world problems without relying on
complex SQL schemas.
Memgraph is implemented in C/C++ and leverages an in-memory first architecture
to ensure that youre getting the best possible performance consistently and
without surprises. Its also ACID-compliant and highly available.
## :video_game: Memgraph Playground
You don't need to install anything to try out Memgraph. Check out
our **[Memgraph Playground](https://playground.memgraph.com/)** sandboxes in
your browser.
<p align="left">
<a href="https://playground.memgraph.com/">
<img width="450px" alt="Memgraph Playground" src="https://download.memgraph.com/asset/github/memgraph/memgraph-playground.png">
</a>
</p>
## :floppy_disk: Download & Install
### Windows
[![Windows](https://img.shields.io/badge/Windows-Docker-0078D6?style=for-the-badge&logo=windows&logoColor=white)](https://memgraph.com/docs/memgraph/install-memgraph-on-windows-docker)
[![Windows](https://img.shields.io/badge/Windows-WSL-0078D6?style=for-the-badge&logo=windows&logoColor=white)](https://memgraph.com/docs/memgraph/install-memgraph-on-windows-wsl)
### macOS
[![macOS](https://img.shields.io/badge/macOS-Docker-000000?style=for-the-badge&logo=macos&logoColor=F0F0F0)](https://memgraph.com/docs/memgraph/install-memgraph-on-macos-docker)
### Linux
[![Linux](https://img.shields.io/badge/Linux-Docker-FCC624?style=for-the-badge&logo=linux&logoColor=black)](https://memgraph.com/docs/memgraph/install-memgraph-on-linux-docker)
[![Debian](https://img.shields.io/badge/Debian-D70A53?style=for-the-badge&logo=debian&logoColor=white)](https://memgraph.com/docs/memgraph/install-memgraph-on-debian)
[![Ubuntu](https://img.shields.io/badge/Ubuntu-E95420?style=for-the-badge&logo=ubuntu&logoColor=white)](https://memgraph.com/docs/memgraph/install-memgraph-on-ubuntu)
[![Cent
OS](https://img.shields.io/badge/cent%20os-002260?style=for-the-badge&logo=centos&logoColor=F0F0F0)](https://memgraph.com/docs/memgraph/install-memgraph-from-rpm)
You can find the binaries and Docker images on the [Download
Hub](https://memgraph.com/download) and the installation instructions in the
[official documentation](https://memgraph.com/docs/memgraph/installation).
## :zap: Features
- Run Python, Rust, and C/C++ code natively, check out the
[MAGE](https://github.com/memgraph/mage) graph algorithm library
- Native support for machine learning
- Streaming support
- Replication
- Authentication and authorization
- ACID compliance
## :bookmark_tabs: Documentation
The Memgraph documentation is available at
[memgraph.com/docs](https://memgraph.com/docs).
## :question: Configuration
Command line options that Memgraph accepts are available in the [reference
guide](https://memgraph.com/docs/memgraph/reference-guide/configuration).
## :trophy: Contributing
The main purpose of this repository is to continue evolving Memgraph, making it
faster and easier to use. Development of Memgraph happens in the open on GitHub,
and we are grateful to the community for contributing bug fixes and
improvements. Read below to learn how you can take part in improving Memgraph.
### Code of Conduct
Memgraph has adopted a Code of Conduct that we expect project participants to
adhere to. Please read [the full text](CODE_OF_CONDUCT.md) so that you can
understand what actions will and will not be tolerated.
### Contributing Guide
Read our [contributing guide](CONTRIBUTING.md) to learn about our development
process and how to propose bug fixes and improvements.
### Internals
Read our
[internal](https://memgraph.notion.site/Memgraph-Internals-12b69132d67a417898972927d6870bd2)
docs to learn more about Memgraph's architecture, how to build the project from
source and how to start contributing. All information related to the database,
can be found in the aforementioned docs.
### :scroll: License
Memgraph Community is available under the [BSL
license](./licenses/BSL.txt).</br> Memgraph Enterprise is available under the
[MEL license](./licenses/MEL.txt).
<p align="center">
<a href="#">
<img src="https://img.shields.io/badge/⬆back_to_top_⬆-white" alt="Back to top" title="Back to top"/>
</a>
</p>
* linux
* clang 3.8 (good c++11 support, especially lock free atomics)
* antlr (compiler frontend)
* cppitertools
* fmt format
* google benchmark
* google test
* glog
* gflags

39
apollo_archives.py Executable file
View File

@@ -0,0 +1,39 @@
#!/usr/bin/env python3
import json
import os
import re
import subprocess
import sys
# paths
SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__))
BUILD_OUTPUT_DIR = os.path.normpath(os.path.join(SCRIPT_DIR, "build_release", "output"))
# helpers
def run_cmd(cmd, cwd):
return subprocess.run(cmd, cwd=cwd, check=True,
stdout=subprocess.PIPE).stdout.decode("utf-8")
# check project
if re.search(r"release", os.environ.get("PROJECT", "")) is None:
print(json.dumps([]))
sys.exit(0)
# generate archive
deb_name = run_cmd(["find", ".", "-maxdepth", "1", "-type", "f",
"-name", "memgraph*.deb"], BUILD_OUTPUT_DIR).split("\n")[0][2:]
arch = run_cmd(["dpkg", "--print-architecture"], BUILD_OUTPUT_DIR).split("\n")[0]
version = deb_name.split("-")[1]
# generate Debian package file name as expected by Debian Policy
standard_deb_name = "memgraph_{}-1_{}.deb".format(version, arch)
archive_path = os.path.relpath(os.path.join(BUILD_OUTPUT_DIR,
deb_name), SCRIPT_DIR)
archives = [{
"name": "Release (deb package)",
"archive": archive_path,
"filename": standard_deb_name,
}]
print(json.dumps(archives, indent=4, sort_keys=True))

15
apollo_archives.yaml Normal file
View File

@@ -0,0 +1,15 @@
- name: Binaries
archive:
- build_debug/memgraph
- build_release/memgraph
- build_release/tools/src/mg_client
- build_release/tools/src/mg_import_csv
- config
filename: binaries.tar.gz
- name: Doxygen documentation
cd: docs/doxygen/html
archive:
- .
filename: documentation.tar.gz
host: true

94
apollo_build.yaml Normal file
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@@ -0,0 +1,94 @@
- name: Diff build
project: ^mg-master-diff$
commands: |
# Activate toolchain
export PATH=/opt/toolchain-v1/bin:$PATH
export LD_LIBRARY_PATH=/opt/toolchain-v1/lib:/opt/toolchain-v1/lib64
# Copy untouched repository to parent folder.
cd ..
cp -r memgraph parent
cd memgraph
# Initialize and create documentation.
TIMEOUT=1200 ./init
doxygen Doxyfile
# Remove default build directory.
rm -r build
# Build debug binaries.
mkdir build_debug
cd build_debug
cmake ..
TIMEOUT=1200 make -j$THREADS
# Build coverage binaries.
cd ..
# TODO: uncomment this build once single node and ha are split
# mkdir build_coverage
# cd build_coverage
# cmake -DTEST_COVERAGE=ON ..
# TIMEOUT=1200 make -j$THREADS memgraph__unit
ln -s build_debug build_coverage
# Build release binaries.
# cd ..
mkdir build_release
cd build_release
cmake -DCMAKE_BUILD_TYPE=release ..
TIMEOUT=1200 make -j$THREADS
cd ..
# Checkout to parent commit and initialize.
cd ../parent
git checkout HEAD~1
TIMEOUT=1200 ./init
# Build parent release binaries.
mkdir build_release
cd build_release
cmake -DCMAKE_BUILD_TYPE=release ..
TIMEOUT=1200 make -j$THREADS memgraph memgraph__macro_benchmark
# release build is the default one
- name: Release build
commands: |
# Activate toolchain
export PATH=/opt/toolchain-v1/bin:$PATH
export LD_LIBRARY_PATH=/opt/toolchain-v1/lib:/opt/toolchain-v1/lib64
# Initialize and create documentation.
TIMEOUT=1200 ./init
doxygen Doxyfile
# Remove default build directory.
rm -r build
# Build debug binaries.
mkdir build_debug
cd build_debug
cmake ..
TIMEOUT=1200 make -j$THREADS
# Build coverage binaries.
cd ..
# TODO: uncomment this build once single node and ha are split
# mkdir build_coverage
# cd build_coverage
# cmake -DTEST_COVERAGE=ON ..
# TIMEOUT=1200 make -j$THREADS memgraph__unit
ln -s build_debug build_coverage
# Build release binaries.
# cd ..
mkdir build_release
cd build_release
cmake -DCMAKE_BUILD_TYPE=Release -DUSE_READLINE=OFF ..
TIMEOUT=1200 make -j$THREADS
# Create Debian package.
mkdir output
cd output
cpack -G DEB --config ../CPackConfig.cmake

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@@ -1,55 +0,0 @@
# Try to find jemalloc library
#
# Use this module as:
# find_package(Jemalloc)
#
# or:
# find_package(Jemalloc REQUIRED)
#
# This will define the following variables:
#
# Jemalloc_FOUND True if the system has the jemalloc library.
# Jemalloc_INCLUDE_DIRS Include directories needed to use jemalloc.
# Jemalloc_LIBRARIES Libraries needed to link to jemalloc.
#
# The following cache variables may also be set:
#
# Jemalloc_INCLUDE_DIR The directory containing jemalloc/jemalloc.h.
# Jemalloc_LIBRARY The path to the jemalloc static library.
find_path(Jemalloc_INCLUDE_DIR NAMES jemalloc/jemalloc.h PATH_SUFFIXES include)
find_library(Jemalloc_LIBRARY NAMES libjemalloc.a PATH_SUFFIXES lib)
include(FindPackageHandleStandardArgs)
find_package_handle_standard_args(Jemalloc
FOUND_VAR Jemalloc_FOUND
REQUIRED_VARS
Jemalloc_LIBRARY
Jemalloc_INCLUDE_DIR
)
if(Jemalloc_FOUND)
set(Jemalloc_LIBRARIES ${Jemalloc_LIBRARY})
set(Jemalloc_INCLUDE_DIRS ${Jemalloc_INCLUDE_DIR})
else()
if(Jemalloc_FIND_REQUIRED)
message(FATAL_ERROR "Cannot find jemalloc!")
else()
message(WARNING "jemalloc is not found!")
endif()
endif()
if(Jemalloc_FOUND AND NOT TARGET Jemalloc::Jemalloc)
add_library(Jemalloc::Jemalloc UNKNOWN IMPORTED)
set_target_properties(Jemalloc::Jemalloc
PROPERTIES
IMPORTED_LOCATION "${Jemalloc_LIBRARY}"
INTERFACE_INCLUDE_DIRECTORIES "${Jemalloc_INCLUDE_DIR}"
)
endif()
mark_as_advanced(
Jemalloc_INCLUDE_DIR
Jemalloc_LIBRARY
)

View File

@@ -39,22 +39,18 @@ modifications:
value: "/var/log/memgraph/memgraph.log"
override: true
- name: "log_level"
value: "WARNING"
- name: "bolt_cert_file"
value: "/etc/memgraph/ssl/cert.pem"
override: true
- name: "bolt_key_file"
value: "/etc/memgraph/ssl/key.pem"
override: true
- name: "bolt_num_workers"
value: ""
override: false
- name: "bolt_cert_file"
value: "/etc/memgraph/ssl/cert.pem"
override: false
- name: "bolt_key_file"
value: "/etc/memgraph/ssl/key.pem"
override: false
- name: "storage_properties_on_edges"
value: "true"
override: true
@@ -83,27 +79,23 @@ modifications:
value: "true"
override: true
# - name: "query_modules_directory"
# value: "/usr/lib/memgraph/query_modules"
# override: true
- name: "memory_limit"
value: "0"
- name: "query_modules_directory"
value: "/usr/lib/memgraph/query_modules"
override: true
- name: "isolation_level"
value: "SNAPSHOT_ISOLATION"
override: true
- name: "allow_load_csv"
value: "true"
- name: "auth_module_executable"
value: "/usr/lib/memgraph/auth_module/example.py"
override: false
undocumented:
- "flag_file"
- "also_log_to_stderr"
- "log_file_mode"
- "log_link_basename"
- "log_prefix"
- "max_log_size"
- "min_log_level"
- "help"
- "help_xml"
- "stderr_threshold"
- "stop_logging_if_full_disk"
- "version"
- "organization_name"
- "license_key"

2
customers/CMakeLists.txt Normal file
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@@ -0,0 +1,2 @@
project(mg_customers)
add_subdirectory(otto)

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@@ -0,0 +1,70 @@
DISCLAIMER: this is just an initial test, graph might not resemble
the graph in the use case at all and the data might be completely
irrelevant.
We tried generating a few sample graphs from the vague description
given in the use case doc. Then we tried writing queries that would
solve the problem of updating nodes when a leaf value changes,
assuming all the internal nodes compute only the sum function.
We start by creating an index on `id` property to improve initial lookup
performance:
CREATE INDEX ON :Leaf(id)
Set values of all leafs to 1:
MATCH (u:Leaf) SET u.value = 1
Now we initialize the values of all other nodes in the graph:
MATCH (u) WHERE NOT u:Leaf SET u.value = 0
MATCH (u) WITH u
ORDER BY u.topological_index DESC
MATCH (u)-->(v) SET u.value = u.value + v.value
Change the value of a leaf:
MATCH (u:Leaf {id: "18"}) SET u.value = 10
We have to reset all the updated nodes to a neutral element:
MATCH (u:Leaf {id: "18"})<-[* bfs]-(v)
WHERE NOT v:Leaf SET v.value = 0
Finally, we recalculate their values in topological order:
MATCH (u:Leaf {id: "18"})<-[* bfs]-(v)
WITH v ORDER BY v.topological_index DESC
MATCH (v)-->(w) SET v.value = v.value + w.value
There are a few assumptions made worth pointing out.
* We are able to efficiently maintain topological order
of vertices in the graph.
* It is possible to accumulate the value of the function. Formally:
$$f(x_1, x_2, ..., x_n) = g(...(g(g(x_1, x_2), x_3), ...), x_n)$$
* There is a neutral element for the operation. However, this
assumption can be dropped by introducing an artificial neutral element.
Number of operations required is proportional to the sum of degrees of affected
nodes.
We generated graph with $10^5$ nodes ($20\ 000$ nodes in each layer), varied the
degree distribution in node layers and measured time for the query to execute:
| # | Root-Category-Group degree | Group-CustomGroup-Leaf degree | Time |
|:-:|:---------------------------:|:-----------------------------:|:---------:|
| 1 | [1, 10] | [20, 40] | ~1.1s |
| 2 | [1, 10] | [50, 100] | ~2.5s |
| 3 | [10, 50] | [50, 100] | ~3.3s |
Due to the structure of the graph, update of a leaf required update of almost
all the nodes in the graph so we don't show times required for initial graph
update and update after leaf change separately.
However, there is not enough info on the use case to make the test more
sophisticated.

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@@ -0,0 +1,71 @@
---
title: "Elliott Management"
subtitle: "Proof of Concept Report"
header-title: "Elliott Management POC"
date: 2017-10-28
copyright: "©2017 Memgraph Ltd. All rights reserved."
titlepage: true
titlepage-color: FFFFFF
titlepage-text-color: 101010
titlepage-rule-color: 101010
titlepage-rule-height: 1
...
# Introduction
We tried generating a few sample graphs from the description given at
the in-person meetings. Then, we tried writing queries that would solve
the problem of updating nodes when a leaf value changes, assuming all the
internal nodes compute only the sum function.
# Technical details
We started by creating an index on `id` property to improve initial lookup
performance:
CREATE INDEX ON :Leaf(id)
Afther that, we set values of all leafs to 1:
MATCH (u:Leaf) SET u.value = 1
We then initialized the values of all other nodes in the graph:
MATCH (u) WHERE NOT u:Leaf SET u.value = 0
MATCH (u) WITH u
ORDER BY u.topological_index DESC
MATCH (u)-->(v) SET u.value = u.value + v.value
Leaf value change and update of affected values in the graph can
be done using three queries. To change the value of a leaf:
MATCH (u:Leaf {id: "18"}) SET u.value = 10
Then we had to reset all the affected nodes to the neutral element:
MATCH (u:Leaf {id: "18"})<-[* bfs]-(v)
WHERE NOT v:Leaf SET v.value = 0
Finally, we recalculated their values in topological order:
MATCH (u:Leaf {id: "18"})<-[* bfs]-(v)
WITH v ORDER BY v.topological_index DESC
MATCH (v)-->(w) SET v.value = v.value + w.value
There are a few assumptions necessary for the approach above to work.
* We are able to maintain topological order of vertices during graph
structure changes.
* It is possible to accumulate the value of the function. Formally:
$$f(x_1, x_2, ..., x_n) = g(...(g(g(x_1, x_2), x_3), ...), x_n)$$
* There is a neutral element for the operation. However, this
assumption can be dropped by introducing an artificial neutral element.
Above assumptions could be changed, relaxed or dropped, depending on the
specifics of the use case.
Number of operations required is proportional to the sum of degrees of affected
nodes.

View File

@@ -0,0 +1,12 @@
CREATE INDEX ON :Leaf(id);
MATCH (u:Leaf) SET u.value = 1;
MATCH (u) WHERE NOT u:Leaf SET u.value = 0;
MATCH (u) WITH u
ORDER BY u.topological_index DESC
MATCH (u)-->(v) SET u.value = u.value + v.value;
MATCH (u:Leaf {id: "85000"}) SET u.value = 10;
MATCH (u:Leaf {id: "85000"})<-[* bfs]-(v)
WHERE NOT v:Leaf SET v.value = 0;
MATCH (u:Leaf {id: "85000"})<-[* bfs]-(v)
WITH v ORDER BY v.topological_index DESC
MATCH (v)-->(w) SET v.value = v.value + w.value;

125
customers/elliott/generate_dag Executable file
View File

@@ -0,0 +1,125 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Generates a DAG from JSON spec in [config] and outputs nodes to
[filename]_nodes, and edges to [filename]_edges in format convertible
to Memgraph snapshot.
Here's an example JSON spec:
{
"layers": [
{
"name": "A",
"sublayers": 1,
"degree_lo": 1,
"degree_hi": 3,
"nodes": 4
},
{
"name": "B",
"sublayers": 3,
"degree_lo": 2,
"degree_hi": 3,
"nodes": 10
},
{
"name": "C",
"sublayers": 1,
"degree_lo": 1,
"degree_hi": 1,
"nodes": 5
}
]
}
Nodes from each layer will be randomly divided into sublayers. A node can
only have edges pointing to nodes in lower sublayers of the same layer, or
to nodes from the layer directly below it. Out-degree is chosen uniformly
random from [degree_lo, degree_hi] interval."""
import argparse
from itertools import accumulate
import json
import random
def _split_into_sum(n, k):
assert 1 <= n, "n should be at least 1"
assert k <= n, "k shouldn't be greater than n"
xs = [0] + sorted(random.sample(range(1, n), k-1)) + [n]
return [b - a for a, b in zip(xs, xs[1:])]
def generate_dag(graph_config, seed=None):
random.seed(seed)
nodes = []
edges = []
layer_lo = 1
for layer in graph_config:
sublayers = _split_into_sum(layer['nodes'], layer['sublayers'])
sub_range = accumulate([layer_lo] + sublayers)
layer['sublayer_range'] = list(sub_range)
nodes.extend([
(u, layer['name'])
for u in range(layer_lo, layer_lo + layer['nodes'])
])
layer_lo += layer['nodes']
edges = []
for layer, next_layer in zip(graph_config, graph_config[1:]):
degree_lo = layer['degree_lo']
degree_hi = layer['degree_hi']
sub_range = layer['sublayer_range']
sub_range_next = next_layer['sublayer_range']
layer_lo = sub_range[0]
next_layer_hi = sub_range_next[-1]
for sub_lo, sub_hi in zip(sub_range, sub_range[1:]):
for u in range(sub_lo, sub_hi):
num_edges = random.randint(degree_lo, degree_hi)
for _ in range(num_edges):
v = random.randint(sub_hi, next_layer_hi - 1)
edges.append((u, v))
for sub_lo, sub_hi in zip(sub_range_next, sub_range_next[1:]):
for u in range(sub_lo, sub_hi):
v = random.randint(layer_lo, sub_lo - 1)
edges.append((v, u))
return nodes, edges
if __name__ == '__main__':
parser = argparse.ArgumentParser(
formatter_class=argparse.RawDescriptionHelpFormatter,
description=__doc__)
parser.add_argument('config', type=str, help='graph config JSON file')
parser.add_argument('filename', type=str,
help='nodes will be stored to filename_nodes, '
'edges to filename_edges')
parser.add_argument('--seed', type=int,
help='seed for the random generator (default = '
'current system time)')
args = parser.parse_args()
with open(args.config, 'r') as f:
graph_config = json.loads(f.read())['layers']
nodes, edges = generate_dag(graph_config, seed=args.seed)
# print nodes into CSV file
with open('{}_nodes'.format(args.filename), 'w') as out:
out.write('nodeId:ID(Node),name,topological_index:Int,:LABEL\n')
for node_id, layer in nodes:
out.write('{0},{1}{0},{0},{1}\n'.format(node_id, layer))
# print edges into CSV file
with open('{}_edges'.format(args.filename), 'w') as out:
out.write(':START_ID(Node),:END_ID(Node),:TYPE\n')
for u, v in edges:
out.write('{},{},child\n'.format(u, v))

View File

@@ -0,0 +1,39 @@
{
"layers": [
{
"name": "Root",
"sublayers": 1,
"degree_lo": 1,
"degree_hi": 10,
"nodes": 20000
},
{
"name": "Category",
"sublayers": 5,
"degree_lo": 1,
"degree_hi": 10,
"nodes": 20000
},
{
"name": "Group",
"sublayers": 1,
"degree_lo": 20,
"degree_hi": 40,
"nodes": 20000
},
{
"name": "CustomGroup",
"sublayers": 15,
"degree_lo": 20,
"degree_hi": 40,
"nodes": 20000
},
{
"name": "Leaf",
"sublayers": 1,
"degree_lo": 1,
"degree_hi": 1,
"nodes": 20000
}
]
}

View File

@@ -0,0 +1,39 @@
{
"layers": [
{
"name": "Root",
"sublayers": 1,
"degree_lo": 1,
"degree_hi": 10,
"nodes": 20000
},
{
"name": "Category",
"sublayers": 5,
"degree_lo": 1,
"degree_hi": 10,
"nodes": 20000
},
{
"name": "Group",
"sublayers": 1,
"degree_lo": 50,
"degree_hi": 100,
"nodes": 20000
},
{
"name": "CustomGroup",
"sublayers": 15,
"degree_lo": 50,
"degree_hi": 100,
"nodes": 20000
},
{
"name": "Leaf",
"sublayers": 1,
"degree_lo": 50,
"degree_hi": 100,
"nodes": 20000
}
]
}

View File

@@ -0,0 +1,39 @@
{
"layers": [
{
"name": "Root",
"sublayers": 1,
"degree_lo": 10,
"degree_hi": 50,
"nodes": 20000
},
{
"name": "Category",
"sublayers": 5,
"degree_lo": 10,
"degree_hi": 50,
"nodes": 20000
},
{
"name": "Group",
"sublayers": 1,
"degree_lo": 50,
"degree_hi": 100,
"nodes": 20000
},
{
"name": "CustomGroup",
"sublayers": 15,
"degree_lo": 50,
"degree_hi": 100,
"nodes": 20000
},
{
"name": "Leaf",
"sublayers": 1,
"degree_lo": 50,
"degree_hi": 100,
"nodes": 20000
}
]
}

View File

@@ -0,0 +1,3 @@
set(exec_name customers_otto_parallel_connected_components)
add_executable(${exec_name} parallel_connected_components.cpp)
target_link_libraries(${exec_name} memgraph_lib)

View File

@@ -0,0 +1,118 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
This script attempts to evaluate the feasibility of using Memgraph for
Otto group's usecase. The usecase is finding connected componentes in
a large, very sparse graph (cca 220M nodes, 250M edges), based on a dynamic
inclusion / exclusion of edges (w.r.t variable parameters and the source node
type).
This implementation defines a random graph with the given number of nodes
and edges and looks for connected components using breadth-first expansion.
Edges are included / excluded based on a simple expression, only demonstrating
possible usage.
"""
from argparse import ArgumentParser
import logging
from time import time
from collections import defaultdict
from math import log2
from random import randint
from neo4j.v1 import GraphDatabase
log = logging.getLogger(__name__)
def generate_graph(sess, node_count, edge_count):
# An index that will speed-up edge creation.
sess.run("CREATE INDEX ON :Node(id)").consume()
# Create the given number of nodes with a randomly selected type from:
# [0.5, 1.5, 2.5].
sess.run(("UNWIND range(0, {} - 1) AS id CREATE "
"(:Node {{id: id, type: 0.5 + tointeger(rand() * 3)}})").format(
node_count)).consume()
# Create the given number of edges, each with a 'value' property of
# a random [0, 3.0) float. Each edge connects two random nodes, so the
# expected node degree is (edge_count * 2 / node_count). Generate edges
# so the connectivity is non-uniform (to produce connected components of
# various sizes).
sess.run(("UNWIND range(0, {0} - 1) AS id WITH id "
"MATCH (from:Node {{id: tointeger(rand() * {1})}}), "
"(to:Node {{id: tointeger(rand() * {1} * id / {0})}}) "
"CREATE (from)-[:Edge {{value: 3 * rand()}}]->(to)").format(
edge_count, node_count)).consume()
def get_connected_ids(sess, node_id):
# Matches a node with the given ID and returns the IDs of all the nodes
# it is connected to. Note that within the BFS lambda expression there
# is an expression used to filter out edges expanded over.
return sess.run((
"MATCH (from:Node {{id: {}}})-"
"[*bfs (e, n | abs(from.type - e.value) < 0.80)]-(d) "
"RETURN count(*) AS c").format(node_id)).data()[0]['c']
def parse_args():
parser = ArgumentParser(description=__doc__)
parser.add_argument('--endpoint', type=str, default='localhost:7687',
help='Memgraph instance endpoint. ')
parser.add_argument('--node-count', type=int, default=1000,
help='The number of nodes in the graph')
parser.add_argument('--edge-count', type=int, default=1000,
help='The number of edges in the graph')
parser.add_argument('--sample-count', type=int, default=None,
help='The number of samples to take')
return parser.parse_args()
def main():
args = parse_args()
logging.basicConfig(level=logging.INFO)
log.info("Memgraph - Otto test database generator")
logging.getLogger("neo4j").setLevel(logging.WARNING)
driver = GraphDatabase.driver(
'bolt://' + args.endpoint,
auth=("ignored", "ignored"),
encrypted=False)
sess = driver.session()
sess.run("MATCH (n) DETACH DELETE n").consume()
log.info("Generating graph with %s nodes and %s edges...",
args.node_count, args.edge_count)
generate_graph(sess, args.node_count, args.edge_count)
# Track which vertices have been found as part of a component.
start_time = time()
max_query_time = 0
log.info("Looking for connected components...")
# Histogram of log2 sizes of connected components found.
histogram = defaultdict(int)
sample_count = args.sample_count if args.sample_count else args.node_count
for i in range(sample_count):
node_id = randint(0, args.node_count - 1)
query_start_time = time()
log2_size = int(log2(1 + get_connected_ids(sess, node_id)))
max_query_time = max(max_query_time, time() - query_start_time)
histogram[log2_size] += 1
elapsed = time() - start_time
log.info("Connected components found in %.2f sec (avg %.2fms, max %.2fms)",
elapsed, elapsed / sample_count * 1000, max_query_time * 1000)
log.info("Component size histogram (count | range)")
for log2_size, count in sorted(histogram.items()):
log.info("\t%5d | %d - %d", count, 2 ** log2_size,
2 ** (log2_size + 1) - 1)
sess.close()
driver.close()
if __name__ == '__main__':
main()

View File

@@ -0,0 +1,207 @@
#include <algorithm>
#include <limits>
#include <mutex>
#include <random>
#include <set>
#include <stack>
#include <thread>
#include "gflags/gflags.h"
#include "glog/logging.h"
#include "data_structures/union_find.hpp"
#include "database/graph_db.hpp"
#include "database/graph_db_accessor.hpp"
#include "storage/property_value.hpp"
#include "threading/sync/spinlock.hpp"
#include "utils/bound.hpp"
#include "utils/timer.hpp"
DEFINE_int32(thread_count, 1, "Number of threads");
DEFINE_int32(vertex_count, 1000, "Number of vertices");
DEFINE_int32(edge_count, 1000, "Number of edges");
DECLARE_int32(gc_cycle_sec);
static const std::string kLabel{"kLabel"};
static const std::string kProperty{"kProperty"};
void GenerateGraph(database::GraphDb &db) {
{
database::GraphDbAccessor dba{db};
dba.BuildIndex(dba.Label(kLabel), dba.Property(kProperty));
dba.Commit();
}
// Randomize the sequence of IDs of created vertices and edges to simulate
// real-world lack of locality.
auto make_id_vector = [](size_t size) {
gid::Generator generator{0};
std::vector<gid::Gid> ids(size);
for (size_t i = 0; i < size; ++i)
ids[i] = generator.Next(std::experimental::nullopt);
std::random_shuffle(ids.begin(), ids.end());
return ids;
};
std::vector<VertexAccessor> vertices;
vertices.reserve(FLAGS_vertex_count);
{
CHECK(FLAGS_vertex_count % FLAGS_thread_count == 0)
<< "Thread count must be a factor of vertex count";
LOG(INFO) << "Generating " << FLAGS_vertex_count << " vertices...";
utils::Timer timer;
auto vertex_ids = make_id_vector(FLAGS_vertex_count);
std::vector<std::thread> threads;
SpinLock vertices_lock;
for (int i = 0; i < FLAGS_thread_count; ++i) {
threads.emplace_back([&db, &vertex_ids, &vertices, &vertices_lock, i]() {
database::GraphDbAccessor dba{db};
auto label = dba.Label(kLabel);
auto property = dba.Property(kProperty);
auto batch_size = FLAGS_vertex_count / FLAGS_thread_count;
for (int j = i * batch_size; j < (i + 1) * batch_size; ++j) {
auto vertex = dba.InsertVertex(vertex_ids[j]);
vertex.add_label(label);
vertex.PropsSet(property, static_cast<int64_t>(vertex_ids[j]));
vertices_lock.lock();
vertices.emplace_back(vertex);
vertices_lock.unlock();
}
dba.Commit();
});
}
for (auto &t : threads) t.join();
LOG(INFO) << "Generated " << FLAGS_vertex_count << " vertices in "
<< timer.Elapsed().count() << " seconds.";
}
{
database::GraphDbAccessor dba{db};
for (int i = 0; i < FLAGS_vertex_count; ++i)
vertices[i] = *dba.Transfer(vertices[i]);
LOG(INFO) << "Generating " << FLAGS_edge_count << " edges...";
auto edge_ids = make_id_vector(FLAGS_edge_count);
std::mt19937 pseudo_rand_gen{std::random_device{}()};
std::uniform_int_distribution<> rand_dist{0, FLAGS_vertex_count - 1};
auto edge_type = dba.EdgeType("edge");
utils::Timer timer;
for (int i = 0; i < FLAGS_edge_count; ++i)
dba.InsertEdge(vertices[rand_dist(pseudo_rand_gen)],
vertices[rand_dist(pseudo_rand_gen)], edge_type,
edge_ids[i]);
dba.Commit();
LOG(INFO) << "Generated " << FLAGS_edge_count << " edges in "
<< timer.Elapsed().count() << " seconds.";
}
}
auto EdgeIteration(database::GraphDb &db) {
database::GraphDbAccessor dba{db};
int64_t sum{0};
for (auto edge : dba.Edges(false)) sum += edge.from().gid() + edge.to().gid();
return sum;
}
auto VertexIteration(database::GraphDb &db) {
database::GraphDbAccessor dba{db};
int64_t sum{0};
for (auto v : dba.Vertices(false))
for (auto e : v.out()) sum += e.gid() + e.to().gid();
return sum;
}
auto ConnectedComponentsEdges(database::GraphDb &db) {
UnionFind<int64_t> connectivity{FLAGS_vertex_count};
database::GraphDbAccessor dba{db};
for (auto edge : dba.Edges(false))
connectivity.Connect(edge.from().gid(), edge.to().gid());
return connectivity.Size();
}
auto ConnectedComponentsVertices(database::GraphDb &db) {
UnionFind<int64_t> connectivity{FLAGS_vertex_count};
database::GraphDbAccessor dba{db};
for (auto from : dba.Vertices(false)) {
for (auto out_edge : from.out())
connectivity.Connect(from.gid(), out_edge.to().gid());
}
return connectivity.Size();
}
auto ConnectedComponentsVerticesParallel(database::GraphDb &db) {
UnionFind<int64_t> connectivity{FLAGS_vertex_count};
SpinLock connectivity_lock;
// Define bounds of vertex IDs for each thread to use.
std::vector<PropertyValue> bounds;
for (int64_t i = 0; i < FLAGS_thread_count; ++i)
bounds.emplace_back(i * FLAGS_vertex_count / FLAGS_thread_count);
bounds.emplace_back(std::numeric_limits<int64_t>::max());
std::vector<std::thread> threads;
for (int i = 0; i < FLAGS_thread_count; ++i) {
threads.emplace_back(
[&connectivity, &connectivity_lock, &bounds, &db, i]() {
database::GraphDbAccessor dba{db};
for (auto from :
dba.Vertices(dba.Label(kLabel), dba.Property(kProperty),
utils::MakeBoundInclusive(bounds[i]),
utils::MakeBoundExclusive(bounds[i + 1]), false)) {
for (auto out_edge : from.out()) {
std::lock_guard<SpinLock> lock{connectivity_lock};
connectivity.Connect(from.gid(), out_edge.to().gid());
}
}
});
}
for (auto &t : threads) t.join();
return connectivity.Size();
}
auto Expansion(database::GraphDb &db) {
std::vector<int> component_ids(FLAGS_vertex_count, -1);
int next_component_id{0};
std::stack<VertexAccessor> expansion_stack;
database::GraphDbAccessor dba{db};
for (auto v : dba.Vertices(false)) {
if (component_ids[v.gid()] != -1) continue;
auto component_id = next_component_id++;
expansion_stack.push(v);
while (!expansion_stack.empty()) {
auto next_v = expansion_stack.top();
expansion_stack.pop();
if (component_ids[next_v.gid()] != -1) continue;
component_ids[next_v.gid()] = component_id;
for (auto e : next_v.out()) expansion_stack.push(e.to());
for (auto e : next_v.in()) expansion_stack.push(e.from());
}
}
return next_component_id;
}
int main(int argc, char **argv) {
gflags::ParseCommandLineFlags(&argc, &argv, true);
google::InitGoogleLogging(argv[0]);
FLAGS_gc_cycle_sec = -1;
database::SingleNode db;
GenerateGraph(db);
auto timed_call = [&db](auto callable, const std::string &descr) {
LOG(INFO) << "Running " << descr << "...";
utils::Timer timer;
auto result = callable(db);
LOG(INFO) << "\tDone in " << timer.Elapsed().count()
<< " seconds, result: " << result;
};
timed_call(EdgeIteration, "Edge iteration");
timed_call(VertexIteration, "Vertex iteration");
timed_call(ConnectedComponentsEdges, "Connected components - Edges");
timed_call(ConnectedComponentsVertices, "Connected components - Vertices");
timed_call(ConnectedComponentsVerticesParallel,
"Parallel connected components - Vertices");
timed_call(Expansion, "Expansion");
return 0;
}

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@@ -0,0 +1,5 @@
WITH tointeger(rand() * 40000000) AS from_id
MATCH (from:Node {id : from_id}) WITH from
MATCH path = (from)-[*bfs..50 (e, n | degree(n) < 50)]->(to) WITH path LIMIT 10000 WHERE to.fraudulent
RETURN path, size(path)

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@@ -0,0 +1,31 @@
{
"indexes":[
"Node.id"
],
"nodes":[
{
"count":40000000,
"labels":[
"Node"
],
"properties":{
"id":{
"type":"counter",
"param":"Node.id"
},
"fraudulent":{
"type":"bernoulli",
"param":0.0005
}
}
}
],
"edges":[
{
"count":80000000,
"from":"Node",
"to":"Node",
"type":"Edge"
}
]
}

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@@ -0,0 +1,20 @@
{
"indexes" : ["Card.id", "Pos.id", "Transaction.fraud_reported"],
"nodes" : [
{
"count_per_worker" : 1250000,
"label" : "Card"
},
{
"count_per_worker" : 1250000,
"label" : "Pos"
},
{
"count_per_worker" : 2500000,
"label" : "Transaction"
}
],
"compromised_pos_probability" : 0.2,
"fraud_reported_probability" : 0.1,
"hop_probability" : 0.1
}

269
docs/dev/code-review.md Normal file
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@@ -0,0 +1,269 @@
# Code Review Guidelines
This chapter describes some of the things you should be on the lookout when
reviewing someone else's code.
## Exceptions
Although the Google C++ Style Guide forbids exceptions, we do allow them in
our codebase. As a reviewer you should watch out for the following.
The documentation of throwing functions needs to be in-sync with the
implementation. This must be enforced recursively. I.e. if a function A now
throws a new exception, and the function B uses A, then B needs to handle that
exception or have its documentation updated and so on. Naturally, the same
applies when an exception is removed.
Transitive callers of the function which throws a new exception must be OK
with that. This ties into the previous point. You need to check that all users
of the new exception either handle it correctly or propagate it.
Exceptions should not escape out of class destructors, because that will
terminate the program. The code should be changed so that such cases are not
possible.
Exceptions being thrown in class constructors. Although this is well defined
in C++, it usually implies that a constructor is doing too much work and the
class construction & initialization should be redesigned. Usual approaches are
using the (Static) Factory Method pattern or having some sort of an
initialization method that needs to be called after the construction is done.
Prefer the Factory Method.
Don't forget that STL functions may also throw!
## Pointers & References
In cases when some code passes a pointer or reference, or if a code stores a
pointer or reference you should take a careful look at the following.
* Lifetime of the pointed to value (this includes both ownership and
multithreaded access).
* In case of a class, check validity of destructor and move/copy
constructors.
* Is the pointed to value mutated, if not it should be `const` (`const Type
*` or `const Type &`).
## Allocators & Memory Resources
With the introduction of polymorphic allocators (C++17 `<memory_resource>` and
our `utils/memory.hpp`) we get a more convenient type signatures for
containers so as to keep the outward facing API nice. This convenience comes
at a cost of less static checks on the type level due to type erasure.
For example:
std::pmr::vector<int> first_vec(std::pmr::null_memory_resource());
std::pmr::vector<int> second_vec(std::pmr::new_delete_resource());
second_vec = first_vec // What happens here?
// Or with our implementation
utils::MonotonicBufferResource monotonic_memory(1024);
std::vector<int, utils::Allocator<int>> first_vec(&monotonic_memory);
std::vector<int, utils::Allocator<int>> second_vec(utils::NewDeleteResource());
second_vec = first_vec // What happens here?
In the above, both `first_vec` and `second_vec` have the same type, but have
*different* allocators! This can lead to ambiguity when moving or copying
elements between them.
You need to watch out for the following.
* Swapping can lead to undefined behaviour if the allocators are not equal.
* Is the move construction done with the right allocator.
* Is the move assignment done correctly, also it may throw an exception.
* Is the copy construction done with the right allocator.
* Is the copy assignment done correctly.
* Using `auto` makes allocator propagation rules rather ambiguous.
## Classes & Object Oriented Programming
A common mistake is to use classes, inheritance and "OOP" when it's not
needed. This sections shows examples of encountered cases.
### Classes without (Meaningful) Members
class MyCoolClass {
public:
int BeCool(int a, int b) { return a + b; }
void SaySomethingCool() { std::cout << "Hello!"; }
};
The above class has no members (i.e. state) which affect the behaviour of
methods. This class should need not exist, it can be easily replaced with a
more modular (and shorter) design -- top level functions.
int BeCool(int a, int b) { return a + b; }
void SaySomethingCool() { std::cout << "Hello!"; }
### Classes with a Single Public Method
clas MyAwesomeClass {
public:
MyAwesomeClass(int state) : state_(state) {}
int GetAwesome() { return GetAwesomeImpl() + 1; }
private:
int state_;
int GetAwesomeImpl() { return state_; }
};
The above class has a `state_` and even a private method, but there's only one
public method -- `GetAwesome`.
You should check "Does the stored state have any meaningful influence on the
public method?", similarly to the previous point.
In the above case it doesn't, and the class should be replaced with a public
function in `.hpp` while the private method should become a private function
in `.cpp` (static or in anonymous namespace).
// hpp
int GetAwesome(int state);
// cpp
namespace {
int GetAwesomeImpl(int state) { return state; }
}
int GetAwesome(int state) { return GetAwesomeImpl(state) + 1; }
A counterexample is when the state is meaningful.
class Counter {
public:
Counter(int state) : state_(state) {}
int Get() { return state_++; }
private:
int state_;
};
But even that could be replaced with a closure.
auto MakeCounter(int state) {
return [state]() mutable { return state++; };
}
### Private Methods
Instead of private methods, top level functions should be preferred. The
reasoning is completely explained in "Effective C++" Item 23 by Scott Meyers.
In our codebase, even improvements to compilation times can be noticed if
private methods in interface (`.hpp`) files are replaced with top level
functions in implementation (`.cpp`) files.
### Inheritance
The rule is simple -- if there are no virtual methods (but maybe destructor),
then the class should be marked as `final` and never inherited.
If there are virtual methods (i.e. class is meant to be inherited), make sure
that either a public virtual destructor or a protected non-virtual destructor
exist. See "Effective C++" Item 7 by Scott Meyers. Also take a look at
"Effective C++" Items 32---39 by Scott Meyers.
An example of how inheritance with no virtual methods is replaced with
composition.
class MyBase {
public:
virtual ~MyBase() {}
void DoSomethingBase() { ... }
};
class MyDerived final : public MyBase {
public:
void DoSomethingNew() { ... DoSomethingBase(); ... }
};
With composition, the above becomes.
class MyBase final {
public:
void DoSomethingBase() { ... }
};
class MyDerived final {
MyBase base_;
public:
void DoSomethingNew() { ... base_.DoSomethingBase(); ... }
};
The composition approach is preferred as it encapsulates the fact that
`MyBase` is used for the implementation and users only interact with the
public interface of `MyDerived`. Additionally, you can easily replace `MyBase
base_;` with a C++ PIMPL idiom (`std::unique_ptr<MyBase> base_;`) to make the
code more modular with regards to compilation.
More advanced C++ users will recognize that the encapsulation feature of the
non-PIMPL composition can be replaced with private inheritance.
class MyDerived final : private MyBase {
public:
void DoSomethingNew() { ... MyBase::DoSomethingBase(); ... }
};
One of the common "counterexample" is the ability to store objects of
different type in a container or pass them to a function. Unfortunately, this
is not that good of a design. For example.
class MyBase {
... // No virtual methods (but the destructor)
};
class MyFirstClass final : public MyBase { ... };
class MySecondClass final : public MyBase { ... };
std::vector<std::unique_ptr<MyBase>> first_and_second_classes;
first_and_second_classes.push_back(std::make_unique<MyFirstClass>());
first_and_second_classes.push_back(std::make_unique<MySecondClass>());
void FunctionOnFirstOrSecond(const MyBase &first_or_second, ...) { ... }
With C++17, the containers for different types should be implemented with
`std::variant`, and as before the functions can be templated.
class MyFirstClass final { ... };
class MySecondClass final { ... };
std::vector<std::variant<MyFirstClass, MySecondClass>> first_and_second_classes;
// Notice no heap allocation, since we don't store a pointer
first_and_second_classes.emplace_back(MyFirstClass());
first_and_second_classes.emplace_back(MySecondClass());
// You can also use `std::variant` here instead of template
template <class TFirstOrSecond>
void FunctionOnFirstOrSecond(const TFirstOrSecond &first_or_second, ...) { ... }
Naturally, if the base class has meaningful virtual methods (i.e. other than
destructor) it maybe is OK to use inheritance but also consider alternatives.
See "Effective C++" Items 32---39 by Scott Meyers.
### Multiple Inheritance
Multiple inheritance should not be used unless all base classes are pure
interface classes. This decision is inherited from [Google C++ Style
Guide](https://google.github.io/styleguide/cppguide.html#Inheritance). For
example on how to design with and around multiple inheritance refer to
"Effective C++" Item 40 by Scott Meyers.
Naturally, if there *really* is no better design, then multiple inheritance is
allowed. An example of this can be found in our codebase when inheriting
Visitor classes (though even that could be replaced with `std::variant` for
example).
## Code Format & Style
If something doesn't conform to our code formatting and style, just refer the
author to either [C++ Style](cpp-code-conventions.md) or [Other Code
Conventions](other-code-conventions.md).

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# C++ Code Conventions
This chapter describes code conventions which should be followed when writing
C++ code.
## Code Style
Memgraph uses the
[Google Style Guide for C++](https://google.github.io/styleguide/cppguide.html)
in most of its code. You should follow them whenever writing new code.
Besides following the style guide, take a look at
[Code Review Guidelines](code-review.md) for common design issues and pitfalls
with C++ as well as [Required Reading](required-reading.md).
### Often Overlooked Style Conventions
#### Pointers & References
References provide a shorter syntax for accessing members and better declare
the intent that a pointer *should* not be `nullptr`. They do not prevent
accessing a `nullptr` and obfuscate the client/calling code because the
reference argument is passed just like a value. Errors with such code have
been very difficult to debug. Therefore, pointers are always used. They will
not prevent bugs but will make some of them more obvious when reading code.
The only time a reference can be used is if it is `const`. Note that this
kind of reference is not allowed if it is stored somewhere, i.e. in a class.
You should use a pointer to `const` then. The primary reason being is that
references obscure the semantics of moving an object, thus making bugs with
references pointing to invalid memory harder to track down.
[Style guide reference](https://google.github.io/styleguide/cppguide.html#Reference_Arguments)
#### Constructors & RAII
RAII (Resource Acquisition is Initialization) is a nice mechanism for managing
resources. It is especially useful when exceptions are used, such as in our
code. Unfortunately, they do have 2 major downsides.
* Only exceptions can be used for to signal failure.
* Calls to virtual methods are not resolved as expected.
For those reasons the style guide recommends minimal work that cannot fail.
Using virtual methods or doing a lot more should be delegated to some form of
`Init` method, possibly coupled with static factory methods. Similar rules
apply to destructors, which are not allowed to even throw exceptions.
[Style guide reference](https://google.github.io/styleguide/cppguide.html#Doing_Work_in_Constructors)
### Additional Style Conventions
Old code may have broken Google C++ Style accidentally, but the new code
should adhere to it as close as possible. We do have some exceptions
to Google style as well as additions for unspecified conventions.
#### Using C++ Exceptions
Unlike Google, we do not forbid using exceptions.
But, you should be very careful when using them and introducing new ones. They
are indeed handy, but cause problems with understanding the control flow since
exceptions are another form of `goto`. It also becomes very hard to determine
that the program is in correct state after the stack is unwound and the thrown
exception handled. Other than those issues, throwing exceptions in destructors
will terminate the program. The same will happen if a thread doesn't handle an
exception even though it is not the main thread.
[Style guide reference](https://google.github.io/styleguide/cppguide.html#Exceptions)
In general, when introducing a new exception, either via `throw` statement or
calling a function which throws, you must examine all transitive callers and
update their implementation and/or documentation.
#### Assertions
We use `CHECK` and `DCHECK` macros from glog library. You are encouraged to
use them as often as possible to both document and validate various pre and
post conditions of a function.
`CHECK` remains even in release build and should be preferred over it's cousin
`DCHECK` which only exists in debug builds. The primary reason is that you
want to trigger assertions in release builds in case the tests didn't
completely validate all code paths. It is better to fail fast and crash the
program, than to leave it in undefined state and potentially corrupt end
user's work. In cases when profiling shows that `CHECK` is causing visible
slowdown you should switch to `DCHECK`.
#### Template Parameter Naming
Template parameter names should start with capital letter 'T' followed by a
short descriptive name. For example:
```cpp
template <typename TKey, typename TValue>
class KeyValueStore
```
## Code Formatting
You should install `clang-format` and run it on code you change or add. The
root of Memgraph's project contains the `.clang-format` file, which specifies
how formatting should behave. Running `clang-format -style=file` in the
project's root will read the file and behave as expected. For ease of use, you
should integrate formatting with your favourite editor.
The code formatting isn't enforced, because sometimes manual formatting may
produce better results. Though, running `clang-format` is strongly encouraged.
## Documentation
Besides following the comment guidelines from [Google Style
Guide](https://google.github.io/styleguide/cppguide.html#Comments), your
documentation of the public API should be
[Doxygen](https://github.com/doxygen/doxygen) compatible. For private parts of
the code or for comments accompanying the implementation, you are free to
break doxygen compatibility. In both cases, you should write your
documentation as full sentences, correctly written in English.
## Doxygen
To start a Doxygen compatible documentation string, you should open your
comment with either a JavaDoc style block comment (`/**`) or a line comment
containing 3 slashes (`///`). Take a look at the 2 examples below.
### Block Comment
```cpp
/**
* One sentence, brief description.
*
* Long form description.
*/
```
### Line Comment
```cpp
/// One sentence, brief description.
///
/// Long form description.
```
If you only have a brief description, you may collapse the documentation into
a single line.
### Block Comment
```cpp
/** Brief description. */
```
### Line Comment
```cpp
/// Brief description.
```
Whichever style you choose, keep it consistent across the whole file.
Doxygen supports various commands in comments, such as `@file` and `@param`.
These help Doxygen to render specified things differently or to track them for
cross referencing. If you want to learn more, take a look at these two links:
* http://www.stack.nl/~dimitri/doxygen/manual/docblocks.html
* http://www.stack.nl/~dimitri/doxygen/manual/commands.html
## Examples
Below are a few examples of documentation from the codebase.
### Function
```cpp
/**
* Removes whitespace characters from the start and from the end of a string.
*
* @param s String that is going to be trimmed.
*
* @return Trimmed string.
*/
inline std::string Trim(const std::string &s);
```
### Class
```cpp
/** Base class for logical operators.
*
* Each operator describes an operation, which is to be performed on the
* database. Operators are iterated over using a @c Cursor. Various operators
* can serve as inputs to others and thus a sequence of operations is formed.
*/
class LogicalOperator
: public ::utils::Visitable<HierarchicalLogicalOperatorVisitor> {
public:
/** Constructs a @c Cursor which is used to run this operator.
*
* @param GraphDbAccessor Used to perform operations on the database.
*/
virtual std::unique_ptr<Cursor> MakeCursor(GraphDbAccessor &db) const = 0;
/** Return @c Symbol vector where the results will be stored.
*
* Currently, outputs symbols are only generated in @c Produce operator.
* @c Skip, @c Limit and @c OrderBy propagate the symbols from @c Produce (if
* it exists as input operator). In the future, we may want this method to
* return the symbols that will be set in this operator.
*
* @param SymbolTable used to find symbols for expressions.
* @return std::vector<Symbol> used for results.
*/
virtual std::vector<Symbol> OutputSymbols(const SymbolTable &) const {
return std::vector<Symbol>();
}
virtual ~LogicalOperator() {}
};
```
### File Header
```cpp
/// @file visitor.hpp
///
/// This file contains the generic implementation of visitor pattern.
///
/// There are 2 approaches to the pattern:
///
/// * classic visitor pattern using @c Accept and @c Visit methods, and
/// * hierarchical visitor which also uses @c PreVisit and @c PostVisit
/// methods.
///
/// Classic Visitor
/// ===============
///
/// Explanation on the classic visitor pattern can be found from many
/// sources, but here is the link to hopefully most easily accessible
/// information: https://en.wikipedia.org/wiki/Visitor_pattern
///
/// The idea behind the generic implementation of classic visitor pattern is to
/// allow returning any type via @c Accept and @c Visit methods. Traversing the
/// class hierarchy is relegated to the visitor classes. Therefore, visitor
/// should call @c Accept on children when visiting their parents. To implement
/// such a visitor refer to @c Visitor and @c Visitable classes.
///
/// Hierarchical Visitor
/// ====================
///
/// Unlike the classic visitor, the intent of this design is to allow the
/// visited structure itself to control the traversal. This way the internal
/// children structure of classes can remain private. On the other hand,
/// visitors may want to differentiate visiting composite types from leaf types.
/// Composite types are those which contain visitable children, unlike the leaf
/// nodes. Differentiation is accomplished by providing @c PreVisit and @c
/// PostVisit methods, which should be called inside @c Accept of composite
/// types. Regular @c Visit is only called inside @c Accept of leaf types.
/// To implement such a visitor refer to @c CompositeVisitor, @c LeafVisitor and
/// @c Visitable classes.
///
/// Implementation of hierarchical visiting is modelled after:
/// http://wiki.c2.com/?HierarchicalVisitorPattern
```

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@@ -0,0 +1,288 @@
// dot -Tpng dependencies.dot -o /path/to/output.png
// TODO (buda): Put PropertyValueStore to storage namespace
digraph {
// At the beginning of each block there is a default style for that block
label="Memgraph Dependencies Diagram"; fontname="Roboto Bold"; fontcolor=black;
fontsize=26; labelloc=top; labeljust=right;
compound=true; // If true, allow edges between clusters
rankdir=TB; // Alternatives: LR
node [shape=record fontname="Roboto", fontsize=12, fontcolor=white];
edge [color="#B5AFB7"];
// -- Legend --
// dir=both arrowtail=diamond arrowhead=vee -> group ownership
// dir=both arrowtail=none, arrowhead=vee -> ownership; stack or uptr
subgraph cluster_tcp_end_client_communication {
label="TCP End Client Communication"; fontsize=14;
node [style=filled, color="#DD2222" fillcolor="#DD2222"];
// Owned elements
"communication::Server";
"io::network::Socket";
// Intracluster connections
"communication::Server" -> "io::network::Socket"
[label="socket_" dir=both arrowtail=none arrowhead=vee];
}
subgraph cluster_bolt_server {
label="Bolt Server"; fontsize=14;
node [style=filled, color="#62A2CA" fillcolor="#62A2CA"];
// Owned elements
"communication::bolt::SessionData";
"communication::bolt::Session";
"communication::bolt::Encoder";
"communication::bolt::Decoder";
// Intracluster connections
"communication::bolt::Session" -> "communication::bolt::Encoder"
[label="encoder_", dir=both arrowtail=none, arrowhead=vee];
"communication::bolt::Session" -> "communication::bolt::Decoder"
[label="decoder_", dir=both arrowtail=none, arrowhead=vee];
}
subgraph cluster_opencypher_engine {
label="openCypher Engine"; fontsize=14;
node [style=filled, color="#68BDF6" fillcolor="#68BDF6"];
// Owned Elements
"query::Interpreter";
"query::AstTreeStorage";
"query::TypedValue"
"query::Path";
"query::Simbol";
"query::Context";
"query::ExpressionEvaluator";
"query::Frame";
"query::SymbolTable";
"query::plan::LogicalOperator";
"query::plan::Cursor";
"query::plan::CostEstimator";
// Intracluster connections
"query::Interpreter" -> "query::AstTreeStorage"
[label="ast_cache" dir=both arrowtail=diamond arrowhead=vee];
"query::TypedValue" -> "query::Path";
"query::plan::Cursor" -> "query::Frame";
"query::plan::Cursor" -> "query::Context";
"query::plan::LogicalOperator" -> "query::Symbol";
"query::plan::LogicalOperator" -> "query::SymbolTable";
"query::plan::LogicalOperator" -> "query::plan::Cursor";
}
subgraph cluster_storage {
label="Storage" fontsize=14;
node [style=filled, color="#FB6E00" fillcolor="#FB6E00"];
// Owned Elements
"database::GraphDb";
"database::GraphDbAccessor";
"storage::Record";
"storage::Vertex";
"storage::Edge";
"storage::RecordAccessor";
"storage::VertexAccessor";
"storage::EdgeAccessor";
"storage::Common";
"storage::Label";
"storage::EdgeType";
"storage::Property";
"storage::compression";
"storage::SingleNodeConcurrentIdMapper";
"storage::Location";
"storage::StorageTypesLocation";
"PropertyValueStore";
"storage::RecordLock";
"mvcc::Version";
"mvcc::Record";
"mvcc::VersionList";
// Intracluster connections
"storage::VertexAccessor" -> "storage::RecordAccessor"
[arrowhead=onormal];
"storage::EdgeAccessor" -> "storage::RecordAccessor"
[arrowhead=onormal];
"storage::RecordAccessor" -> "database::GraphDbAccessor"
[style=dashed arrowhead=vee];
"storage::Vertex" -> "mvcc::Record"
[arrowhead=onormal];
"storage::Edge" -> "mvcc::Record"
[arrowhead=onormal];
"storage::Edge" -> "PropertyValueStore"
[arrowhead=vee];
"storage::Vertex" -> "PropertyValueStore"
[arrowhead=vee];
"storage::Edge" -> "mvcc::VersionList"
[label="from,to" arrowhead=vee style=dashed];
"storage::VertexAccessor" -> "storage::Vertex"
[arrowhead=vee];
"storage::EdgeAccessor" -> "storage::Edge"
[arrowhead=vee];
"storage::SingleNodeConcurrentIdMapper" -> "storage::StorageTypesLocation"
[arrowhead=vee];
"storage::StorageTypesLocation" -> "storage::Location"
[arrowhead=vee];
"storage::Storage" -> "storage::StorageTypesLocation"
[arrowhead=vee];
"storage::Property" -> "storage::Common"
[arrowhead=onormal];
"storage::Label" -> "storage::Common"
[arrowhead=onormal];
"storage::EdgeType" -> "storage::Common"
[arrowhead=onormal];
"storage::Property" -> "storage::Location"
[arrowhead=vee];
"PropertyValueStore" -> "storage::Property"
[arrowhead=vee];
"PropertyValueStore" -> "storage::Location"
[arrowhead=vee];
"database::GraphDbAccessor" -> "database::GraphDb"
[arrowhead=vee];
"database::GraphDbAccessor" -> "tx::TransactionId"
[arrowhead=vee];
"mvcc::VersionList" -> "storge::RecordLock"
[label="lock" arrowhead=vee];
"mvcc::VersionList" -> "mvcc::Record"
[label="head" arrowhead=vee];
"mvcc::Record" -> "mvcc::Version"
[arrowhead=onormal];
// Explicit positioning
{rank=same;
"database::GraphDbAccessor";
"storage::VertexAccessor";
"storage::EdgeAccessor";}
{rank=same;
"storage::Common";
"storage::compression";}
}
subgraph cluster_properties_on_disk {
label="Properties on Disk" fontsize=14;
node [style=filled, color="#102647" fillcolor="#102647"];
// Owned Elements
"storage::KVStore";
"rocksdb";
// Intracluster connections
"storage::KVStore" -> "rocksdb";
}
subgraph cluster_distributed {
label="Distributed" fontsize=14;
node [style=filled, color="#FFC500" fillcolor="#FFC500"];
// Owned Elements
"distributed::DataManager";
"distributed::DataRpcClients";
// Intracluster connections
"distributed::DataManager" -> "distributed::DataRpcClients"
[arrowhead=vee];
"storage::RecordAccessor" -> "distributed::DataManager"
[style=dashed arrowhead=vee];
}
subgraph cluster_dynamic_partitioning {
label="Dynamic Partitioning" fontsize=14;
node [style=filled, color="#720096" fillcolor="#720096"];
// Owned Elements
"DynamicPartitioner";
}
subgraph cluster_security {
label="Security" fontsize=14;
node [style=filled, color="#857F87" fillcolor="#857F87"];
// Owned Elements
"Communication Encryption";
"Data Encryption";
"Access Control";
"Audit Logging";
}
subgraph cluster_web_dashboard {
label="Dashaboard" fontsize=14;
node [style=filled, color="#FF0092" fillcolor="#FF0092"];
// Owned Elements
"Memgraph Ops / Memgraph Cockpit";
}
subgraph cluster_rpc {
label="RPC" fontsize=14;
node [style=filled, color="#857F87" fillcolor="#857F87"];
// Owned Elements
"communication::rpc::Server";
"communication::rpc::Client";
}
subgraph cluster_ingestion {
label="Ingestion" fontsize=14;
node [style=filled, color="#0B6D88" fillcolor="#0B6D88"];
// Owned Elements
"Extract";
"Transform";
"Load";
"Amazon S3";
"Kafka";
// Intracluster connections
"Extract" -> "Amazon S3";
"Extract" -> "Kafka";
// Explicit positioning
{rank=same;"Extract";"Transform";"Load";}
}
// -- Intercluster connections --
// cluster_tcp_end_client_communication -- cluster_bolt_server
"communication::Server" -> "communication::bolt::SessionData" [color=black];
"communication::Server" -> "communication::bolt::Session" [color=black];
// cluster_bolt_server -> cluster_storage
"communication::bolt::SessionData" -> "database::GraphDb" [color=red];
"communication::bolt::Session" -> "database::GraphDbAccessor" [color=red];
// cluster_bolt_server -> cluster_opencypher_engine
"communication::bolt::SessionData" -> "query::Interpreter" [color=red];
// cluster_opencypher_engine -- cluster_storage
"query::Interpreter" -> "database::GraphDbAccessor" [color=black];
"query::Interpreter" -> "storage::VertexAccessor" [color=black];
"query::Interpreter" -> "storage::EdgeAccessor" [color=black];
"query::TypedValue" -> "storage::VertexAccessor" [color=black];
"query::TypedValue" -> "storage::EdgeAccessor" [color=black];
"query::Path" -> "storage::VertexAccessor"
[label="vertices" dir=both arrowtail=diamond arrowhead=vee color=black];
"query::Path" -> "storage::EdgeAccessor"
[label="edges" dir=both arrowtail=diamond arrowhead=vee color=black];
"query::plan::LogicalOperator" -> "database::GraphDbAccessor"
[color=black arrowhead=vee];
// cluster_distributed -- cluster_storage
"distributed::DataManager" -> "database::GraphDb"
[arrowhead=vee style=dashed color=red];
"distributed::DataManager" -> "tx::TransactionId"
[label="ves_caches_key" dir=both arrowhead=none arrowtail=diamond
color=red];
"distributed::DataManager" -> "storage::Vertex"
[label="vertices_caches" dir=both arrowhead=none arrowtail=diamond
color=red];
"distributed::DataManager" -> "storage::Edge"
[label="edges_caches" dir=both arrowhead=none arrowtail=diamond
color=red];
// cluster_storage -- cluster_properties_on_disk
"PropertyValueStore" -> "storage::KVStore"
[label="static" arrowhead=vee color=black];
// cluster_dynamic_partitioning -- cluster_storage
"database::GraphDb" -> "DynamicPartitioner"
[arrowhead=vee color=red];
"DynamicPartitioner" -> "database::GraphDbAccessor"
[arrowhead=vee color=black];
}

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digraph {
// label="Dynamig Graph Partitioning";
fontname="Roboto Bold"; fontcolor=black;
fontsize=26; labelloc=top; labeljust=center;
compound=true; // If true, allow edges between clusters
rankdir=TB; // Alternatives: LR
node [shape=record fontname="Roboto", fontsize=12, fontcolor=white
style=filled, color="#FB6E00" fillcolor="#FB6E00"];
edge [color="#B5AFB7"];
"distributed::DistributedGraphDb" -> "distributed::TokenSharingRpcServer";
"distributed::TokenSharingRpcServer" -> "communication::rpc::Server";
"distributed::TokenSharingRpcServer" -> "distributed::Coordination";
"distributed::TokenSharingRpcServer" -> "distributed::TokenSharingRpcClients";
"distributed::TokenSharingRpcServer" -> "distributed::dgp::Partitioner";
"distributed::dgp::Partitioner" -> "distributed::DistributedGraphDb" [style=dashed];
"distributed::dgp::Partitioner" -> "distributed::dgp::VertexMigrator";
"distributed::dgp::VertexMigrator" -> "database::GraphDbAccessor" [style=dashed];
}

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# Distributed addressing
In distributed Memgraph a single graph element must be owned by exactly
one worker. It is possible that multiple workers have cached copies of
a single graph element (which is inevitable), but there is only one
owner.
The owner of a graph element can change. This is not yet implemented,
but is intended. Graph partitioning is intended to be dynamic.
Graph elements refer to other graph elements that are possibly on some
other worker. Even though each graph element is identified with a unique
ID, that ID does not contain the information about where that element
currently resides (which worker is the owner).
Thus we introduce the concept of a global address. It indicates both
which graph element is referred to (it's global ID), and where it
resides. Semantically it's a pair of two elements, but for efficiency
it's stored in 64 bits.
The global address is efficient for usage in a cluster: it indicates
where something can be found. However, finding a graph element based on
it's ID is still not a free operation (in the current implementation
it's a skiplist lookup). So, whenever possible, it's better to use local
addresses (pointers).
Succinctly, the requirements for addressing are:
- global addressing containing location info
- fast local addressing
- storage of both types in the same location efficiently
- translation between the two
The `storage::Address` class handles the enumerated storage
requirements. It stores either a local or global address in the size of
a local pointer (typically 8 bytes).
Conversion between the two is done in multiple places. The general
approach is to use local addresses (when possible) only for local
in-memory handling. All the communication and persistence uses global
addresses. Also, when receiving address from another worker, attempt to
localize addresses as soon as possible, so that least code has to worry
about potential inefficiency of using a global address for a local graph
element.

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# Distributed durability
Durability in distributed is slightly different then in single-node as
the state itself is shared between multiple workers and none of those
states are independent.
Note that recovering from persistent storage must result in a stable
database state. This means that across the cluster the state
modification of every transaction that was running is either recovered
fully or not at all. Also, if transaction A committed before transaction B,
then if B is recovered so must A.
## Snapshots
It is possibly avoidable but highly desirable that the database can be
recovered from snapshot only, without relying on WAL files. For this to
be possible in distributed, it must be ensured that the same
transactions are recovered on all the workers (including master) in the
cluster. Since the snapshot does not contain information about which
state change happened in which transaction, the only way to achieve this
is to have synchronized snapshots. This means that the process of
creating a snapshot, which is in itself transactional (it happens within
a transaction and thus observes some consistent database state), must
happen in the same transaction. This is achieved by the master starting
a snapshot generating transaction and triggering the process on all
workers in the cluster.
## WAL
Unlike the snapshot, write-ahead logs contain the information on which
transaction made which state change. This makes it possible to include
or exclude transactions during the recovery process. What is necessary
however is a global consensus on which of the transactions should be
recovered and which not, to ensure recovery into a consistent state.
It would be possible to achieve this with some kind of synchronized
recovery process, but it would impose constraints on cluster startup and
would not be trivial.
A simpler alternative is that the consensus is achieved beforehand,
while the database (to be recovered) is still operational. What is
necessary is to keep track of which transactions are guaranteed to
have been flushed to the WAL files on all the workers in the cluster. It
makes sense to keep this record on the master, so a mechanism is
introduced which periodically pings all the workers, telling them to
flush their WALs, and writes some sort of a log indicating that this has
been confirmed. The downside of this is a periodic broadcast must be
done, and that potentially slightly less data can be recovered in the
case of a crash then if using a post-crash consensus. It is however much
simpler to implement.

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## Dynamic Graph Partitioning
Memgraph supports dynamic graph partitioning similar to the Spinner algorithm,
mentioned in this paper: [https://arxiv.org/pdf/1404.3861.pdf].
Dgp is useful because it tries to group `local` date on the same worker, i.e.
it tries to keep closely connected data on one worker. It tries to avoid jumps
across workers when querying/traversing the distributed graph.
### Our implementation
It works independently on each worker but it is always running the migration
on only one worker at the same time. It achieves that by sharing a token
between workers, and the token ownership is transferred to the next worker
when the current worker finishes its migration step.
The reason that we want workers to work in disjoint time slots is it avoid
serialization errors caused by creating/removing edges of vertices during
migrations, which might cause an update of some vertex from two or more
different transactions.
### Migrations
For each vertex and workerid (label in the context of Dgp algorithm) we define
a score function. Score function takes into account labels of surrounding
endpoints of vertex edges (in/out) and the capacity of the worker with said
label. Score function loosely looks like this
```
locality(v, l) =
count endpoints of edges of vertex `v` with label `l` / degree of `v`
capacity(l) =
number of vertices on worker `l` divided by the worker capacity
(usually equal to the average number of vertices per worker)
score(v, l) = locality(v, l) - capacity(l)
```
We also define two flags alongside ```dynamic_graph_partitioner_enabled```,
```dgp_improvement_threshold``` and ```dgp_max_batch_size```.
These two flags are used during the migration phase.
When deciding if we need to migrate some vertex `v` from worker `l1` to worker
`l2` we examine the difference in scores, i.e.
if score(v, l1) - dgp_improvement_threshold / 100 < score(v, l2) then we
migrate the vertex.
Max batch size flag limits the number of vertices we can transfer in one batch
(one migration step).
Setting this value to a too large value will probably cause
a lot of interference with client queries, and having it a small value
will slow down convergence of the algorithm.

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# Memgraph distributed
This chapter describes some of the concepts used in distributed
Memgraph. By "distributed" here we mean the sharding of a single graph
onto multiple processing units (servers).
## Conceptual organization
There is a single master and multiple workers. The master contains all
the global sources of truth (transaction engine,
[label|edge-type|property] to name mappings). Also, in the current
organization it is the only one that contains a Bolt server (for
communication with the end client) and an interpretation engine. Workers
contain the data and means of subquery interpretation (query plans
recieved from the master) and means of communication with the master and
other workers.
In many query plans the load on the master is much larger then the load
on the workers. For that reason it might be beneficial to make the
master contain less data (or none at all), and/or having multiple
interpretation masters.
## Logic organization
Both the distributed and the single node Memgraph use the same codebase.
In cases where the behavior in single-node differs from that in
distributed, some kind of dynamic behavior change is implemented (either
through inheritance or conditional logic).
### GraphDb
The `database::GraphDb` is an "umbrella" object for parts of the
database such as storage, garbage collection, transaction engine etc.
There is a class heirarchy of `GraphDb` implementations, as well as a
base interface object. There are subclasses for single-node, master and
worker deplotyments. Which implementation is used depends on the
configuration processed in the `main` entry point of memgraph.
The `GraphDb` interface exposes getters to base classes of
other similar heirarchies (for example to `tx::Engine`). In that way
much of the code that uses those objects (for example query plan
interpretation) is agnostic to the type of deployment.
### RecordAccessors
The functionality of `RecordAccessors` and it's subclasses is already
documented. It's important to note that the same implementation of
accessors is used in all deployments, with internal changes of behavior
depending on the locality of the graph element (vertex or edge) the
accessor represents. For example, if the graph element is local, an
update operation on an accessor will make the necessary MVCC ops, update
local data, indexes, the write-ahead log etc. However, if the accessor
represents a remote graph element, an update will trigger an RPC message
to the owner about the update and a change in the local cache.

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# Distributed updates
Operations that modify the graph state are somewhat more complex in the
distributed system, as opposed to a single-node Memgraph deployment. The
complexity arises from two factors.
First, the data being modified is not necessarily owned by the worker
performing the modification. This situation is completely valid workers
execute parts of the query plan and parts must be executed by the
master.
Second, there are less guarantees regarding multi-threaded access. In
single-node Memgraph it was guaranteed that only one transaction will be
performing database work in a single transaction. This implied that
per-version storage could be thread-unsafe. In distributed Memgraph it
is possible that multiple threads could be performing work in the same
transaction as a consequence of the query being executed at the same
time on multiple workers and those executions interacting with the
globally partitioned database state.
## Deferred state modification
Making the per-version data storage thread-safe would most likely have a
performance impact very undesirable in a transactional database intended
for high throughput.
An alternative is that state modification over unsafe structures is not
performed immediately when requested, but postponed until it is safe to
do (there is is a guarantee of no concurrent access).
Since local query plan execution is done the same way on local data as
it is in single-node Memgraph, it is not possible to deffer that part of
the modification story. What can be deferred are modifications requested
by other workers. Since local query plan execution still is
single-threaded, this approach is safe.
At the same time those workers requesting the remote update can update
local copies (caches) of the not-owned data since that cache is only
being used by the single, local-execution thread.
### Visibility
Since updates are deferred the question arises: when do the updates
become visible? The above described process offers the following
visibility guarantees:
- updates done on the local state are visible to the owner
- updates done on the local state are NOT visible to anyone else during
the same (transaction + command)
- updates done on remote state are deferred on the owner and not
visible to the owner until applied
- updates done on the remote state are applied immediately to the local
caches and thus visible locally
This implies an inconsistent view of the database state. In a concurrent
execution of a single query this can hardly be avoided and is accepted
as such. It does not change the Cypher query execution semantic in any
of the well-defined scenarios. It possibly changes some of the behaviors
in which the semantic is not well defined even in single-node execution.
### Synchronization, update application
In many queries it is mandatory to observe the latest global graph state
(typically when returning it to the client). That means that before that
happens all the deferred updates need to be applied, and all the caches
to remote data invalidated. Exactly this happens when executing queries
that modify the graph state. At some point a global synchronization
point is reached. First it is waited that all workers finish the
execution of query plan parts performing state modifications. After that
all the workers are told to apply the deferred updates they received to
their graph state. Since there is no concurrent query plan execution,
this is safe. Once that is done all the local caches are cleared and the
requested data can be returned to the client.
### Command advancement
In complex queries where a read part follows a state modification part
the synchronization process after the state modification part is
followed by command advancement, like in single-node execution.
## Creation
Graph element creation is not deferred. This is practical because the
response to a creation is the global ID of the newly created element. At
the same time it is safe because no other worker (including the owner)
will be using the newly added graph element.
## Updating
Updating is deferred, as described. Note that this also means that
record locking conflicts are deferred and serialization errors
(including lock timeouts) are postponed until the deferred update
application phase. In certain scenarios it might be beneficial to force
these errors to happen earlier, when the deferred update request is
processed.
## Deletion
Deletion is also deferred. Deleting an edge implies a modification of
it's endpoint vertices, which must be deferred as those data structures
are not thread-safe. Deleting a vertex is either with detaching, in
which case an arbitrary number of updates are implied in the vertex's
neighborhood, or without detaching which relies on checking the current
state of the graph which is generally impossible in distributed.

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# Snapshots
A "snapshot" is a record of the current database state stored in permanent
storage. Note that the term "snapshot" is used also in the context of
the transaction engine to denote a set of running transactions.
A snapshot is written to the file by Memgraph periodically if so
configured. The snapshot creation process is done within a transaction created
specifically for that purpose. The transaction is needed to ensure that
the stored state is internally consistent.
The database state can be recovered from the snapshot during startup, if
so configured. This recovery works in conjunction with write-ahead log
recovery.
A single snapshot contains all the data needed to recover a database. In
that sense snapshots are independent of each other and old snapshots can
be deleted once the new ones are safely stored, if it is not necessary
to revert the database to some older state.
The exact format of the snapshot file is defined inline in the snapshot
creation code.

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# Write-ahead logging
Typically WAL denotes the process of writing a "log" of database
operations (state changes) to persistent storage before committing the
transaction, thus ensuring that the state can be recovered (in the case
of a crash) for all the transactions which the database committed.
The WAL is a fine-grained durability format. It's purpose is to store
database changes fast. It's primary purpose is not to provide
space-efficient storage, nor to support fast recovery. For that reason
it's often used in combination with a different persistence mechanism
(in Memgraph's case the "snapshot") that has complementary
characteristics.
### Guarantees
Ensuring that the log is written before the transaction is committed can
slow down the database. For that reason this guarantee is most often
configurable in databases.
Memgraph offers two options for the WAL. The default option, where the WAL is
flushed to the disk periodically and transactions do not wait for this to
complete, introduces the risk of database inconsistency because an operating
system or hardware crash might lead to missing transactions in the WAL. Memgraph
will handle this as if those transactions never happened. The second option,
called synchronous commit, will instruct Memgraph to wait for the WAL to be
flushed to the disk when a transactions completes and the transaction will wait
for this to complete. This option can be turned on with the
`--synchronous-commit` command line flag.
### Format
The WAL file contains a series of DB state changes called `StateDelta`s.
Each of them describes what the state change is and in which transaction
it happened. Also some kinds of meta-information needed to ensure proper
state recovery are recorded (transaction beginnings and commits/abort).
The following is guaranteed w.r.t. `StateDelta` ordering in
a single WAL file:
- For two ops in the same transaction, if op A happened before B in the
database, that ordering is preserved in the log.
- Transaction begin/commit/abort messages also appear in exactly the
same order as they were executed in the transactional engine.
### Recovery
The database can recover from the WAL on startup. This works in
conjunction with snapshot recovery. The database attempts to recover from
the latest snapshot and then apply as much as possible from the WAL
files. Only those transactions that were not recovered from the snapshot
are recovered from the WAL, for speed efficiency. It is possible (but
inefficient) to recover the database from WAL only, provided all the WAL
files created from DB start are available. It is not possible to recover
partial database state (i.e. from some suffix of WAL files, without the
preceding snapshot).

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# Other Code Conventions
While we are mainly programming in C++, we do use other programming languages
when appropriate. This chapter describes conventions for such code.
## Python
Code written in Python should adhere to
[PEP 8](https://www.python.org/dev/peps/pep-0008/). You should run `flake8` on
your code to automatically check compliance.
## Common Lisp
Code written in Common Lisp should adhere to
[Google Common Lisp Style](https://google.github.io/styleguide/lispguide.xml).

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html/

16
docs/dev/query/build-html Executable file
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#!/bin/bash
script_dir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
mkdir -p $script_dir/html
for markdown_file in $(find $script_dir -name '*.md'); do
name=$(basename -s .md $markdown_file)
sed -e 's/.md/.html/' $markdown_file | \
pandoc -s -f markdown -t html -o $script_dir/html/$name.html
done
for dot_file in $(find $script_dir -name '*.dot'); do
name=$(basename -s .dot $dot_file)
dot -Tpng $dot_file -o $script_dir/html/$name.png
done

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# Query Parsing, Planning and Execution
This part of the documentation deals with query execution.
Memgraph currently supports only query interpretation. Each new query is
parsed, analysed and translated into a sequence of operations which are then
executed on the main database storage. Query execution is organized into the
following phases:
1. [Lexical Analysis (Tokenization)](parsing.md)
2. [Syntactic Analysis (Parsing)](parsing.md)
3. [Semantic Analysis and Symbol Generation](semantic.md)
4. [Logical Planning](planning.md)
5. [Logical Plan Execution](execution.md)
The main entry point is `Interpreter::operator()`, which takes a query text
string and produces a `Results` object. To instantiate the object,
`Interpreter` needs to perform the above steps from 1 to 4. If any of the
steps fail, a `QueryException` is thrown. The complete `LogicalPlan` is
wrapped into a `CachedPlan` and stored for reuse. This way we can skip the
whole process of analysing a query if it appears to be the same as before.
When we have valid plan, the client code can invoke `Results::PullAll` with a
stream object. The `Results` instance will then execute the plan and fill the
stream with the obtained results.
Since we want to optionally run Memgraph as a distributed database, we have
hooks for creating a different plan of logical operators.
`DistributedInterpreter` inherits from `Interpreter` and overrides
`MakeLogicalPlan` method. This method needs to return a concrete instance of
`LogicalPlan`, and in case of distributed database that will be
`DistributedLogicalPlan`.
![Intepreter Class Diagram](interpreter-class.png)

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# Logical Plan Execution
We implement classical iterator style operators. Logical operators define
operations on database. They encapsulate the following info: what the input is
(another `LogicalOperator`), what to do with the data, and how to do it.
Currently logical operators can have zero or more input operations, and thus a
`LogicalOperator` tree is formed. Most `LogicalOperator` types have only one
input, so we are mostly working with chains instead of full fledged trees.
You can find information on each operator in `src/query/plan/operator.lcp`.
## Cursor
Logical operators do not perform database work themselves. Instead they create
`Cursor` objects that do the actual work, based on the info in the operator.
Cursors expose a `Pull` method that gets called by the cursor's consumer. The
consumer keeps pulling as long as the `Pull` returns `true` (indicating it
successfully performed some work and might be eligible for another `Pull`).
Most cursors will call the `Pull` function of their input provided cursor, so
typically a cursor chain is created that is analogue to the logical operator
chain it's created from.
## Frame
The `Frame` object contains all the data of the current `Pull` chain. It
serves for communicating data between cursors.
For example, in a `MATCH (n) RETURN n` query the `ScanAllCursor` places a
vertex on the `Frame` for each `Pull`. It places it on the place reserved for
the `n` symbol. Then the `ProduceCursor` can take that same value from the
`Frame` because it knows the appropriate symbol. `Frame` positions are indexed
by `Symbol` objects.
## ExpressionEvaluator
Expressions results are not placed on the `Frame` since they do not need to be
communicated between different `Cursors`. Instead, expressions are evaluated
using an instance of `ExpressionEvaluator`. Since generally speaking an
expression can be defined by a tree of subexpressions, the
`ExpressionEvaluator` is implemented as a tree visitor. There is a performance
sub-optimality here because a stack is used to communicate intermediary
expression results between elements of the tree. This is one of the reasons
why it's planned to use `Frame` for intermediary expression results as well.
The other reason is that it might facilitate compilation later on.
## Cypher Execution Semantics
Cypher query execution has *mostly* well-defined semantics. Some are
explicitly defined by openCypher and its TCK, while others are implicitly
defined by Neo4j's implementation of Cypher that we want to be generally
compatible with.
These semantics can in short be described as follows: a Cypher query consists
of multiple clauses some of which modify it. Generally, every clause in the
query, when reading it left to right, operates on a consistent state of the
property graph, untouched by subsequent clauses. This means that a `MATCH`
clause in the beginning operates on a graph-state in which modifications by
the subsequent `SET` are not visible.
The stated semantics feel very natural to the end-user, and Neo seems to
implement them well. For Memgraph the situation is complex because
`LogicalOperator` execution (through a `Cursor`) happens one `Pull` at a time
(generally meaning all the query clauses get executed for every top-level
`Pull`). This is not inherently consistent with Cypher semantics because a
`SET` clause can modify data, and the `MATCH` clause that precedes it might
see the modification in a subsequent `Pull`. Also, the `RETURN` clause might
want to stream results to the user before all `SET` clauses have been
executed, so the user might see some intermediate graph state. There are many
edge-cases that Memgraph does its best to avoid to stay true to Cypher
semantics, while at the same time using a high-performance streaming approach.
The edge-cases are enumerated in this document along with the implementation
details they imply.
## Implementation Peculiarities
### Once
An operator that does nothing but whose `Cursor::Pull` returns `true` on the
first `Pull` and `false` on subsequent ones. This operator is used when
another operator has an optional input, because in Cypher a clause will
typically execute once for every input from the preceding clauses, or just
once if there was no preceding input. For example, consider the `CREATE`
clause. In the query `CREATE (n)` only one node is created, while in the query
`MATCH (n) CREATE (m)` a node is created for each existing node. Thus in our
`CreateNode` logical operator the input is either a `ScanAll` operator, or a
`Once` operator.
### storage::View
In the previous section, [Cypher Execution
Semantics](#cypher-execution-semantics), we mentioned how the preceding
clauses should not see changes made in subsequent ones. For that reason, some
operators take a `storage::View` enum value. This value determines which state of
the graph an operator sees.
Consider the query `MATCH (n)--(m) WHERE n.x = 0 SET m.x = 1`. Naive streaming
could match a vertex `n` on the given criteria, expand to `m`, update it's
property, and in the next iteration consider the vertex previously matched to
`m` and skip it because it's newly set property value does not qualify. This
is not how Cypher works. To handle this issue properly, Memgraph designed the
`VertexAccessor` class that tracks two versions of data: one that was visible
before the current transaction+command, and the optional other that was
created in the current transaction+command. The `MATCH` clause will be planned
as `ScanAll` and `Expand` operations using `storage::View::OLD` value. This
will ensure modifications performed in the same query do not affect it. The
same applies to edges and the `EdgeAccessor` class.
### Existing Record Detection
It's possible that a pattern element has already been declared in the same
pattern, or a preceding pattern. For example `MATCH (n)--(m), (n)--(l)` or a
cycle-detection match `MATCH (n)-->(n) RETURN n`. Implementation-wise,
existing record detection just checks that the expanded record is equal to the
one already on the frame.
### Why Not Use Separate Expansion Ops for Edges and Vertices?
Expanding an edge and a vertex in separate ops is not feasible when matching a
cycle in bi-directional expansions. Consider the query `MATCH (n)--(n) RETURN
n`. Let's try to expand first the edge in one op, and vertex in the next. The
vertex expansion consumes the edge expansion input. It takes the expanded edge
from the frame. It needs to detect a cycle by comparing the vertex existing on
the frame with one of the edge vertices (`from` or `to`). But which one? It
doesn't know, and can't ensure correct cycle detection.
### Data Visibility During and After SET
In Cypher, setting values always works on the latest version of data (from
preceding or current clause). That means that within a `SET` clause all the
changes from previous clauses must be visible, as well as changes done by the
current `SET` clause. Also, if there is a clause after `SET` it must see *all*
the changes performed by the preceding `SET`. Both these things are best
illustrated with the following queries executed on an empty database:
CREATE (n:A {x:0})-[:EdgeType]->(m:B {x:0})
MATCH (n)--(m) SET m.x = n.x + 1 RETURN labels(n), n.x, labels(m), m.x
This returns:
+---------+---+---------+---+
|labels(n)|n.x|labels(m)|m.x|
+:=======:+:=:+:=======:+:=:+
|[A] |2 |[B] |1 |
+---------+---+---------+---+
|[B] |1 |[A] |2 |
+---------+---+---------+---+
The obtained result implies the following operations:
1. In the first iteration set the value of the `B.x` to 1
2. In the second iteration the we observe `B.x` with the value of 1 and set
`A.x` to 2
3. In `RETURN` we see all the changes made in both iterations
To implement the desired behavior Memgraph utilizes two techniques. First is
the already mentioned tracking of two versions of data in vertex accessors.
Using this approach ensures that the second iteration in the example query
sees the data modification performed by the preceding iteration. The second
technique is the `Accumulate` operation that accumulates all the iterations
from the preceding logical op before passing them to the next logical op. In
the example query, `Accumulate` ensures that the results returned to the user
reflect changes performed in all iterations of the query (naive streaming
could stream results at the end of first iteration producing inconsistent
results). Note that `Accumulate` is demanding regarding memory and slows down
query execution. For that reason it should be used only when necessary, for
example it does not have to be used in a query that has `MATCH` and `SET` but
no `RETURN`.
### Neo4j Inconsistency on Multiple SET Clauses
Considering the preceding example it could be expected that when a query has
multiple `SET` clauses all the changes from those preceding one are visible.
This is not the case in Neo4j's implementation. Consider the following queries
executed on an empty database:
CREATE (n:A {x:0})-[:EdgeType]->(m:B {x:0})
MATCH (n)--(m) SET n.x = n.x + 1 SET m.x = m.x * 2
RETURN labels(n), n.x, labels(m), m.x
This returns:
+---------+---+---------+---+
|labels(n)|n.x|labels(m)|m.x|
+:=======:+:=:+:=======:+:=:+
|[A] |2 |[B] |1 |
+---------+---+---------+---+
|[B] |1 |[A] |2 |
+---------+---+---------+---+
If all the iterations of the first `SET` clause were executed before executing
the second, all the resulting values would be 2. This not being the case, we
conclude that Neo4j does not use a barrier-like mechanism between `SET`
clauses. It is Memgraph's current vision that this is inconsistent and we
plan to reduce Neo4j compliance in favour of operation consistency.
### Double Deletion
It's possible to match the same graph element multiple times in a single query
and delete it. Neo supports this, and so do we. The relevant implementation
detail is in the `GraphDbAccessor` class, where the record deletion functions
reside, and not in the logical plan execution. It comes down to checking if a
record has already been deleted in the current transaction+command and not
attempting to do it again (results in a crash).
### Set + Delete Edge-case
It's legal for a query to combine `SET` and `DELETE` clauses. Consider the
following queries executed on an empty database:
CREATE ()-[:T]->()
MATCH (n)--(m) SET n.x = 42 DETACH DELETE m
Due to the `MATCH` being undirected the second pull will attempt to set data
on a deleted vertex. This is not a legal operation in Memgraph storage
implementation. For that reason the logical operator for `SET` must check if
the record it's trying to set something on has been deleted by the current
transaction+command. If so, the modification is not executed.
### Deletion Accumulation
Sometimes it's necessary to accumulate deletions of all the matches before
attempting to execute them. Consider this the following. Start with an empty
database and execute queries:
CREATE ()-[:T]->()-[:T]->()
MATCH (a)-[r1]-(b)-[r2]-(c) DELETE r1, b, c
Note that the `DELETE` clause attempts to delete node `c`, but it does not
detach it by deleting edge `r2`. However, due to undirected edge in the
`MATCH`, both edges get pulled and deleted.
Currently Memgraph does not support this behavior, Neo does. There are a few
ways that we could do this.
* Accumulate on deletion (that sucks because we have to keep track of
everything that gets returned after the deletion).
* Maybe we could stream through the deletion op, but defer actual deletion
until plan-execution end.
* Ignore this because it's very edgy (this is the currently selected option).
### Aggregation Without Input
It is necessary to define what aggregation ops return when they receive no
input. Following is a table that shows what Neo4j's Cypher implementation and
SQL produce.
+-------------+------------------------+---------------------+---------------------+------------------+
| \<OP\> | 1. Cypher, no group-by | 2. Cypher, group-by | 3. SQL, no group-by | 4. SQL, group-by |
+=============+:======================:+:===================:+:===================:+:================:+
| Count(\*) | 0 | \<NO\_ROWS> | 0 | \<NO\_ROWS> |
+-------------+------------------------+---------------------+---------------------+------------------+
| Count(prop) | 0 | \<NO\_ROWS> | 0 | \<NO\_ROWS> |
+-------------+------------------------+---------------------+---------------------+------------------+
| Sum | 0 | \<NO\_ROWS> | NULL | \<NO\_ROWS> |
+-------------+------------------------+---------------------+---------------------+------------------+
| Avg | NULL | \<NO\_ROWS> | NULL | \<NO\_ROWS> |
+-------------+------------------------+---------------------+---------------------+------------------+
| Min | NULL | \<NO\_ROWS> | NULL | \<NO\_ROWS> |
+-------------+------------------------+---------------------+---------------------+------------------+
| Max | NULL | \<NO\_ROWS> | NULL | \<NO\_ROWS> |
+-------------+------------------------+---------------------+---------------------+------------------+
| Collect | [] | \<NO\_ROWS> | N/A | N/A |
+-------------+------------------------+---------------------+---------------------+------------------+
Where:
1. `MATCH (n) RETURN <OP>(n.prop)`
2. `MATCH (n) RETURN <OP>(n.prop), (n.prop2)`
3. `SELECT <OP>(prop) FROM Table`
4. `SELECT <OP>(prop), prop2 FROM Table GROUP BY prop2`
Neo's Cypher implementation diverges from SQL only when performing `SUM`.
Memgraph implements SQL-like behavior. It is considered that `SUM` of
arbitrary elements should not be implicitly 0, especially in a property graph
without a strict schema (the property in question can contain values of
arbitrary types, or no values at all).
### OrderBy
The `OrderBy` logical operator sorts the results in the desired order. It
occurs in Cypher as part of a `WITH` or `RETURN` clause. Both the concept and
the implementation are straightforward. It's necessary for the logical op to
`Pull` everything from its input so it can be sorted. It's not necessary to
keep the whole `Frame` state of each input, it is sufficient to keep a list of
`TypedValues` on which the results will be sorted, and another list of values
that need to be remembered and recreated on the `Frame` when yielding.
The sorting itself is made to reflect that of Neo's implementation which comes
down to these points.
* `Null` comes last (as if it's greater than anything).
* Primitive types compare naturally, with no implicit casting except from
`int` to `double`.
* Complex types are not comparable.
* Every unsupported comparison results in an exception that gets propagated
to the end user.
### Limit in Write Queries
`Limit` can be used as part of a write query, in which case it will *not*
reduce the amount of performed updates. For example, consider a database that
has 10 vertices. The query `MATCH (n) SET n.x = 1 RETURN n LIMIT 3` will
result in all vertices having their property value changed, while returning
only the first to the client. This makes sense from the implementation
standpoint, because `Accumulate` is planned after `SetProperty` but before
`Produce` and `Limit` operations. Note that this behavior can be
non-deterministic in some queries, since it relies on the order of iteration
over nodes which is undefined when not explicitly specified.
### Merge
`MERGE` in Cypher attempts to match a pattern. If it already exists, it does
nothing and subsequent clauses like `RETURN` can use the matched pattern
elements. If the pattern can't match to any data, it creates it. For detailed
information see Neo4j's [merge
documentation.](https://neo4j.com/docs/developer-manual/current/cypher/clauses/merge/)
An important thing about `MERGE` is visibility of modified data. `MERGE` takes
an input (typically a `MATCH`) and has two additional *phases*: the merging
part, and the subsequent set parts (`ON MATCH SET` and `ON CREATE SET`).
Analysis of Neo4j's behavior indicates that each of these three phases (input,
merge, set) does not see changes to the graph state done by subsequent phase.
The input phase does not see data created by the merge phase, nor the set
phase. This is consistent with what seems like the general Cypher philosophy
that query clause effects aren't visible in the preceding clauses.
We define the `Merge` logical operator as a *routing* operator that uses three
logical operator branches.
1. The input from a preceding clause.
For example in `MATCH (n), (m) MERGE (n)-[:T]-(m)`. This input is
optional because `MERGE` is allowed to be the first clause in a query.
2. The `merge_match` branch.
This logical operator branch is `Pull`-ed from until exhausted for each
successful `Pull` from the input branch.
3. The `merge_create` branch.
This branch is `Pull`ed when the `merge_match` branch does not match
anything (no successful `Pull`s) for an input `Pull`. It is `Pull`ed only
once in such a situation, since only one creation needs to occur for a
failed match.
The `ON MATCH SET` and `ON CREATE SET` parts of the `MERGE` clause are
included in the `merge_match` and `merge_create` branches respectively. They
are placed on the end of their branches so that they execute only when those
branches succeed.
Memgraph strives to be consistent with Neo in its `MERGE` implementation,
while at the same time keeping performance as good as possible. Consistency
with Neo w.r.t. graph state visibility is not trivial. Documentation for
`Expand` and `Set` describe how Memgraph keeps track of both the updated
version of an edge/vertex and the old one, as it was before the current
transaction+command. This technique is also used in `Merge`. The input
phase/branch of `Merge` always looks at the old data. The merge phase needs to
see the new data so it doesn't create more data then necessary.
For example, consider the query.
MATCH (p:Person) MERGE (c:City {name: p.lives_in})
This query needs to create a city node only once for each unique `p.lives_in`.
Finally the set phase of a `MERGE` clause should not affect the merge phase.
To achieve this the `merge_match` branch of the `Merge` operator should see
the latest created nodes, but filter them on their old state (if those nodes
were not created by the `create_branch`). Implementation-wise that means that
`ScanAll` and `Expand` operators in the `merge_branch` need to look at the new
graph state, while `Filter` operators the old, if available.

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digraph interpreter {
node [fontname="dejavusansmono"]
edge [fontname="dejavusansmono"]
node [shape=record]
edge [dir=back,arrowtail=empty,arrowsize=1.5]
Interpreter [label="{\N|+ operator(query : string, ...) : Results\l|
# MakeLogicalPlan(...) : LogicalPlan\l|
- plan_cache_ : Map(QueryHash, CachedPlan)\l}"]
Interpreter -> DistributedInterpreter
Results [label="{\N|+ PullAll(stream) : void\l|- plan_ : CachedPlan\l}"]
Interpreter -> Results
[dir=forward,style=dashed,arrowhead=open,label="<<create>>"]
CachedPlan -> Results
[dir=forward,arrowhead=odiamond,taillabel="1",headlabel="*"]
Interpreter -> CachedPlan [arrowtail=diamond,taillabel="1",headlabel="*"]
CachedPlan -> LogicalPlan [arrowtail=diamond]
LogicalPlan [label="{\N|+ GetRoot() : LogicalOperator
\l+ GetCost() : double\l}"]
LogicalPlan -> SingleNodeLogicalPlan [style=dashed]
LogicalPlan -> DistributedLogicalPlan [style=dashed]
DistributedInterpreter -> DistributedLogicalPlan
[dir=forward,style=dashed,arrowhead=open,label="<<create>>"]
}

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# Lexical and Syntactic Analysis
## Antlr
We use Antlr for lexical and syntax analysis of Cypher queries. Antrl uses
grammar file `Cypher.g4` downloaded from http://www.opencypher.org to generate
the parser and the visitor for the Cypher parse tree. Even though the provided
grammar is not very pleasant to work with we decided not to do any drastic
changes to it so that our transition to newly published versions of
`Cypher.g4` would be easier. Nevertheless, we had to fix some bugs and add
features, so our version is not completely the same.
In addition to using `Cypher.g4`, we have `MemgraphCypher.g4`. This grammar
file defines Memgraph specific extensions to the original grammar. Most
notable example is the inclusion of syntax for handling authorization. At the
moment, some extensions are also found in `Cypher.g4`. For example, the syntax
for using a lambda function in relationship patterns. These extensions should
be moved out of `Cypher.g4`, so that it remains as close to the original
grammar as possible. Additionally, having `MemgraphCypher.g4` may not be
enough if we wish to split the functionality for community and enterprise
editions of Memgraph.
## Abstract Syntax Tree (AST)
Since Antlr generated visitor and the official openCypher grammar are not very
practical to use, we translate the Antlr's AST to our own AST. Currently there
are ~40 types of nodes in our AST. Their definitions can be found in
`src/query/frontend/ast/ast.lcp`.
Major groups of types can be found under the following base types.
* `Expression` --- types corresponding to Cypher expressions.
* `Clause` --- types corresponding to Cypher clauses.
* `PatternAtom` --- node or edge related information.
* `Query` --- different kinds of queries, allows extending the language with
Memgraph specific query syntax.
Memory management of created AST nodes is done with `AstStorage`. Each type
must be created by invoking `AstStorage::Create` method. This way all of the
pointers to nodes and their children are raw pointers. The only owner of
allocated memory is the `AstStorage`. When the storage goes out of scope, the
pointers become invalid. It may be more natural to handle tree ownership via
`unique_ptr`, i.e. each node owns its children. But there are some benefits to
having a custom storage and allocation scheme.
The primary reason we opted for not using `unique_ptr` is the requirement of
Antlr's base visitor class that the resulting values must by copyable. The
result is wrapped in `antlr::Any` so that the derived visitor classes may
return any type they wish when visiting Antlr's AST. Unfortunately,
`antlr::Any` does not work with non-copyable types.
Another benefit of having `AstStorage` is that we can easily add a different
allocation scheme for AST nodes. The interface of node creation would not
change.
### AST Translation
The translation process is done via `CypherMainVisitor` class, which is
derived from Antlr generated visitor. Besides instancing our AST types, a
minimal number of syntactic checks are done on a query. These checks handle
the cases which were valid in original openCypher grammar, but may be invalid
when combined with other syntax elements.

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# Logical Planning
After the semantic analysis and symbol generation, the AST is converted to a
tree of logical operators. This conversion is called *planning* and the tree
of logical operators is called a *plan*. The whole planning process is done in
the following steps.
1. [AST Preprocessing](#ast-preprocessing)
The first step is to preprocess the AST by collecting
information on filters, divide the query into parts, normalize patterns
in `MATCH` clauses, etc.
2. [Logical Operator Planning](#logical-operator-planning)
After the preprocess step, the planning can be done via 2 planners:
`VariableStartPlanner` and `RuleBasedPlanner`. The first planner will
generate multiple plans where each plan has different starting points for
searching the patterns in `MATCH` clauses. The second planner produces a
single plan by mapping the query parts as they are to logical operators.
3. [Logical Plan Postprocessing](#logical-plan-postprocessing)
In this stage, we perform various transformations on the generated logical
plan. Here we want to optimize the operations in order to improve
performance during the execution. Naturally, transformations need to
preserve the semantic behaviour of the original plan.
4. [Cost Estimation](#cost-estimation)
After the generation, the execution cost of each plan is estimated. This
estimation is used to select the best plan which will be executed.
5. [Distributed Planning](#distributed-planning)
In case we are running distributed Memgraph, the final plan is adapted
for distributed execution. NOTE: This appears to be an error in the
workflow. Distributed planning should be moved before step 3. or
integrated with it. With the workflow ordered as is now, cost estimation
doesn't consider the distributed plan.
The implementation can be found in the `query/plan` directory, with the public
entry point being `query/plan/planner.hpp`.
## AST Preprocessing
Each openCypher query consists of at least 1 **single query**. Multiple single
queries are chained together using a **query combinator**. Currently, there is
only one combinator, `UNION`. The preprocessing step starts in the
`CollectQueryParts` function. This function will take a look at each single
query and divide it into parts. Each part is separated with `RETURN` and
`WITH` clauses. For example:
MATCH (n) CREATE (m) WITH m MATCH (l)-[]-(m) RETURN l
| | |
|------- part 1 -----------+-------- part 2 --------|
| |
|-------------------- single query -----------------|
Each part is created by collecting all `MATCH` clauses and *normalizing* their
patterns. Pattern normalization is the process of converting an arbitrarily
long pattern chain of nodes and edges into a list of triplets `(start node,
edge, end node)`. The triplets should preserve the semantics of the match. For
example:
MATCH (a)-[p]-(b)-[q]-(c)-[r]-(d)
is equivalent to:
MATCH (a)-[p]-(b), (b)-[q]-(c), (c)-[r]-(d)
With this representation, it becomes easier to reorder the triplets and choose
different strategies for pattern matching.
In addition to normalizing patterns, all of the filter expressions in patterns
and inside of the `WHERE` clause (of the accompanying `MATCH`) are extracted
and stored separately. During the extraction, symbols used in the filter
expression are collected. This allows for planning filters in a valid order,
as the matching for triplets is being done. Another important benefit of
having extra information on filters, is to recognize when a database index
could be used.
After each `MATCH` is processed, they are all grouped, so that even the whole
`MATCH` clauses may be reordered. The important thing is to remember which
symbols were used to name edges in each `MATCH`. With those symbols we can
plan for *cyphermorphism*, i.e. ensure different edges in the search pattern
of a single `MATCH` map to different edges in the graph. This preserves the
semantic of the query, even though we may have reordered the matching. The
same steps are done for `OPTIONAL MATCH`.
Another clause which needs processing is `MERGE`. Here we normalize the
pattern, since the `MERGE` is a bit like `MATCH` and `CREATE` in one.
All the other clauses are left as is.
In the end, each query part consists of:
* processed and grouped `MATCH` clauses;
* processed and grouped `OPTIONAL MATCH` clauses;
* processed `MERGE` matching pattern and
* unchanged remaining clauses.
The last stored clause is guaranteed to be either `WITH` or `RETURN`.
## Logical Operator Planning
### Variable Start Planner
The `VariableStartPlanner` generates multiple plans for a single query. Each
plan is generated by selecting a different starting point for pattern
matching.
The algorithm works as follows.
1. For each query part:
1. For each node in triplets of collected `MATCH` clauses:
i. Add the node to a set of `expanded` nodes
ii. Select a triplet `(start node, edge, end node)` whose `start node` is
in the `expanded` set
iii. If no triplet was selected, choose a new starting node that isn't in
`expanded` and continue expanding
iv. Repeat steps ii. -- iii. until all triplets have been selected
and store that as a variation of the `MATCH` clauses
2. Do step 1.1. for `OPTIONAL MATCH` and `MERGE` clauses
3. Take all combinations of the generated `MATCH`, `OPTIONAL MATCH` and
`MERGE` and store them as variations of the query part.
2. For each combination of query part variations:
1. Generate a plan using the rule based planner
### Rule Based Planner
The `RuleBasedPlanner` generates a single plan for a single query. A plan is
generated by following hardcoded rules for producing logical operators. The
following sections are an overview on how each openCypher clause is converted
to a `LogicalOperator`.
#### MATCH
`MATCH` clause is used to specify which patterns need to be searched for in
the database. These patterns are normalized in the preprocess step to be
represented as triplets `(start node, edge, end node)`. When there is no edge,
then the triplet is reduced only to the `start node`. Generating the operators
is done by looping over these triplets.
##### Searching for Nodes
The simplest search is finding standalone nodes. For example, `MATCH (n)`
will find all the nodes in the graph. This is accomplished by generating a
`ScanAll` operator and forwarding the node symbol which should store the
results. In this case, all the nodes will be referenced by `n`.
Multiple nodes can be specified in a single match, e.g. `MATCH (n), (m)`.
Planning is done by repeating the same steps for each sub pattern (separated
by a comma). In this case, we would get 2 `ScanAll` operators chained one
after the other. An optimization can be obtained if the node in the pattern is
already searched for. In `MATCH (n), (n)` we can drop the second `ScanAll`
operator since we have already generated it for the first node.
##### Searching for Relationships
A more advanced search includes finding nodes with relationships. For example,
`MATCH (n)-[r]-(m)` should find every pair of connected nodes in the database.
This means, that if a single node has multiple connections, it will be
repeated for each combination of pairs. The generation of operators starts
from the first node in the pattern. If we are referencing a new starting node,
we need to generate a `ScanAll` which finds all the nodes and stores them
into `n`. Then, we generate an `Expand` operator which reads the `n` and
traverses all the edges of that node. The edge is stored into `r`, while the
destination node is stored in `m`.
Matching multiple relationships proceeds similarly, by repeating the same
steps. The only difference is that we need to ensure different edges in the
search pattern, map to different edges in the graph. This means that after each
`Expand` operator, we need to generate an `EdgeUniquenessFilter`. We provide
this operator with a list of symbols for the previously matched edges and the
symbol for the current edge.
For example.
MATCH (n)-[r1]-(m)-[r2]-(l)
The above is preprocessed into
MATCH (n)-[r1]-(m), (m)-[r2]-(l)
Then we look at each triplet in order and perform the described steps. This
way, we would generate:
ScanAll (n) > Expand (n, r1, m) > Expand (m, r2, l) >
EdgeUniquenessFilter ([r1], r2)
Note that we don't need to make `EdgeUniquenessFilter` after the first
`Expand`, since there are no edges to compare to. This filtering needs to work
across multiple pattern, but inside a *single* `MATCH` clause.
Let's take a look at the following.
MATCH (n)-[r1]-(m), (m)-[r2]-(l)
We would also generate the exact same operators.
ScanAll (n) > Expand (n, r1, m) > Expand (m, r2, l) >
EdgeUniquenessFilter ([r1], r2)
On the other hand,
MATCH (n)-[r1]-(m) MATCH (m)-[r2]-(l)-[r3]-(i)
would reset the uniqueness filtering at the start of the second match. This
would mean that we output the following:
ScanAll (n) > Expand (n, r1, m) > Expand (m, r2, l) > Expand (l, r3, i) >
EdgeUniquenessFilter ([r2], r3)
There is a difference in how we handle edge uniqueness compared to Neo4j.
Neo4j does not allow searching for a single edge multiple times, but we've
decided to support that.
For example, the user can say the following.
MATCH (n)-[r]-(m)-[r]-l
We would ensure that both `r` variables match to the same edge. In our
terminology, we call this the *edge cycle*. For the above example, we would
generate this plan.
ScanAll (n) > Expand (n, r, m) > Expand (m, r, l)
We do not put an `EdgeUniquenessFilter` operator between 2 `Expand`
operators and we tell the 2nd `Expand` that it is an edge cycle. This, 2nd
`Expand` will ensure we have matched both the same edges.
##### Filtering
To narrow the search down, the patterns in `MATCH` can have filtered labels
and properties. A more general filtering is done using the accompanying
`WHERE` clause. During the preprocess step, all filters are collected and
extracted into expressions. Additional information on which symbols are used
is also stored. This way, each time we generate a `ScanAll` or `Expand`, we
look at all the filters to see if any of them can be used. I.e. if the symbols
they use have been bound by a newly produced operator. If a filter expression
can be used, we immediately add a `Filter` operator with that expression.
For example.
MATCH (n)-[r]-(m :label) WHERE n.prop = 42
We would produce:
ScanAll (n) > Filter (n.prop) > Expand (n, r, m) > Filter (m :label)
This means that the same plan is generated for the query:
MATCH (n {prop: 42})-[r]-(m :label)
#### OPTIONAL
If a `MATCH` clause is preceded by `OPTIONAL`, then we need to generate a plan
such that we produce results even if we fail to match anything. This is
accomplished by generating an `Optional` operator, which takes 2 operator
trees:
* input operation and
* optional operation.
The input is the operation we generated for the part of the query before
`OPTIONAL MATCH`. For the optional operation, we simply generate the `OPTIONAL
MATCH` part just like we would for regular `MATCH`. In addition to operations,
we need to send the symbols which are set during optional matching to the
`Optional` operator. The operator will reset values of those symbols to
`null`, when the optional part fails to match.
#### RETURN & WITH
`RETURN` and `WITH` clauses are very similar to each other. The only
difference is that `WITH` separates parts of the query and can be paired with
`WHERE` clause.
The common part is generating operators for the body of the clause. Separation
of query parts is mostly done in semantic analysis, which checks that only the
symbols exposed through `WITH` are visible in the query parts after the
clause. The minor part is done in planning.
##### Named Results
Both clauses contain multiple named expressions (`expr AS name`) which are
used to generate `Produce` operator.
##### Aggregations
If an expression contains an aggregation operator (`sum`, `avg`, ...) we need
to plan the `Aggregate` operator as input to `Produce`. This case is more
complex, because aggregation in openCypher can perform implicit grouping of
results used for aggregation.
For example, `WITH/RETURN sum(n.x) AS s, n.y AS group` will implicitly group
by `n.y` expression.
Another, obscure grouping can be achieved with `RETURN sum(n.a) + n.b AS s`.
Here, the `n.b` will be used for grouping, even though both the `sum` and
`n.b` are in the same named expression.
Therefore, we need to collect all expressions which do not contain
aggregations and use them for grouping. You may have noticed that in the last
example `sum` is actually a sub-expression of `+`. `Aggregate` operator does
not see that (nor it should), so the responsibility of evaluating that falls
on `Produce`. One way is for `Aggregate` to store results of grouping
expressions on the frame in addition to aggregation results. Unfortunately,
this would require rewiring named expressions in `Produce` to reference
already evaluated expressions. In the current implementation, we opted for
`Aggregate` to store only aggregation results on the frame, while `Produce`
will re-evaluate all the other (grouping) expressions. To handle that, symbols
which are used in expressions are passed to `Aggregate`, so that they can be
remembered. `Produce` will read those symbols from the frame and use it to
re-evaluate the needed expressions.
##### Accumulation
After we have `Produce` and potentially `Aggregate`, we need to handle a
special case when the part of the query before `RETURN` or `WITH` performs
updates. For that, we want to run that part of the query fully, so that we get
the latest results. This is accomplished by adding `Accumulate` operator as
input to `Aggregate` or `Produce` (if there is no aggregation). Accumulation
will store all the values for all the used symbols inside `RETURN` and `WITH`,
so that they can be used in the operator which follows. This way, only parts
of the frame are copied, instead of the whole frame. Here is a minor
difference between planning `WITH`, compared to `RETURN`. Since `WITH` can
separate writing from reading, we need to advance the transaction command.
This enables the later, read parts of the query to obtain the newest changes.
This is supported by passing `advance_command` flag to `Accumulate` operator.
In the simplest case, common to both clauses, we have `Accumulate > Aggregate
> Produce` operators, where `Accumulate` and `Aggregate` may be left out.
##### Ordering
Planning `ORDER BY` is simple enough. Since it may see new symbols (filled in
`Produce`), we add the `OrderBy` operator at the end. The operator will change
the order of produced results, so we pass it the ordering expressions and the
output symbols of named expressions.
##### Filtering
A final difference in `WITH`, is when it contains a `WHERE` clause. For that,
we simply generate the `Filter` operator, appended after `Produce` or
`OrderBy` (depending which operator is last).
##### Skipping and Limiting
If we have `SKIP` or `LIMIT`, we generate `Skip` or `Limit` operators,
respectively. These operators are put at the end of the clause.
This placement may have some unexpected behaviour when combined with
operations that update the graph. For example.
MATCH (n) SET n.x = n.x + 1 RETURN n LIMIT 1
The above query may be interpreted as if the `SET` will be done only once.
Since this is a write query, we need to accumulate results, so the part before
`RETURN` will execute completely. The accumulated results will be yielded up
to the given limit, and the user would get only the first `n` that was
updated. This may confuse the user because in reality, every node in the
database had been updated.
Note that `Skip` always comes before `Limit`. In the current implementation,
they are generated directly one after the other.
#### CREATE
`CREATE` clause is used to create nodes and edges (relationships).
For multiple `CREATE` clauses or multiple creation patterns in a single
clause, we perform the same, following steps.
##### Creating a Single Node
A node is created by simply specifying a node pattern.
For example `CREATE (n :label {property: "value"}), ()` would create 2 nodes.
The 1st one would be created with a label and a property. This node could be
referenced later in the query, by using the variable `n`. The 2nd node cannot
be referenced and it would be created without any labels nor properties. For
node creation, we generate a `CreateNode` operator and pass it all the details
of node creation: variable symbol, labels and properties. In the mentioned
example, we would have `CreateNode > CreateNode`.
##### Creating a Relationship
To create a relationship, the `CREATE` clause must contain a pattern with a
directed edge. Compared to creating a single node, this case is a bit more
complicated, because either side of the edge may not exist. By exist, we mean
that the endpoint is a variable which already references a node.
For example, `MATCH (n) CREATE (n)-[r]->(m)` would create an edge `r` and a
node `m` for each matched node `n`. If we focus on the `CREATE` part, we
generate `CreateExpand (n, r, m)` where `n` already exists (refers to matched
node) and `m` would be newly created along with edge `r`. If we had only
`CREATE (n)-[r]->(m)`, then we would need to create both nodes of the edge
`r`. This is done by generating `CreateNode (n) > CreateExpand(n, r, m)`. The
final case is when both endpoints refer to an existing node. For example, when
adding a node with a cyclical connection `CREATE (n)-[r]->(n)`. In this case,
we would generate `CreateNode (n) > CreateExpand (n, r, n)`. We would tell
`CreateExpand` to only create the edge `r` between the already created `n`.
#### MERGE
Although the merge operation is complex, planning turns out to be relatively
simple. The pattern inside the `MERGE` clause is used for both matching and
creating. Therefore, we create 2 operator trees, one for each action.
For example.
MERGE (n)-[r:r]-(m)
We would generate a single `Merge` operator which has the following.
* No input operation (since it is not preceded by any other clause).
* On match operation
`ScanAll (n) > Expand (n, r, m) > Filter (r)`
* On create operation
`CreateNode (n) > CreateExpand (n, r, m)`
In cases when `MERGE` contains `ON MATCH` and `ON CREATE` parts, we simply
append their operations to the respective operator trees.
Observe the following example.
MERGE (n)-[r:r]-(m) ON MATCH SET n.x = 42 ON CREATE SET m :label
The `Merge` would be generated with the following.
* No input operation (again, since there is no clause preceding it).
* On match operation
`ScanAll (n) > Expand (n, r, m) > Filter (r) > SetProperty (n.x, 42)`
* On create operation
`CreateNode (n) > CreateExpand (n, r, m) > SetLabels (n, :label)`
When we have preceding clauses, we simply put their operator as input to
`Merge`.
MATCH (n) MERGE (n)-[r:r]-(m)
The above would be generated as
ScanAll (n) > Merge (on_match_operation, on_create_operation)
Here we need to be careful to recognize which symbols are already declared.
But, since the `on_match_operation` uses the same algorithm for generating a
`Match`, that problem is handled there. The same should hold for
`on_create_operation`, which uses the process of generating a `Create`. So,
finally for this example, the `Merge` would have:
* Input operation
`ScanAll (n)`
* On match operation
`Expand (n, r, m) > Filter (r)`
Note that `ScanAll` is not needed since we get the nodes from input.
* On create operation
`CreateExpand (n, r, m)`
Note that `CreateNode` is dropped, since we want to expand the existing one.
## Logical Plan Postprocessing
NOTE: TODO
## Cost Estimation
NOTE: TODO
## Distributed Planning
NOTE: TODO

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# Semantic Analysis and Symbol Generation
In this phase, various semantic and variable type checks are performed.
Additionally, we generate symbols which map AST nodes to stored values
computed from evaluated expressions.
## Symbol Generation
Implementation can be found in `query/frontend/semantic/symbol_generator.cpp`.
Symbols are generated for each AST node that represents data that needs to
have storage. Currently, these are:
* `NamedExpression`
* `CypherUnion`
* `Identifier`
* `Aggregation`
You may notice that the above AST nodes may not correspond to something named
by a user. For example, `Aggregation` can be a part of larger expression and
thus remain unnamed. The reason we still generate symbols is to have a uniform
behaviour when executing a query as well as allow for caching the results of
expression evaluation.
AST nodes do not actually store a `Symbol` instance, instead they have a
`int32_t` index identifying the symbol in the `SymbolTable` class. This is
done to minimize the size of AST types as well as allow easier sharing of same
symbols with multiple instances of AST nodes.
The storage for evaluated data is represented by the `Frame` class. Each
symbol determines a unique position in the frame. During interpretation,
evaluation of expressions which have a symbol will either read or store values
in the frame. For example, instance of an `Identifier` will use the symbol to
find and read the value from `Frame`. On the other hand, `NamedExpression`
will take the result of evaluating its own expression and store it in the
`Frame`.
When a symbol is created, context of creation is used to assign a type to that
symbol. This type is used for simple type checking operations. For example,
`MATCH (n)` will create a symbol for variable `n`. Since the `MATCH (n)`
represents finding a vertex in the graph, we can set `Symbol::Type::Vertex`
for that symbol. Later, for example in `MATCH ()-[n]-()` we see that variable
`n` is used as an edge. Since we already have a symbol for that variable, we
detect this type mismatch and raise a `SemanticException`.
Basic rule of symbol generation, is that variables inside `MATCH`, `CREATE`,
`MERGE`, `WITH ... AS` and `RETURN ... AS` clauses establish new symbols.
### Symbols in Patterns
Inside `MATCH`, symbols are created only if they didn't exist before. For
example, patterns in `MATCH (n {a: 5})--(m {b: 5}) RETURN n, m` will create 2
symbols: one for `n` and one for `m`. `RETURN` clause will, in turn, reference
those symbols. Symbols established in a part of pattern are immediately bound
and visible in later parts. For example, `MATCH (n)--(n)` will create a symbol
for variable `n` for 1st `(n)`. That symbol is referenced in 2nd `(n)`. Note
that the symbol is not bound inside 1st `(n)` itself. What this means is that,
for example, `MATCH (n {a: n.b})` should raise an error, because `n` is not
yet bound when encountering `n.b`. On the other hand,
`MATCH (n)--(n {a: n.b})` is fine.
The `CREATE` is similar to `MATCH`, but it *always* establishes symbols for
variables which create graph elements. What this means is that, for example
`MATCH (n) CREATE (n)` is not allowed. `CREATE` wants to create a new node,
for which we already have a symbol. In such a case, we need to throw an error
that the variable `n` is being redeclared. On the other hand `MATCH (n) CREATE
(n)-[r :r]->(n)` is fine, because `CREATE` will only create the edge `r`,
connecting the already existing node `n`. Remaining behaviour is the same as
in `MATCH`. This means that we can simplify `CREATE` to be like `MATCH` with 2
special cases.
1. Are we creating a node, i.e. `CREATE (n)`? If yes, then the symbol for
`n` must not have been created before. Otherwise, we reference the
existing symbol.
2. Are we creating an edge, i.e. we encounter a variable for an edge inside
`CREATE`? If yes, then that variable must not reference a symbol.
The `MERGE` clause is treated the same as `CREATE` with regards to symbol
generation. The only difference is that we allow bidirectional edges in the
pattern. When creating such a pattern, the direction of the created edge is
arbitrarily determined.
### Symbols in WITH and RETURN
In addition to patterns, new symbols are established in the `WITH` clause.
This clause makes the new symbols visible *only* to the rest of the query.
For example, `MATCH (old) WITH old AS new RETURN new, old` should raise an
error that `old` is unbound inside `RETURN`.
There is a special case with symbol visibility in `WHERE` and `ORDER BY`. They
need to see both the old and the new symbols. Therefore `MATCH (old) RETURN
old AS new ORDER BY old.prop` needs to work. On the other hand, if we perform
aggregations inside `WITH` or `RETURN`, then the old symbols should not be
visible neither in `WHERE` nor in `ORDER BY`. Since the aggregation has to go
through all the results in order to generate the final value, it makes no
sense to store old symbols and their values. A query like `MATCH (old) WITH
SUM(old.prop) AS sum WHERE old.prop = 42 RETURN sum` needs to raise an error
that `old` is unbound inside `WHERE`.
For cases when `SKIP` and `LIMIT` appear, we disallow any identifiers from
appearing in their expressions. Basically, `SKIP` and `LIMIT` can only be
constant expressions[^1]. For example, `MATCH (old) RETURN old AS new SKIP
new.prop` needs to raise that variables are not allowed in `SKIP`. It makes no
sense to allow variables, since their values may vary on each iteration. On
the other hand, we could support variables to constant expressions, but for
simplicity we do not. For example, `MATCH (old) RETURN old, 2 AS limit_var
LIMIT limit_var` would still throw an error.
Finally, we generate symbols for names created in `RETURN` clause. These
symbols are used for the final results of a query.
NOTE: New symbols in `WITH` and `RETURN` should be unique. This means that
`WITH a AS same, b AS same` is not allowed, neither is a construct like
`RETURN 2, 2`
### Symbols in Functions which Establish New Scope
Symbols can also be created in some functions. These functions usually take an
expression, bind a single variable and run the expression inside the newly
established scope.
The `all` function takes a list, creates a variable for list element and runs
the predicate expression. For example:
MATCH (n) RETURN n, all(n IN n.prop_list WHERE n < 42)
We create a new symbol for use inside `all`, this means that the `WHERE n <
42` uses the `n` which takes values from a `n.prop_list` elements. The
original `n` bound by `MATCH` is not visible inside the `all` function, but it
is visible outside. Therefore, the `RETURN n` and `n.prop_list` reference the
`n` from `MATCH`.
[^1]: Constant expressions are expressions for which the result can be
computed at compile time.

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# Quick Start
A short chapter on downloading the Memgraph source, compiling and running.
## Obtaining the Source Code
Memgraph uses `git` for source version control. You will need to install `git`
on your machine before you can download the source code.
On Debian systems, you can do it inside a terminal with the following
command:
sudo apt-get install git
On ArchLinux or Gentoo, you probably already know what to do.
After installing `git`, you are now ready to fetch your own copy of Memgraph
source code. Run the following command:
git clone https://phabricator.memgraph.io/diffusion/MG/memgraph.git
The above will create a `memgraph` directory and put all source code there.
## Compiling Memgraph
With the source code, you are now ready to compile Memgraph. Well... Not
quite. You'll need to download Memgraph's dependencies first.
In your terminal, position yourself in the obtained memgraph directory.
cd memgraph
### Installing Dependencies
On Debian systems, dependencies that are required by the codebase should be
setup by running the `init` script:
./init -s
Currently, other systems aren't supported in the `init` script. But you can
issue the needed steps manually. First run the `init` script.
./init
The script will output the required packages, which you should be able to
install via your favorite package manager. For example, `pacman` on ArchLinux.
After installing the packages, issue the following commands:
mkdir -p build
./libs/setup.sh
### Compiling
Memgraph is compiled using our own custom toolchain that can be obtained from
[Toolchain repository](https://deps.memgraph.io/toolchain). You should read
the `README.txt` file in the repository and install the apropriate toolchain
for your distribution. After you have installed the toolchain you should read
the instructions for the toolchain in the toolchain install directory
(`/opt/toolchain-vXYZ/README.md`) and install dependencies that are necessary
to run the toolchain.
When you want to compile Memgraph you should activate the toolchain using the
prepared toolchain activation script that is also described in the toolchain
`README`.
NOTE: You *must* activate the toolchain every time you want to compile
Memgraph!
You should now activate the toolchain in your console.
source /opt/toolchain-vXYZ/activate
With all of the dependencies installed and the build environment set-up, you
need to configure the build system. To do that, execute the following:
cd build
cmake ..
If everything went OK, you can now, finally, compile Memgraph.
make -j$(nproc)
### Running
After the compilation verify that Memgraph works:
./memgraph --version
To make extra sure, run the unit tests:
ctest -R unit -j$(nproc)
## Problems
If you have any trouble running the above commands, contact your nearest
developer who successfully built Memgraph. Ask for help and insist on getting
this document updated with correct steps!
## Next Steps
Familiarise yourself with our code conventions and guidelines:
* [C++ Code](cpp-code-conventions.md)
* [Other Code](other-code-conventions.md)
* [Code Review Guidelines](code-review.md)
Take a look at the list of [required reading](required-reading.md) for
brushing up on technical skills.

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# Required Reading
This chapter lists a few books that should be read by everyone working on
Memgraph. Since Memgraph is developed primarily with C++, Python and Common
Lisp, books are oriented around those languages. Of course, there are plenty
of general books which will help you improve your technical skills (such as
"The Pragmatic Programmer", "The Mythical Man-Month", etc.), but they are not
listed here. This way the list should be kept short and the *required* part in
"Required Reading" more easily honored.
Some of these books you may find in our office, so feel free to pick them up.
If any are missing and you would like a physical copy, don't be afraid to
request the book for our office shelves.
Besides reading, don't get stuck in a rut and be a
[Blub Programmer](http://www.paulgraham.com/avg.html).
## Effective C++ by Scott Meyers
Required for C++ developers.
The book is a must-read as it explains most common gotchas of using C++. After
reading this book, you are good to write competent C++ which will pass code
reviews easily.
## Effective Modern C++ by Scott Meyers
Required for C++ developers.
This is a continuation of the previous book, it covers updates to C++ which
came with C++11 and later. The book isn't as imperative as the previous one,
but it will make you aware of modern features we are using in our codebase.
## Practical Common Lisp by Peter Siebel
Required for Common Lisp developers.
Free: http://www.gigamonkeys.com/book/
We use Common Lisp to generate C++ code and make our lives easier.
Unfortunately, not many developers are familiar with the language. This book
will make you familiar very quickly as it has tons of very practical
exercises. E.g. implementing unit testing library, serialization library and
bundling all that to create a mp3 music server.
## Effective Python by Brett Slatkin
(Almost) required reading for Python developers.
Why the "almost"? Well, Python is relatively easy to pick up and you will
probably learn all the gotchas during code review from someone more
experienced. This makes the book less necessary for a newcomer to Memgraph,
but the book is not advanced enough to delegate it to
[Advanced Reading](#advanced-reading). The book is written in similar vein as
the "Effective C++" ones and will make you familiar with nifty Python features
that make everyone's lives easier.
# Advanced Reading
The books listed below are not required reading, but you may want to read them
at some point when you feel comfortable enough.
## Design Patterns by Gamma et. al.
Recommended for C++ developers.
This book is highly divisive because it introduced a culture centered around
design patterns. The main issues is overuse of patterns which complicates the
code. This has made many Java programs to serve as examples of highly
complicated, "enterprise" code.
Unfortunately, design patterns are pretty much missing
language features. This is most evident in dynamic languages such as Python
and Lisp, as demonstrated by
[Peter Norvig](http://www.norvig.com/design-patterns/).
Or as [Paul Graham](http://www.paulgraham.com/icad.html) put it:
```
This practice is not only common, but institutionalized. For example, in the
OO world you hear a good deal about "patterns". I wonder if these patterns are
not sometimes evidence of case (c), the human compiler, at work. When I see
patterns in my programs, I consider it a sign of trouble. The shape of a
program should reflect only the problem it needs to solve. Any other
regularity in the code is a sign, to me at least, that I'm using abstractions
that aren't powerful enough-- often that I'm generating by hand the expansions
of some macro that I need to write
```
After presenting the book so negatively, why you should even read it then?
Well, it is good to be aware of those design patterns and use them when
appropriate. They can improve modularity and reuse of the code. You will also
find examples of such patterns in our code, primarily Strategy and Visitor
patterns. The book is also a good stepping stone to more advanced reading
about software design.
## Modern C++ Design by Andrei Alexandrescu
Recommended for C++ developers.
This book can be treated as a continuation of the previous "Design Patterns"
book. It introduced "dark arts of template meta-programming" to the world.
Many of the patterns are converted to use C++ templates which makes them even
better for reuse. But, like the previous book, there are downsides if used too
much. You should approach it with a critical eye and it will help you
understand ideas that are used in some parts of our codebase.
## Large Scale C++ Software Design by John Lakos
Recommended for C++ developers.
An old book, but well worth the read. Lakos presents a very pragmatic view of
writing modular software and how it affects both development time as well as
program runtime. Some things are outdated or controversial, but it will help
you understand how the whole C++ process of working in a large team, compiling
and linking affects development.
## On Lisp by Paul Graham
Recommended for Common Lisp developers.
Free: http://www.paulgraham.com/onlisp.html
An excellent continuation to "Practical Common Lisp". It starts of slow, as if
introducing the language, but very quickly picks up speed. The main meat of
the book are macros and their uses. From using macros to define cooperative
concurrency to including Prolog as if it's part of Common Lisp. The book will
help you understand more advanced macros that are occasionally used in our
Lisp C++ Preprocessor (LCP).

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# DatabaseAccessor
A `DatabaseAccessor` actually wraps a transactional access to database
data, for a single transaction. In that sense the naming is bad. It
encapsulates references to the database and the transaction object.
It contains logic for working with database content (graph element
data) in the context of a single transaction. All CRUD operations are
performed within a single transaction (as Memgraph is a transactional
database), and therefore iteration over data, finding a specific graph
element etc are all functionalities of a `GraphDbAccessor`.
In single-node Memgraph the database accessor also defined the lifetime
of a transaction. Even though a `Transaction` object was owned by the
transactional engine, it was `GraphDbAccessor`'s lifetime that object
was bound to (the transaction was implicitly aborted in
`GraphDbAccessor`'s destructor, if it was not explicitly ended before
that).
# RecordAccessor
It is important to understand data organization and access in the
storage layer. This discussion pertains to vertices and edges as graph
elements that the end client works with.
Memgraph uses MVCC (documented on it's own page). This means that for
each graph element there could be different versions visible to
different currently executing transactions. When we talk about a
`Vertex` or `Edge` as a data structure we typically mean one of those
versions. In code this semantic is implemented so that both those classes
inherit `mvcc::Record`, which in turn inherits `mvcc::Version`.
Handling MVCC and visibility is not in itself trivial. Next to that,
there is other book-keeping to be performed when working with data. For
that reason, Memgraph uses "accessors" to define an API of working with
data in a safe way. Most of the code in Memgraph (for example the
interpretation code) should work with accessors. There is a
`RecordAccessor` as a base class for `VertexAccessor` and
`EdgeAccessor`. Following is an enumeration of their purpose.
### Data access
The client interacts with Memgraph using the Cypher query language. That
language has certain semantics which imply that multiple versions of the
data need to be visible during the execution of a single query. For
example: expansion over the graph is always done over the graph state as
it was at the beginning of the transaction.
The `RecordAccessor` exposes functions to switch between the old and the new
versions of the same graph element (intelligently named `SwitchOld` and
`SwitchNew`) within a single transaction. In that way the client code
(mostly the interpreter) can avoid dealing with the underlying MVCC
version concepts.
### Updates
Data updates are also done through accessors. Meaning: there are methods
on the accessors that modify data, the client code should almost never
interact directly with `Vertex` or `Edge` objects.
The accessor layer takes care of creating version in the MVCC layer and
performing updates on appropriate versions.
Next, for many kinds of updates it is necessary to update the relevant
indexes. There are implicit indexes for vertex labels, as
well as user-created indexes for (label, property) pairs. The accessor
layer takes care of updating the indexes when these values are changed.
Each update also triggers a log statement in the write-ahead log. This
is also handled by the accessor layer.
### Distributed
In distributed Memgraph accessors also contain a lot of the remote graph
element handling logic. More info on that is available in the
documentation for distributed.
### Deferred MVCC data lookup for Edges
Vertices and edges are versioned using MVCC. This means that for each
transaction an MVCC lookup needs to be done to determine which version
is visible to that transaction. This tends to slow things down due to
cache invalidations (version lists and versions are stored in arbitrary
locations on the heap).
However, for edges, only the properties are mutable. The edge endpoints
and type are fixed once the edge is created. For that reason both edge
endpoints and type are available in vertex data, so that when expanding
it is not mandatory to do MVCC lookups of versioned, mutable data. This
logic is implemented in `RecordAccessor` and `EdgeAccessor`.
### Exposure
The original idea and implementation of graph element accessors was that
they'd prevent client code from ever interacting with raw `Vertex` or
`Edge` data. This however turned out to be impractical when implementing
distributed Memgraph and the raw data members have since been exposed
(through getters to old and new version pointers). However, refrain from
working with that data directly whenever possible! Always consider the
accessors to be the first go-to for interacting with data, especially
when in the context of a transaction.
# Skiplist accessor
The term "accessor" is also used in the context of a skiplist. Every
operation on a skiplist must be performed within on an
accessor. The skiplist ensures that there will be no physical deletions
of an object during the lifetime of an accessor. This mechanism is used
to ensure deletion correctness in a highly concurrent container.
We only mention that here to avoid confusion regarding terminology.

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# Label indexes
These are unsorted indexes that contain all the vertices that have the label
the indexes are for (one index per label). These kinds of indexes get
automatically generated for each label used in the database.
### Updating the indexes
Whenever something gets added to the record we update the index (add that
record to index). We keep an index which might contain garbage (not relevant
records, because the value got removed or something similar) but we will
filter it out when querying the index. We do it like this because we don't
have to do bookkeeping and deciding if we update the index on the end of the
transaction (commit/abort phase), moreover current interpreter advances the
command in transaction and as such assumes that the indexes now contain
objects added in the previous command inside this transaction, so we need to
update over the whole scope of transaction (whenever something is added to the
record).
### Index Entries Label
These kinds of indexes are internally keeping track of pair (record, vlist).
Why do we need to keep track of exactly those two things?
Problems with two different approaches
1) Keep track of just the record:
- We need the `VersionList` for creating an accessor (this in itself is a
deal-breaker).
- Semantically it makes sense. An edge/vertex maps bijectionally to a
`VersionList`.
- We might try to access some members of record while the record is being
modified from another thread.
- A vertex/edge could get updated, thus expiring the record in the index.
The newly created record should be present in the index, but it's not.
Without the `VersionList` we can't reach the newly created record.
- Probably there are even more reasons... It should be obvious by now that
we need the `VersionList` in the index.
2) Keep track of just the version list:
- Removing from an index is a problem for two major reasons. First, if we
only have the `VersionList`, checking if it should be removed implies
checking all the reachable records, which is not thread-safe. Second,
there are issues with concurrent removal and insertion. The cleanup thread
could determine the vertex/edge should be removed from the index and
remove it, while in between those ops another thread attempts to insert
the `VersionList` into the index. The insertion does nothing because the
`VersionList` is already in, but it gets removed immediately after.
Because of inability to keep track of just the record, or value, we need to
keep track of both of them. Resolution of problems mentioned above, in the
same order, with (record, vlist) pair
- simple `vlist.find(current transaction)` will get us the newest visible
record
- we'll never try to access some record if it's still being written since we
will always operate on vlist.find returned record
- newest record will contain that label
- since we have (record, vlist) pair as the key in the index when we update
and delete in the same time we will never delete the same record, vlist
pair we are adding because the record, vlist pair we are deleting is
already superseded by a newer record and as such won't be inserted while
it's being deleted
### Querying the index
We run through the index for the given label and do `vlist.find` operation for
the current transaction, and check if the newest return record has that
label. If it has it then we return it. By now you are probably wondering
aren't we sometimes returning duplicate vlist entries? And you are wondering
correctly, we would be returning them, but we are making sure that the entires
in the index are sorted by their `vlist*` and as such we can filter consecutive
duplicate `vlist*` to only return one of those while still being able to create
an iterator to index.
### Cleaning the index
Cleaning the index is not as straightforward as it seems as a lot of garbage
can accumulate, but it's hard to know when exactly can we delete some (record,
vlist) pair. First, let's assume that we are doing the cleaning process at
some `transaction_id`, `id` such that there doesn't exist an active transaction
with an id lower than `id`.
We scan through the whole index and for each (record, vlist) pair we first
check if it was deleted before the id (i.e. no transaction with an id >= `id`
will ever again see that record), if it was deleted before we might naively
say that it's safe to delete it, but, we must take into account that when some
new record is created from this record (update operation), that record still
contains the label but by deleting this record we won't be able to see that
vlist because that new record won't add again to index because we didn't
explicitly add that label again to it.
Because of this we have to 'update' this index (record, vlist) pair. We have
to update the record to now point to a newer record in vlist, the one that is
not deleted yet. We can do that by querying the `version_list` for the last
record inside (oldest it has &mdash; remember that `mvcc_gc` will re-link not
visible records so the last record will be visible for the current GC id).
When updating the record inside the index, it's not okay to just update the
pointer and leave the index as it is, because with updating the `record*` we
might change the relative order of entries inside the index. We first have to
re-insert it with new `record*`, and then delete the old entry. And we need to
do insertion before the remove operation! Otherwise it could happen that the
vlist with a newer record with that label won't exist while some transaction
is querying the index.
Records which we added as a consequence of deleting older records will be
eventually removed from the index if they don't contain label because if we
see that the record is not deleted we try to check if that record still
contains the label. We also need to be careful here because we can't check
that while the record is being potentially updated by some transaction (race
condition), so we need can check if records still contain label if it's
creation id is smaller than our `id`, as that implies that the creating
transaction either aborted or committed as our `id` is equal to the oldest
active transaction in time of starting the GC.

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# Property storage
Although the reader is probably familiar with properties in *Memgraph*, let's
briefly recap.
Both vertices and edges can store an arbitrary number of properties. Properties
are, in essence, ordered pairs of property names and property values. Each
property name within a single graph element (edge/node) can store a single
property value. Property names are represented as strings, while property values
must be one of the following types:
Type | Description
-----------|------------
`Null` | Denotes that the property has no value. This is the same as if the property does not exist.
`String` | A character string, i.e. text.
`Boolean` | A boolean value, either `true` or `false`.
`Integer` | An integer number.
`Float` | A floating-point number, i.e. a real number.
`List` | A list containing any number of property values of any supported type. It can be used to store multiple values under a single property name.
`Map` | A mapping of string keys to values of any supported type.
Property values are modeled in a class conveniently called `PropertyValue`.
## Mapping between property names and property keys.
Although users think of property names in terms of descriptive strings
(e.g. "location" or "department"), *Memgraph* internally converts those names
into property keys which are, essentially, unsigned 16-bit integers.
Property keys are modelled by a not-so-conveniently named class called
`Property` which can be found in `storage/types.hpp`. The actual conversion
between property names and property keys is done within the `ConcurrentIdMapper`
but the internals of that implementation are out of scope for understanding
property storage.
## PropertyValueStore
Both `Edge` and `Vertex` objects contain an instance of `PropertyValueStore`
object which is responsible for storing properties of a corresponding graph
element.
An interface of `PropertyValueStore` is as follows:
Method | Description
-----------|------------
`at` | Returns the `PropertyValue` for a given `Property` (key).
`set` | Stores a given `PropertyValue` under a given `Property` (key).
`erase` | Deletes a given `Property` (key) alongside its corresponding `PropertyValue`.
`clear` | Clears the storage.
`iterator`| Provides an extension of `std::input_iterator` that iterates over storage.
## Storage location
By default, *Memgraph* is an in-memory database and all properties are therefore
stored in working memory unless specified otherwise by the user. User has an
option to specify via the command line which properties they wish to be stored
on disk.
Storage location of each property is encapsulated within a `Property` object
which is ensured by the `ConcurrentIdMapper`. More precisely, the unsigned 16-bit
property key has the following format:
```
|---location--|------id------|
|-Memory|Disk-|-----2^15-----|
```
In other words, the most significant bit determines the location where the
property will be stored.
### In-memory storage
The underlying implementation of in-memory storage for the time being is
`std::vector<std::pair<Property, PropertyValue>>`. Implementations of`at`, `set`
and `erase` are linear in time. This implementation is arguably more efficient
than `std::map` or `std::unordered_map` when the average number of properties of
a record is relatively small (up to 10) which seems to be the case.
### On-disk storage
#### KVStore
Disk storage is modeled by an abstraction of key-value storage as implemented in
`storage/kvstore.hpp'. An interface of this abstraction is as follows:
Method | Description
----------------|------------
`Put` | Stores the given value under the given key.
`Get` | Obtains the given value stored under the given key.
`Delete` | Deletes a given (key, value) pair from storage..
`DeletePrefix` | Deletes all (key, value) pairs where key begins with a given prefix.
`Size` | Returns the size of the storage or, optionally, the number of stored pairs that begin with a given prefix.
`iterator` | Provides an extension of `std::input_iterator` that iterates over storage.
Keys and values in this context are of type `std::string`.
The actual underlying implementation of this abstraction uses
[RocksDB]{https://rocksdb.org} &mdash; a persistent key-value store for fast
storage.
It is worthy to note that the custom iterator implementation allows the user
to iterate over a given prefix. Otherwise, the implementation follows familiar
c++ constructs and can be used as follows:
```
KVStore storage = ...;
for (auto it = storage.begin(); it != storage.end(); ++it) {}
for (auto kv : storage) {}
for (auto it = storage.begin("prefix"); it != storage.end("prefix"); ++it) {}
```
Note that it is not possible to scan over multiple prefixes. For instance, one
might assume that you can scan over all keys that fall in a certain
lexicographical range. Unfortunately, that is not the case and running the
following code will result in an infinite loop with a touch of undefined
behavior.
```
KVStore storage = ...;
for (auto it = storage.begin("alpha"); it != storage.end("omega"); ++it) {}
```
#### Data organization on disk
Each `PropertyValueStore` instance can access a static `KVStore` object that can
store `(key, value)` pairs on disk. The key of each property on disk consists of
two parts &mdash; a unique identifier (unsigned 64-bit integer) of the current
record version (see mvcc docummentation for further clarification) and a
property key as described above. The actual value of the property is serialized
into a bytestring using bolt `BaseEncoder`. Similarly, deserialization is
performed by bolt `Decoder`.

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# Bootstrapping Compilation Toolchain for Memgraph
Requirements:
* libstdc++ shipped with gcc-6.3 or gcc-6.4
* cmake >= 3.1, Debian Stretch uses cmake-3.7.2
* clang-3.9
## Installing gcc-6.4
gcc-6.3 has a bug, so use the 6.4 version which is just a bugfix release.
Requirements on CentOS 7:
* wget
* make
* gcc (bootstrap)
* gcc-c++ (bootstrap)
* gmp-devel (bootstrap)
* mpfr-devel (bootstrap)
* libmpc-devel (bootstrap)
* zip
* perl
* dejagnu (testing)
* expect (testing)
* tcl (testing)
```
wget ftp://ftp.mpi-sb.mpg.de/pub/gnu/mirror/gcc.gnu.org/pub/gcc/releases/gcc-6.4.0/gcc-6.4.0.tar.gz
tar xf gcc-6.4.0.tar.gz
cd gcc-6.4.0
mkdir build
cd build
../configure --disable-multilib --prefix=<install-dst>
make
# Testing
make -k check
make install
```
*Do not put gcc + libs on PATH* (unless you know what you are doing).
## Installing cmake-3.7.2
Requirements on CentOS 7:
* wget
* make
* gcc
* gcc-c++
* ncurses-devel (optional, for ccmake)
```
wget https://cmake.org/files/v3.7/cmake-3.7.2.tar.gz
tar xf cmake-3.7.2.tar.gz
cd cmake-3.7.2.tar.gz
./bootstrap --prefix<install-dst>
make
make install
```
Put cmake on PATH (if appropriate)
**Fix the bug in CpackRPM**
`"<path-to-cmake>/share/cmake-3.7/Modules/CPackRPM.cmake" line 2273 of 2442`
The line
```
set(RPMBUILD_FLAGS "-bb")
```
needs to be before
```
if(CPACK_RPM_GENERATE_USER_BINARY_SPECFILE_TEMPLATE OR NOT CPACK_RPM_USER_BINARY_SPECFILE)
```
It was probably accidentally placed after, and is fixed in later cmake
releases.
## Installing clang-3.9
Requirements on CentOS 7:
* wget
* make
* cmake
```
wget http://releases.llvm.org/3.9.1/llvm-3.9.1.src.tar.xz
tar xf llvm-3.9.1.src.tar.xz
mv llvm-3.9.1.src llvm
wget http://releases.llvm.org/3.9.1/cfe-3.9.1.src.tar.xz
tar xf cfe-3.9.1.src.tar.xz
mv cfe-3.9.1.src llvm/tools/clang
cd llvm
mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE="Release" -DGCC_INSTALL_PREFIX=<gcc-dir> \
-DCMAKE_C_COMPILER=<gcc> -DCMAKE_CXX_COMPILER=<g++> \
-DCMAKE_CXX_LINK_FLAGS="-L<gcc-dir>/lib64 -Wl,-rpath,<gcc-dir>/lib64" \
-DCMAKE_INSTALL_PREFIX=<install-dst> ..
make
# Testing
make check-clang
make install
```
Put clang on PATH (if appropriate)
## Memgraph
Requirements on CentOS 7:
* libuuid-devel (antlr4)
* java-1.8.0-openjdk (antlr4)
* boost-static (too low version --- compile manually)
* rpm-build (RPM)
* python3 (tests, ...)
* which (required for rocksdb)
* sbcl (lisp C++ preprocessing)
### Boost 1.62
```
wget https://netix.dl.sourceforge.net/project/boost/boost/1.62.0/boost_1_62_0.tar.gz
tar xf boost_1_62_0.tar.gz
cd boost_1_62_0
./bootstrap.sh --with-toolset=clang --with-libraries=iostreams,serialization --prefix=<install-dst>
./b2
# Default installs to /usr/local/
./b2 install
```
### Building Memgraph
clang is *required* to be findable by cmake, i.e. it should be on PATH.
cmake isn't required to be on the path, since you run it manually, so can use
the full path to executable in order to run it. Obviously, it is convenient to
put cmake also on PATH.
Building is done as explained in [Quick Start](quick-start.md), but each
`make` invocation needs to be prepended with:
`LD_RUN_PATH=<gcc-dir>/lib64 make ...`
### RPM
Name format: `memgraph-<version>-<pkg-version>.<arch>.rpm`

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# Memgraph Workflow
This chapter describes the usual workflow for working on Memgraph.
## Git
Memgraph uses [git](https://git-scm.com/) for source version control. If you
obtained the source, you probably already have it installed. Before you can
track new changes, you need to setup some basic information.
First, tell git your name:
git config --global user.name "FirstName LastName"
Then, set your Memgraph email:
git config --global user.email "my.email@memgraph.com"
Finally, make git aware of your favourite editor:
git config --global core.editor "vim"
## Phabricator
All of the code in Memgraph needs to go through code review before it can be
accepted in the codebase. This is done through
[Phabricator](https://phacility.com/phabricator/). The command line tool for
interfacing with Phabricator is
[arcanist](https://phacility.com/phabricator/arcanist/). You should already
have it installed if you followed the steps in [Quick Start](quick-start.md).
The only required setup is to go in the root of Memgraph's project and run:
arc install-certificate
## Working on Your Feature Branch
Git has a concept of source code *branches*. The `master` branch contains all
of the changes which were reviewed and accepted in Memgraph's code base. The
`master` branch is selected by default.
### Creating a Branch
When working on a new feature or fixing a bug, you should create a new branch
out of the `master` branch. For example, let's say you are adding static type
checking to the query language compiler. You would create a branch called
`mg_query_static_typing` with the following command:
git branch mg_query_static_typing
To switch to that branch, type:
git checkout mg_query_static_typing
Since doing these two steps will happen often, you can use a shortcut command:
git checkout -b mg_query_static_typing
Note that a branch is created from the currently selected branch. So, if you
wish to create another branch from `master` you need to switch to `master`
first.
The usual convention for naming your branches is `mg_<feature_name>`, you may
switch underscores ('\_') for hyphens ('-').
Do take care not to mix the case of your branch names! Certain operating
systems (like Windows) don't distinguish the casing in git branches. This may
cause hard to track down issues when trying to switch branches. Therefore, you
should always name your branches with lowercase letters.
### Making and Committing Changes
When you have a branch for your new addition, you can now actually start
implementing it. After some amount of time, you may have created new files,
modified others and maybe even deleted unused files. You need to tell git to
track those changes. This is accomplished with `git add` and `git rm`
commands.
git add path-to-new-file path-to-modified-file
git rm path-to-deleted-file
To check that everything is correctly tracked, you may use the `git status`
command. It will also print the name of the currently selected branch.
If everything seems OK, you should commit these changes to git.
git commit
You will be presented with an editor where you need to type the commit
message. Writing a good commit message is an art in itself. You should take a
look at the links below. We try to follow these conventions as much as
possible.
* [How to Write a Git Commit Message](http://chris.beams.io/posts/git-commit/)
* [A Note About Git Commit Messages](http://tbaggery.com/2008/04/19/a-note-about-git-commit-messages.html)
* [stopwritingramblingcommitmessages](http://stopwritingramblingcommitmessages.com/)
### Sending Changes on a Review
After finishing your work on your feature branch, you will want to send it on
code review. This is done through Arcanist. To do that, run the following
command:
arc diff
You will, once again, be presented with an editor where you need to describe
your whole work. `arc` will by default fill that description with your commit
messages. The title and summary of your work should also follow the
conventions of git messages as described above. If you followed the
guidelines, the message filled by `arc` should be fine.
In addition to the message, you need to fill the `Reviewers:` line with
usernames of people who should do the code review.
You changes will be visible on Phabricator as a so called "diff". You can find
the default view of active diffs
[here](https://phabricator.memgraph.io/differential/)
### Updating Changes Based on Review
When you get comments in the code review, you will want to make additional
modifications to your work. The same workflow as before applies: [Making and
Committing Changes](#making-and-committing-changes)
After making those changes, send them back on code review:
arc diff
### Updating From New Master
Let's say that, while you were working, someone else added some new features
to the codebase that you would like to use in your current work. To obtain
those changes you should update your `master` branch:
git checkout master
git pull origin master
Now, these changes are on `master`, but you want them in your local branch. To
do that, use `git rebase`:
git checkout mg_query_static_typing
git rebase master
During `git rebase`, you may get reports that some files have conflicting
changes. If you need help resolving them, don't be afraid to ask around! After
you've resolved them, mark them as done with `git add` command. You may
then continue with `git rebase --continue`.
After the `git rebase` is done, you will now have new changes from `master` on
your feature branch as if you just created and started working on that branch.
You may continue with the usual workflow of [Making and Committing
Changes](#making-and-committing-changes) and [Sending Changes on a
Review](#sending-changes-on-a-review).
### Sending Your Changes on Master Branch
When your changes pass the code review, you are ready to integrate them in the
`master` branch. To do that, run the following command:
arc land
Arcanist will take care of obtaining the latest changes from `master` and
merging your changes on top. If the `land` was successful, Arcanist will
delete your local branch and you will be back on `master`. Continuing from the
examples above, the deleted branch would be `mg_query_static_typing`.
This marks the completion of your changes, and you are ready to work on
something else.
### Note For People Familiar With Git
Since Arcanist takes care of merging your git commits and pushing them on
`master`, you should *never* have to call `git merge` and `git push`. If you
find yourself typing those commands, check that you are doing the right thing.
The most common mistake is to use `git merge` instead of `git rebase` for the
case described in [Updating From New Master](#updating-from-new-master).

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@@ -1,6 +1,7 @@
# Memgraph Code Documentation
IMPORTANT: Auto-generated (run doxygen Doxyfile in the project root).
IMPORTANT: auto-generated (run doxygen Doxyfile in the project root)
* HTML - Open docs/doxygen/html/index.html.
* Latex - Run make inside docs/doxygen/latex.
* HTML - just open docs/doxygen/html/index.html
* Latex - run make inside docs/doxygen/latex

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## Dynamic Graph Partitioner
Memgraph supports dynamic graph partitioning which dynamically improves
performance on badly partitioned dataset over workers. To enable it, the user
should use the following flag when firing up the *master* node:
```plaintext
--dynamic_graph_partitioner_enable
```
### Parameters
| Name | Default Value | Description | Range |
|------|---------------|-------------|-------|
|--dgp_improvement_threshold | 10 | How much better should specific node score
be to consider a migration to another worker. This represents the minimal
difference between new score that the vertex will have when migrated and the
old one such that it's migrated. | Min: 1, Max: 100
|--dgp_max_batch_size | 2000 | Maximal amount of vertices which should be
migrated in one dynamic graph partitioner step. | Min: 1, Max: MaxInt32 |

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# Distributed Memgraph specs
This document describes reasnonings behind Memgraphs distributed concepts.
## Distributed state machine
Memgraphs distributed mode introduces two states of the cluster, recovering and
working. The change between states shouldn't happen often, but when it happens
it can take a while to make a transition from one to another.
### Recovering
This state is the default state for Memgraph when the cluster starts with
recovery flags. If the recovery finishes successfully, the state changes to
working. If recovery fails, the user will be presented with a message that
explains what happened and what are the next steps.
Another way to enter this state is failure. If the cluster encounters a failure,
the master will enter the Recovering mode. This time, it will wait for all
workers to respond with a message saying they are alive and well, and making
sure they all have consistent state.
### Working
This state should be the default state of Memgraph most of the time. When in
this state, Memgraph accepts connections from Bolt clients and allows query
execution.
If distributed execution fails for a transaction, that transaction, and all
other active transactions will be aborted and the cluster will enter the
Recovering state.
## Durability
One of the important concepts in distributed Memgraph is durability.
### Cluster configuration
When running Memgraph in distributed mode, the master will store cluster
metadata in a persistent store. If fore some reason the cluster shuts down,
recovering Memgraph from durability files shouldn't require any additional
flags.
### Database ID
Each new and clean run of Memgraph should generate a new globally unique
database id. This id will associate all files that have persisted with this
run. Adding the database id to snapshots, write-ahead logs and cluster metadata
files ties them a specific Memgraph run, and it makes recovery easier to reason
about.
When recovering, the cluster won't generate a new id, but will reuse the one
from the snapshot/wal that it was able to recover from.
### Durability files
Memgraph uses snapshots and write-ahead logs for durability.
When Memgraph recovers it has to make sure all machines in the cluster recover
to the same recovery point. This is done by finding a common snapshot and
finding common transactions in per-machine available write-ahead logs.
Since we can not be sure that each machine persisted durability files, we need
to be able to negotiate a common recovery point in the cluster. Possible
durability file failures could require to start the cluster from scratch,
purging everything from storage and recovering from existing durability files.
We need to ensure that we keep wal files containing information about
transactions between all existing snapshots. This will provide better durability
in the case of a random machine durability file failure, where the cluster can
find a common recovery point that all machines in the cluster have.
Also, we should suggest and make clear docs that anything less than two
snapshots isn't considered safe for recovery.
### Recovery
The recovery happens in following steps:
* Master enables worker registration.
* Master recovers cluster metadata from the persisted storage.
* Master waits all required workers to register.
* Master broadcasts a recovery request to all workers.
* Workers respond with with a set of possible recovery points.
* Master finds a common recovery point for the whole cluster.
* Master broadcasts a recovery request with the common recovery point.
* Master waits for the cluster to recover.
* After a successful cluster recovery, master can enter Working state.

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# Dynamic Graph Partitioning (abbr. DGP)
## Implementation
Take a look under `dev/memgraph/distributed/dynamic_graph_partitioning.md`.
### Implemented parameters
--dynamic-graph-partitioner-enabled (If the dynamic graph partitioner should be
enabled.) type: bool default: false (start time)
--dgp-improvement-threshold (How much better should specific node score be
to consider a migration to another worker. This represents the minimal
difference between new score that the vertex will have when migrated
and the old one such that it's migrated.) type: int32 default: 10
(start time)
--dgp-max-batch-size (Maximal amount of vertices which should be migrated
in one dynamic graph partitioner step.) type: int32 default: 2000
(start time)
## Planning
### Design decisions
* Each partitioning session has to be a new transaction.
* When and how does an instance perform the moves?
* Periodically.
* Token sharing (round robin, exactly one instance at a time has an
opportunity to perform the moves).
* On server-side serialization error (when DGP receives an error).
-> Quit partitioning and wait for the next turn.
* On client-side serialization error (when end client receives an error).
-> The client should never receive an error because of any
internal operation.
-> For the first implementation, it's good enough to wait until data becomes
available again.
-> It would be nice to achieve that DGP has lower priority than end client
operations.
### End-user parameters
* --dynamic-graph-partitioner-enabled (execution time)
* --dgp-improvement-threshold (execution time)
* --dgp-max-batch-size (execution time)
* --dgp-min-batch-size (execution time)
-> Minimum number of nodes that will be moved in each step.
* --dgp-fitness-threshold (execution time)
-> Do not perform moves if partitioning is good enough.
* --dgp-delta-turn-time (execution time)
-> Time between each turn.
* --dgp-delta-step-time (execution time)
-> Time between each step.
* --dgp-step-time (execution time)
-> Time limit per each step.
### Testing
The implementation has to provide good enough results in terms of:
* How good the partitioning is (numeric value), aka goodness.
* Workload execution time.
* Stress test correctness.
Test cases:
* N not connected subgraphs
-> shuffle nodes to N instances
-> run partitioning
-> test perfect partitioning.
* N connected subgraph
-> shuffle nodes to N instance
-> run partitioning
-> test partitioning.
* Take realistic workload (Long Running, LDBC1, LDBC2, Card Fraud, BFS, WSP)
-> measure exec time
-> run partitioning
-> test partitioning
-> measure exec time (during and after partitioning).

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# High Availability (abbr. HA)
## Introduction
High availability is a characteristic of a system which aims to ensure a
certain level of operational performance for a higher-than-normal period.
Although there are multiple ways to design highly available systems, Memgraph
strives to achieve HA by elimination of single points of failure. In essence,
this implies adding redundancy to the system so that a failure of a component
does not imply the failure of the entire system.
## Theoretical Background
The following chapter serves as an introduction into some theoretical aspects
of Memgraph's high availability implementation. If the reader is solely
interested in design decisions around HA implementation, they can skip this
chapter.
An important implication of any HA implementation stems from Eric Brewer's
[CAP Theorem](https://fenix.tecnico.ulisboa.pt/downloadFile/1126518382178117/10.e-CAP-3.pdf)
which states that it is impossible for a distributed system to simultaneously
achieve:
* Consistency (C - every read receives the most recent write or an error)
* Availability (A - every request receives a response that is not an error)
* Partition tolerance (P - The system continues to operate despite an
arbitrary number of messages being dropped by the
network between nodes)
In the context of HA, Memgraph should strive to achieve CA.
### Consensus
Implications of the CAP theorem naturally lead us towards introducing a
cluster of machines which will have identical internal states. When a designated
machine for handling client requests fails, it can simply be replaced with
another.
Well... turns out this is not as easy as it sounds :(
Keeping around a cluster of machines with consistent internal state is an
inherently difficult problem. More precisely, this problem is as hard as
getting a cluster of machines to agree on a single value, which is a highly
researched area in distributed systems. Our research of state of the art
consensus algorithms lead us to Diego Ongaro's
[Raft algorithm](https://raft.github.io/raft.pdf).
#### Raft
As you might have guessed, analyzing each subtle detail of Raft goes way
beyond the scope of this document. In the remainder of the chapter we will
outline only the most important ideas and implications, leaving all further
analysis to the reader. Detailed explanation can be found either in Diego's
[dissertation](https://ramcloud.stanford.edu/~ongaro/thesis.pdf) \[1\] or the
Raft [paper](https://raft.github.io/raft.pdf) \[2\].
In essence, Raft allows us to implement the previously mentioned idea of
managing a cluster of machines with identical internal states. In other
words, the Raft protocol allows us to manage a cluster of replicated
state machines which is fully functional as long as the *majority* of
the machines in the cluster operate correctly.
Another important fact is that those state machines must be *deterministic*.
In other words, the same command on two different machines with the same
internal state must yield the same result. This is important because Memgraph,
as a black box, is not entirely deterministic. Non-determinism can easily be
introduced by the user (e.g. by using the `rand` function) or by algorithms
behind query execution (e.g. introducing fuzzy logic in the planner could yield
a different order of results). Luckily, once we enter the storage level,
everything should be fully deterministic.
To summarize, Raft is a protocol which achieves consensus in a cluster of
deterministic state machines via log replication. The cluster is fully
functional if the majority of the machines work correctly. The reader
is strongly encouraged to gain a deeper understanding (at least read through
the paper) of Raft before reading the rest of this document.
## Integration with Memgraph
The first thing that should be defined is a single instruction within the
context of Raft (i.e. a single entry in a replicated log). As mentioned
before, these instructions should be completely deterministic when applied
to the state machine. We have therefore decided that the appropriate level
of abstraction within Memgraph corresponds to `StateDelta`-s (data structures
which describe a single change to the Memgraph state, used for durability
in WAL). Moreover, a single instruction in a replicated log will consist of a
batch of `StateDelta`s which correspond to a single **committed** transaction.
This decision both improves performance and handles some special cases that
present themselves otherwise by leveraging the knowledge that the transaction
should be committed.
"What happens with aborted transactions?"
A great question, they are handled solely by the leader which is the only
machine that communicates with the client. Aborted transactions do not alter
the state of the database and there is no need to replicate it to other machines
in the cluster. If, for instance, the leader dies before returning the result
of some read operation in an aborted transaction, the client will notice that
the leader has crashed. A new leader will be elected in the next term and the
client should retry the transaction.
"OK, that makes sense! But, wait a minute, this is broken by design! Merely
generating `StateDelta`s on the leader for any transaction will taint its
internal storage before sending the first RPC to some follower. This deviates
from Raft and will crash the universe!"
Another great observation. It is indeed true that applying `StateDelta`s makes
changes to local storage, but only a single type of `StateDelta` makes that
change durable. That `StateDelta` type is called `TRANSACTION_COMMIT` and we
will change its behaviour when working as a HA instance. More precisely, we
must not allow the transaction engine to modify the commit log saying that
the transaction has been committed. That action should be delayed until those
`StateDelta`s have been applied to the majority of the cluster. At that point
the commit log can be safely modified leaving it up to Raft to ensure the
durability of the transaction.
We should also address one subtle detail that arises in this case. Consider
the following scenario:
* The leader starts working on a transaction which creates a new record in the
database. Suppose that record is stored in the leader's internal storage
but the transaction was not committed (i.e. no such entry in the commit log).
* The leader should start replicating those `StateDelta`s to its followers
but, suddenly, it's cut off from the rest of the cluster.
* Due to timeout, a new election is held and a new leader has been elected.
* Our old leader comes back to life and becomes a follower.
* The new leader receives a transaction which creates that same record, but
this transaction is successfully replicated and committed by the new leader.
The problem lies in the fact that there is still a record within the internal
storage of our old leader with the same transaction ID and GID as the recently
committed record by the new leader. Obviously, this is broken. As a solution, on
each transition from `Leader` to `Follower`, we will reinitialize storage, reset
the transaction engine and recover data from the Raft log. This will ensure all
ongoing transactions which have "polluted" the storage will be gone.
"When will followers append that transaction to their commit logs?"
When the leader deduces that the transaction is safe to commit, it will include
the relevant information in all further heartbeats which will alert the
followers that it is safe to commit those entries from their raft logs.
Naturally, the followers need not to delay appending data to the commit log
as they know that the transaction has already been committed (from the clusters
point of view). If this sounds really messed up, seriously, read the Raft paper.
"How does the raft log differ from WAL"
Conceptually, it doesn't. When operating in HA, we don't really need the
recovery mechanisms implemented in Memgraph thus far. When a dead machine
comes back to life, it will eventually come in sync with the rest of the
cluster and everything will be done using the machine's raft log as well
as the messages received from the cluster leader.
"Those logs will become huge, isn't that recovery going to be painfully slow?"
True, but there are mechanisms for making raft logs more compact. The most
popular method is, wait for it, making snapshots :)
Although the process of bringing an old machine back to life is a long one,
it doesn't really affect the performance of the cluster in a great degree.
The cluster will work perfectly fine with that machine being way out of sync.
"I don't know, everything seems to be a lot slower than before!"
Absolutely true, the user should be aware that they will suffer dire
consequences on the performance side if they choose to be highly available.
As Frankie says, "That's life!".
"Also, I didn't really care about most of the things you've said. I'm
not a part of the storage team and couldn't care less about the issues you
face, how does HA affect 'my part of the codebase'?"
Answer for query execution: That's ok, you'll be able to use the same beloved
API (when we implement it, he he :) towards storage and continue to
make fun of us when you find a bug.
Answer for infrastructure: We'll talk. Some changes will surely need to
be made on the Memgraph client. There is a chapter in Diego's dissertation
called 'Client interaction', but we'll cross that bridge when we get there.
There will also be the whole 'integration with Jepsen tests' thing going on.
Answer for analytics: I'm astonished you've read this article. Wanna join
storage?
### Subtlety Regarding Reads
As we have hinted in the previous chapter, we would like to bypass log
replication for operations which do not alter the internal state of Memgraph.
Those operations should therefore be handled only by the leader, which is not
as trivial as it seems. The subtlety arises from the fact that a (newly-elected)
leader can have an entry in its log which was committed by the previous leader
that has crashed but that entry is not yet committed in its internal storage
by the current leader. Moreover, the rule about safely committing logs that are
replicated on the majority of the cluster only applies for entries replicated in
the leaders current term. Therefore, we are faced with two issues:
* We cannot simply perform read operations if the leader has a non-committed
entry in its log (breaks consistency).
* Replicating those entries onto the majority of the cluster is not enough
to guarantee that they can be safely committed.
This can be solved by introducing a blank no-op operation which the new leader
will try to replicate at the start of its term. Once that operation is
replicated and committed, the leader can safely perform those non-altering
operations on its own.
For further information about these issues, you should check out section
5.4.2 from the raft paper \[1\] which hints as to why its not safe to commit
entries from previous terms. Also, you should check out section 6.4 from
the thesis \[2\] which goes into more details around efficiently processing
read-only queries.
## How do we test HA
[Check this out](https://jepsen.io/analyses/dgraph-1-0-2)

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# Kafka - openCypher clause
One must be able to specify the following when importing data from Kafka:
* Kafka URI
* Kafka topic
* Transform [script](transform.md) URI
Minimum required syntax looks like:
```opencypher
CREATE STREAM stream_name AS LOAD DATA KAFKA 'URI'
WITH TOPIC 'topic'
WITH TRANSFORM 'URI';
```
The full openCypher clause for creating a stream is:
```opencypher
CREATE STREAM stream_name AS
LOAD DATA KAFKA 'URI'
WITH TOPIC 'topic'
WITH TRANSFORM 'URI'
[BATCH_INTERVAL milliseconds]
[BATCH_SIZE count]
```
The `CREATE STREAM` clause happens in a transaction.
`WITH TOPIC` parameter specifies the Kafka topic from which we'll stream
data.
`WITH TRANSFORM` parameter should contain a URI of the transform script.
`BATCH_INTERVAL` parameter defines the time interval in milliseconds
which is the time between two successive stream importing operations.
`BATCH_SIZE` parameter defines the count of Kafka messages that will be
batched together before import.
If both `BATCH_INTERVAL` and `BATCH_SIZE` parameters are given, the condition
that is satisfied first will trigger the batched import.
Default value for `BATCH_INTERVAL` is 100 milliseconds, and the default value
for `BATCH_SIZE` is 10;
The `DROP` clause deletes a stream:
```opencypher
DROP STREAM stream_name;
```
The `SHOW` clause enables you to see all configured streams:
```opencypher
SHOW STREAMS;
```
You can also start/stop streams with the `START` and `STOP` clauses:
```opencypher
START STREAM stream_name [LIMIT count BATCHES];
STOP STREAM stream_name;
```
A stream needs to be stopped in order to start it and it needs to be started in
order to stop it. Starting a started or stopping a stopped stream will not
affect that stream.
There are also convenience clauses to start and stop all streams:
```opencypher
START ALL STREAMS;
STOP ALL STREAMS;
```
Before the actual import, you can also test the stream with the `TEST
STREAM` clause:
```opencypher
TEST STREAM stream_name [LIMIT count BATCHES];
```
When a stream is tested, data extraction and transformation occurs, but no
output is inserted in the graph.
A stream needs to be stopped in order to test it. When the batch limit is
omitted, `TEST STREAM` will run for only one batch by default.

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# Kafka - data transform
The transform script is a user defined script written in Python. The script
should be aware of the data format in the Kafka message.
Each Kafka message is byte length encoded, which means that the first eight
bytes of each message contain the length of the message.
A sample code for a streaming transform script could look like this:
```python
def create_vertex(vertex_id):
return ("CREATE (:Node {id: $id})", {"id": vertex_id})
def create_edge(from_id, to_id):
return ("MATCH (n:Node {id: $from_id}), (m:Node {id: $to_id}) "\
"CREATE (n)-[:Edge]->(m)", {"from_id": from_id, "to_id": to_id})
def stream(batch):
result = []
for item in batch:
message = item.decode('utf-8').strip().split()
if len(message) == 1:
result.append(create_vertex(message[0])))
else:
result.append(create_edge(message[0], message[1]))
return result
```
The script should output openCypher query strings based on the type of the
records.

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# Tensorflow Op - Technicalities
The final result should be a shared object (".so") file that can be
dynamically loaded by the Tensorflow runtime in order to directly
access the bolt client.
## About Tensorflow
Tensorflow is usually used with Python such that the Python code is used
to define a directed acyclic computation graph. Basically no computation
is done in Python. Instead, values from Python are copied into the graph
structure as constants to be used by other Ops. The directed acyclic graph
naturally ends up with two sets of border nodes, one for inputs, one for
outputs. These are sometimes called "feeds".
Following the Python definition of the graph, during training, the entire
data processing graph/pipeline is called from Python as a single expression.
This leads to lazy evaluation since the called result has already been
defined for a while.
Tensorflow internally works with tensors, i.e. n-dimensional arrays. That
means all of its inputs need to be matrices as well as its outputs. While
it is possible to feed data directly from Python's numpy matrices straight
into Tensorflow, this is less desirable than using the Tensorflow data API
(which defines data input and processing as a Tensorflow graph) because:
1. The data API is written in C++ and entirely avoids Python and as such
is faster
2. The data API, unlike Python is available in "Tensorflow serving". The
default way to serve Tensorflow models in production.
Once the entire input pipeline is defined via the tf.data API, its input
is basically a list of node IDs the model is supposed to work with. The
model, through the data API knows how to connect to Memgraph and execute
openCypher queries in order to get the remaining data it needs.
(For example features of neighbouring nodes.)
## The Interface
I think it's best you read the official guide...
<https://www.tensorflow.org/extend/adding_an_op>
And especially the addition that specifies how data ops are special
<https://www.tensorflow.org/extend/new_data_formats>
## Compiling the TF Op
There are two options for compiling a custom op.
One of them involves pulling the TF source, adding your code to it and
compiling via bazel.
This is probably awkward to do for us and would
significantly slow down compilation.
The other method involves installing Tensorflow as a Python package and
pulling the required headers from for example:
`/usr/local/lib/python3.6/site-packages/tensorflow/include`
We can then compile our Op with our regular build system.
This is practical since we can copy the required headers to our repo.
If necessary, we can have several versions of the headers to build several
versions of our Op for every TF version which we want to support.
(But this is unlikely to be required as the API should be stable).

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# Example for Using the Bolt Client Tensorflow Op
## Dynamic Loading
``` python3
import tensorflow as tf
mg_ops = tf.load_op_library('/usr/bin/memgraph/tensorflow_ops.so')
```
## Basic Usage
``` python3
dataset = mg_ops.OpenCypherDataset(
# This is probably unfortunate as the username and password
# get hardcoded into the graph, but for the simple case it's fine
"hostname:7687", auth=("user", "pass"),
# Our query
'''
MATCH (n:Train) RETURN n.id, n.features
''',
# Cast return values to these types
(tf.string, tf.float32))
# Some Tensorflow data api boilerplate
iterator = dataset.make_one_shot_iterator()
next_element = iterator.get_next()
# Up to now we have only defined our computation graph which basically
# just connects to Memgraph
# `next_element` is not really data but a handle to a node in the Tensorflow
# graph, which we can and do evaluate
# It is a Tensorflow tensor with shape=(None, 2)
# and dtype=(tf.string, tf.float)
# shape `None` means the shape of the tensor is unknown at definition time
# and is dynamic and will only be known once the tensor has been evaluated
with tf.Session() as sess:
node_ids = sess.run(next_element)
# `node_ids` contains IDs and features of all the nodes
# in the graph with the label "Train"
# It is a numpy.ndarray with a shape ($n_matching_nodes, 2)
```
## Memgraph Client as a Generic Tensorflow Op
Other than the Tensorflow Data Op, we'll want to support a generic Tensorflow
Op which can be put anywhere in the Tensorflow computation Graph. It takes in
an arbitrary tensor and produces a tensor. This would be used in the GraphSage
algorithm to fetch the lowest level features into Tensorflow
```python3
requested_ids = np.array([1, 2, 3])
ids_placeholder = tf.placeholder(tf.int32)
model = mg_ops.OpenCypher()
"hostname:7687", auth=("user", "pass"),
"""
UNWIND $node_ids as nid
MATCH (n:Train {id: nid})
RETURN n.features
""",
# What to call the input tensor as an openCypher parameter
parameter_name="node_ids",
# Type of our resulting tensor
dtype=(tf.float32)
)
features = model(ids_placeholder)
with tf.Session() as sess:
result = sess.run(features,
feed_dict={ids_placeholder: requested_ids})
```
This is probably easier to implement than the Data Op, so it might be a good
idea to start with.
## Production Usage
During training, in the GraphSage algorithm at least, Memgraph is at the
beginning and at the end of the Tensorflow computation graph.
At the beginning, the Data Op provides the node IDs which are fed into the
generic Tensorflow Op to find their neighbours and their neighbours and
their features.
Production usage differs in that we don't use the Data Op. The Data Op is
effectively cut off and the initial input is fed by Tensorflow serving,
with the data found in the request.
For example a JSON request to classify a node might look like:
`POST http://host:port/v1/models/GraphSage/versions/v1:classify`
With the contents:
```json
{
"examples": [
{"node_id": 1},
{"node_id": 2}
],
}
```
Every element of the "examples" list is an example to be computed. Each is
represented by a dict with keys matching names of feeds in the Tensorflow
graph and values being the values we want fed in for each example
The REST API then replies in kind with the classification result in JSON
Note about adding our custom Op to Tensorflow serving.
Our Ops .so can be added into the Bazel build to link with Tensorflow serving
or it can be dynamically loaded by starting Tensorflow serving with a flag
`--custom_op_paths`
## Considerations
There might be issues here that the url to connect to Memgraph is
hardcoded into the op and would thus be wrong when moved to production,
requiring some type of a hack to make work. We probably want to solve
this by having the client op take in another tf.Variable as an input
which would contain a connection url and username/password.
We have to research whether this makes it easy enough to move to
production, as the connection string variable is still a part of the
graph, but maybe easier to replace.
It is probably the best idea to utilize openCypher parameters to make
our queries flexible. The exact API as to how to declare the parameters
in Python is open to discussion.
The Data Op might not even be necessary to implement as it is not
key for production use. It can be replaced in training mode with
feed dicts and either
1. Getting the initial list of nodes via a Python Bolt client
2. Creating a separate Tensorflow computation graph that gets all the
relevant node IDs into Python

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# Memgraph LaTeX Beamer Template
This folder contains all of the needed files for creating a presentation with
Memgraph styling. You should use this style for any public presentations.
Feel free to improve it according to style guidelines and raise issues if you
find any.
## Usage
Copy the contents of this folder (excluding this README file) to where you
want to write your own presentation. After copying, you can start editing the
`template.tex` with your content.
To compile the presentation to a PDF, run `latexmk -pdf -xelatex`. Some
directives require XeLaTeX, so you need to pass `-xelatex` as the final option
of `latexmk`. You may also need to install some packages if the compilation
complains about missing packages.
To clean up the generated files, use `latexmk -C`. This will also delete the
generated PDF. If you wish to remove generated files except the PDF, use
`latexmk -c`.

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\NeedsTeXFormat{LaTeX2e}
\ProvidesClass{mg-beamer}[2018/03/26 Memgraph Beamer]
\DeclareOption*{\PassOptionsToClass{\CurrentOption}{beamer}}
\ProcessOptions \relax
\LoadClass{beamer}
\usetheme{Pittsburgh}
% Memgraph color palette
\definecolor{mg-purple}{HTML}{720096}
\definecolor{mg-red}{HTML}{DD2222}
\definecolor{mg-orange}{HTML}{FB6E00}
\definecolor{mg-yellow}{HTML}{FFC500}
\definecolor{mg-gray}{HTML}{857F87}
\definecolor{mg-black}{HTML}{231F20}
\RequirePackage{fontspec}
% Title fonts
\setbeamerfont{frametitle}{family={\fontspec[Path = ./mg-style/fonts/]{EncodeSansSemiCondensed-Regular.ttf}}}
\setbeamerfont{title}{family={\fontspec[Path = ./mg-style/fonts/]{EncodeSansSemiCondensed-Regular.ttf}}}
% Body font
\RequirePackage[sfdefault,light]{roboto}
% Roboto is pretty bad for monospace font. We will find a replacement.
% \setmonofont{RobotoMono-Regular.ttf}[Path = ./mg-style/fonts/]
% Title slide styles
% \setbeamerfont{frametitle}{size=\huge}
% \setbeamerfont{title}{size=\huge}
% \setbeamerfont{date}{size=\tiny}
% Other typography styles
\setbeamertemplate{frametitle}[default][center]
\setbeamercolor{frametitle}{fg=mg-black}
\setbeamercolor{title}{fg=mg-black}
\setbeamercolor{section in toc}{fg=mg-black}
\setbeamercolor{local structure}{fg=mg-orange}
\setbeamercolor{alert text}{fg=mg-red}
% Commands
\newcommand{\mgalert}[1]{{\usebeamercolor[fg]{alert text}#1}}
\newcommand{\titleframe}{\frame[plain]{\titlepage}}
\newcommand{\mgtexttt}[1]{{\textcolor{mg-gray}{\texttt{#1}}}}
% Title slide background
\RequirePackage{tikz,calc}
% Use title-slide-169 if aspect ration is 16:9
\pgfdeclareimage[interpolate=true,width=\paperwidth,height=\paperheight]{logo}{mg-style/title-slide-169}
\setbeamertemplate{background}{
\begin{tikzpicture}
\useasboundingbox (0,0) rectangle (\the\paperwidth,\the\paperheight);
\pgftext[at=\pgfpoint{0}{0},left,base]{\pgfuseimage{logo}};
\ifnum\thepage>1\relax
\useasboundingbox (0,0) rectangle (\the\paperwidth,\the\paperheight);
\fill[white, opacity=1](0,\the\paperheight)--(\the\paperwidth,\the\paperheight)--(\the\paperwidth,0)--(0,0)--(0,\the\paperheight);
\fi
\end{tikzpicture}
}
% Footline content
\setbeamertemplate{navigation symbols}{}%remove navigation symbols
\setbeamertemplate{footline}{
\begin{beamercolorbox}[ht=1.6cm,wd=\paperwidth]{footlinecolor}
\vspace{0.1cm}
\hfill
\begin{minipage}[c]{3cm}
\begin{center}
\includegraphics[height=0.8cm]{mg-style/memgraph-logo.png}
\end{center}
\end{minipage}
\begin{minipage}[c]{7cm}
\insertshorttitle\ --- \insertsection
\end{minipage}
\begin{minipage}[c]{2cm}
\tiny{\insertframenumber{} of \inserttotalframenumber}
\end{minipage}
\end{beamercolorbox}
}
\endinput

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% Set 16:9 aspect ratio
\documentclass[aspectratio=169]{mg-beamer}
% Default directive sets the regular 4:3 aspect ratio
% \documentclass{mg-beamer}
\mode<presentation>
% requires xelatex
\usepackage{ccicons}
\title{Insert Presentation Title}
\titlegraphic{\ccbyncnd}
\author{Insert Name}
% Institute doesn't look good in our current styling class.
% \institute[Memgraph Ltd.]{\pgfimage[height=1.5cm]{mg-logo.png}}
% Date is autogenerated on compilation, so no need to set it explicitly,
% unless you wish to override it with a different date.
% \date{March 23, 2018}
\begin{document}
\titleframe
\section{Intro}
\begin{frame}{Contents}
\tableofcontents
\end{frame}
\begin{frame}{Memgraph Markup Test}
\begin{itemize}
\item \mgtexttt{Prefer \\mgtexttt for monospace}
\item Replace this slide with your own
\item Add even more slides in different sections
\item Make sure you spellcheck your presentation
\end{itemize}
\end{frame}
\end{document}

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*.deb
*.rpm
*.tar.gz

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@@ -1,148 +0,0 @@
#!/bin/bash
set -Eeuo pipefail
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
source "$DIR/../util.sh"
check_operating_system "centos-7"
check_architecture "x86_64"
TOOLCHAIN_BUILD_DEPS=(
coreutils gcc gcc-c++ make # generic build tools
wget # used for archive download
gnupg2 # used for archive signature verification
tar gzip bzip2 xz unzip # used for archive unpacking
zlib-devel # zlib library used for all builds
expat-devel libipt libipt-devel libbabeltrace-devel xz-devel python3-devel # gdb
texinfo # gdb
libcurl-devel # cmake
curl # snappy
readline-devel # cmake and llvm
libffi-devel libxml2-devel perl-Digest-MD5 # llvm
libedit-devel pcre-devel automake bison # swig
file
openssl-devel
gmp-devel
gperf
patch
)
TOOLCHAIN_RUN_DEPS=(
make # generic build tools
tar gzip bzip2 xz # used for archive unpacking
zlib # zlib library used for all builds
expat libipt libbabeltrace xz-libs python3 # for gdb
readline # for cmake and llvm
libffi libxml2 # for llvm
openssl-devel
)
MEMGRAPH_BUILD_DEPS=(
make pkgconfig # build system
curl wget # for downloading libs
libuuid-devel java-11-openjdk # required by antlr
readline-devel # for memgraph console
python3-devel # for query modules
openssl-devel
libseccomp-devel
python3 python-virtualenv python3-pip nmap-ncat # for qa, macro_benchmark and stress tests
#
# IMPORTANT: python3-yaml does NOT exist on CentOS
# Install it using `pip3 install PyYAML`
#
PyYAML # Package name here does not correspond to the yum package!
libcurl-devel # mg-requests
sbcl # for custom Lisp C++ preprocessing
rpm-build rpmlint # for RPM package building
doxygen graphviz # source documentation generators
which mono-complete dotnet-sdk-3.1 golang nodejs zip unzip java-11-openjdk-devel # for driver tests
autoconf # for jemalloc code generation
libtool # for protobuf code generation
)
list() {
echo "$1"
}
check() {
local missing=""
for pkg in $1; do
if [ "$pkg" == git ]; then
if ! which "git" >/dev/null; then
missing="git $missing"
fi
continue
fi
if [ "$pkg" == "PyYAML" ]; then
if ! python3 -c "import yaml" >/dev/null 2>/dev/null; then
missing="$pkg $missing"
fi
continue
fi
if ! yum list installed "$pkg" >/dev/null 2>/dev/null; then
missing="$pkg $missing"
fi
done
if [ "$missing" != "" ]; then
echo "MISSING PACKAGES: $missing"
exit 1
fi
}
install() {
cd "$DIR"
if [ "$EUID" -ne 0 ]; then
echo "Please run as root."
exit 1
fi
# If GitHub Actions runner is installed, append LANG to the environment.
# Python related tests doesn't work the LANG export.
if [ -d "/home/gh/actions-runner" ]; then
echo "LANG=en_US.utf8" >> /home/gh/actions-runner/.env
else
echo "NOTE: export LANG=en_US.utf8"
fi
yum install -y epel-release
yum remove -y ius-release
yum install -y \
https://repo.ius.io/ius-release-el7.rpm
yum update -y
yum install -y wget python3 python3-pip
yum install -y git
for pkg in $1; do
if [ "$pkg" == libipt ]; then
if ! yum list installed libipt >/dev/null 2>/dev/null; then
yum install -y http://repo.okay.com.mx/centos/8/x86_64/release/libipt-1.6.1-8.el8.x86_64.rpm
fi
continue
fi
if [ "$pkg" == libipt-devel ]; then
if ! yum list installed libipt-devel >/dev/null 2>/dev/null; then
yum install -y http://repo.okay.com.mx/centos/8/x86_64/release/libipt-devel-1.6.1-8.el8.x86_64.rpm
fi
continue
fi
if [ "$pkg" == dotnet-sdk-3.1 ]; then
if ! yum list installed dotnet-sdk-3.1 >/dev/null 2>/dev/null; then
wget -nv https://packages.microsoft.com/config/centos/7/packages-microsoft-prod.rpm -O packages-microsoft-prod.rpm
rpm -Uvh https://packages.microsoft.com/config/centos/7/packages-microsoft-prod.rpm
yum update -y
yum install -y dotnet-sdk-3.1
fi
continue
fi
if [ "$pkg" == PyYAML ]; then
if [ -z ${SUDO_USER+x} ]; then # Running as root (e.g. Docker).
pip3 install --user PyYAML
else # Running using sudo.
sudo -H -u "$SUDO_USER" bash -c "pip3 install --user PyYAML"
fi
continue
fi
yum install -y "$pkg"
done
}
deps=$2"[*]"
"$1" "${!deps}"

View File

@@ -1,164 +0,0 @@
#!/bin/bash
set -Eeuo pipefail
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
source "$DIR/../util.sh"
check_operating_system "centos-9"
check_architecture "x86_64"
TOOLCHAIN_BUILD_DEPS=(
coreutils-common gcc gcc-c++ make # generic build tools
wget # used for archive download
gnupg2 # used for archive signature verification
tar gzip bzip2 xz unzip # used for archive unpacking
zlib-devel # zlib library used for all builds
expat-devel xz-devel python3-devel texinfo libbabeltrace-devel # for gdb
readline-devel # for cmake and llvm
libffi-devel libxml2-devel # for llvm
libedit-devel pcre-devel automake bison # for swig
file
openssl-devel
gmp-devel
gperf
diffutils
libipt libipt-devel # intel
patch
)
TOOLCHAIN_RUN_DEPS=(
make # generic build tools
tar gzip bzip2 xz # used for archive unpacking
zlib # zlib library used for all builds
expat xz-libs python3 # for gdb
readline # for cmake and llvm
libffi libxml2 # for llvm
openssl-devel
perl # for openssl
)
MEMGRAPH_BUILD_DEPS=(
git # source code control
make pkgconf-pkg-config # build system
wget # for downloading libs
libuuid-devel java-11-openjdk # required by antlr
readline-devel # for memgraph console
python3-devel # for query modules
openssl-devel
libseccomp-devel
python3 python3-pip python3-virtualenv nmap-ncat # for qa, macro_benchmark and stress tests
#
# IMPORTANT: python3-yaml does NOT exist on CentOS
# Install it manually using `pip3 install PyYAML`
#
PyYAML # Package name here does not correspond to the yum package!
libcurl-devel # mg-requests
rpm-build rpmlint # for RPM package building
doxygen graphviz # source documentation generators
which nodejs golang zip unzip java-11-openjdk-devel # for driver tests
sbcl # for custom Lisp C++ preprocessing
autoconf # for jemalloc code generation
libtool # for protobuf code generation
)
list() {
echo "$1"
}
check() {
local missing=""
for pkg in $1; do
if [ "$pkg" == "PyYAML" ]; then
if ! python3 -c "import yaml" >/dev/null 2>/dev/null; then
missing="$pkg $missing"
fi
continue
fi
if [ "$pkg" == "python3-virtualenv" ]; then
continue
fi
if ! yum list installed "$pkg" >/dev/null 2>/dev/null; then
missing="$pkg $missing"
fi
done
if [ "$missing" != "" ]; then
echo "MISSING PACKAGES: $missing"
exit 1
fi
}
install() {
cd "$DIR"
if [ "$EUID" -ne 0 ]; then
echo "Please run as root."
exit 1
fi
# If GitHub Actions runner is installed, append LANG to the environment.
# Python related tests doesn't work the LANG export.
if [ -d "/home/gh/actions-runner" ]; then
echo "LANG=en_US.utf8" >> /home/gh/actions-runner/.env
else
echo "NOTE: export LANG=en_US.utf8"
fi
yum update -y
yum install -y wget git python3 python3-pip
for pkg in $1; do
# Since there is no support for libipt-devel for CentOS 9 we install
# Fedoras version of same libs, they are the same version but released
# for different OS
# TODO Update when libipt-devel releases for CentOS 9
if [ "$pkg" == libipt ]; then
if ! dnf list installed libipt >/dev/null 2>/dev/null; then
dnf install -y http://repo.okay.com.mx/centos/8/x86_64/release/libipt-1.6.1-8.el8.x86_64.rpm
fi
continue
fi
if [ "$pkg" == libipt-devel ]; then
if ! dnf list installed libipt-devel >/dev/null 2>/dev/null; then
dnf install -y http://repo.okay.com.mx/centos/8/x86_64/release/libipt-devel-1.6.1-8.el8.x86_64.rpm
fi
continue
fi
if [ "$pkg" == libbabeltrace-devel ]; then
if ! dnf list installed libbabeltrace-devel >/dev/null 2>/dev/null; then
dnf install -y http://mirror.stream.centos.org/9-stream/CRB/x86_64/os/Packages/libbabeltrace-devel-1.5.8-10.el9.x86_64.rpm
fi
continue
fi
if [ "$pkg" == sbcl ]; then
if ! dnf list installed cl-asdf >/dev/null 2>/dev/null; then
dnf install -y https://pkgs.dyn.su/el8/base/x86_64/cl-asdf-20101028-18.el8.noarch.rpm
fi
if ! dnf list installed common-lisp-controller >/dev/null 2>/dev/null; then
dnf install -y https://pkgs.dyn.su/el8/base/x86_64/common-lisp-controller-7.4-20.el8.noarch.rpm
fi
if ! dnf list installed sbcl >/dev/null 2>/dev/null; then
dnf install -y https://pkgs.dyn.su/el8/base/x86_64/sbcl-2.0.1-4.el8.x86_64.rpm
fi
continue
fi
if [ "$pkg" == PyYAML ]; then
if [ -z ${SUDO_USER+x} ]; then # Running as root (e.g. Docker).
pip3 install --user PyYAML
else # Running using sudo.
sudo -H -u "$SUDO_USER" bash -c "pip3 install --user PyYAML"
fi
continue
fi
if [ "$pkg" == python3-virtualenv ]; then
if [ -z ${SUDO_USER+x} ]; then # Running as root (e.g. Docker).
pip3 install virtualenv
pip3 install virtualenvwrapper
else # Running using sudo.
sudo -H -u "$SUDO_USER" bash -c "pip3 install virtualenv"
sudo -H -u "$SUDO_USER" bash -c "pip3 install virtualenvwrapper"
fi
continue
fi
yum install -y "$pkg"
done
}
deps=$2"[*]"
"$1" "${!deps}"

View File

@@ -1,104 +0,0 @@
#!/bin/bash
set -Eeuo pipefail
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
source "$DIR/../util.sh"
check_operating_system "debian-10"
check_architecture "x86_64"
TOOLCHAIN_BUILD_DEPS=(
coreutils gcc g++ build-essential make # generic build tools
wget # used for archive download
gnupg # used for archive signature verification
tar gzip bzip2 xz-utils unzip # used for archive unpacking
zlib1g-dev # zlib library used for all builds
libexpat1-dev libipt-dev libbabeltrace-dev liblzma-dev python3-dev texinfo # for gdb
libcurl4-openssl-dev # for cmake
libreadline-dev # for cmake and llvm
libffi-dev libxml2-dev # for llvm
curl # snappy
file # for libunwind
libssl-dev # for libevent
libgmp-dev # for gdb
gperf # for proxygen
git # for fbthrift
libedit-dev libpcre3-dev automake bison # for swig
)
TOOLCHAIN_RUN_DEPS=(
make # generic build tools
tar gzip bzip2 xz-utils # used for archive unpacking
zlib1g # zlib library used for all builds
libexpat1 libipt2 libbabeltrace1 liblzma5 python3 # for gdb
libcurl4 # for cmake
libreadline7 # for cmake and llvm
libffi6 libxml2 # for llvm
libssl-dev # for libevent
)
MEMGRAPH_BUILD_DEPS=(
git # source code control
make pkg-config # build system
curl wget # for downloading libs
uuid-dev default-jre-headless # required by antlr
libreadline-dev # for memgraph console
libpython3-dev python3-dev # for query modules
libssl-dev
libseccomp-dev
netcat # tests are using nc to wait for memgraph
python3 virtualenv python3-virtualenv python3-pip # for qa, macro_benchmark and stress tests
python3-yaml # for the configuration generator
libcurl4-openssl-dev # mg-requests
sbcl # for custom Lisp C++ preprocessing
doxygen graphviz # source documentation generators
mono-runtime mono-mcs zip unzip default-jdk-headless # for driver tests
dotnet-sdk-3.1 golang nodejs npm
autoconf # for jemalloc code generation
libtool # for protobuf code generation
)
list() {
echo "$1"
}
check() {
check_all_dpkg "$1"
}
install() {
cat >/etc/apt/sources.list <<EOF
deb http://deb.debian.org/debian/ buster main non-free contrib
deb-src http://deb.debian.org/debian/ buster main non-free contrib
deb http://deb.debian.org/debian/ buster-updates main contrib non-free
deb-src http://deb.debian.org/debian/ buster-updates main contrib non-free
deb http://security.debian.org/debian-security buster/updates main contrib non-free
deb-src http://security.debian.org/debian-security buster/updates main contrib non-free
EOF
cd "$DIR"
apt --allow-releaseinfo-change update
# If GitHub Actions runner is installed, append LANG to the environment.
# Python related tests doesn't work the LANG export.
if [ -d "/home/gh/actions-runner" ]; then
echo "LANG=en_US.utf8" >> /home/gh/actions-runner/.env
else
echo "NOTE: export LANG=en_US.utf8"
fi
apt install -y wget
for pkg in $1; do
if [ "$pkg" == dotnet-sdk-3.1 ]; then
if ! dpkg -s "$pkg" 2>/dev/null >/dev/null; then
wget -nv https://packages.microsoft.com/config/debian/10/packages-microsoft-prod.deb -O packages-microsoft-prod.deb
dpkg -i packages-microsoft-prod.deb
apt-get update
apt-get install -y apt-transport-https dotnet-sdk-3.1
fi
continue
fi
apt install -y "$pkg"
done
}
deps=$2"[*]"
"$1" "${!deps}"

View File

@@ -1,98 +0,0 @@
#!/bin/bash
set -Eeuo pipefail
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
source "$DIR/../util.sh"
check_operating_system "debian-11"
check_architecture "arm64"
TOOLCHAIN_BUILD_DEPS=(
coreutils gcc g++ build-essential make # generic build tools
wget # used for archive download
gnupg # used for archive signature verification
tar gzip bzip2 xz-utils unzip # used for archive unpacking
zlib1g-dev # zlib library used for all builds
libexpat1-dev liblzma-dev python3-dev texinfo # for gdb
libcurl4-openssl-dev # for cmake
libreadline-dev # for cmake and llvm
libffi-dev libxml2-dev # for llvm
libedit-dev libpcre3-dev automake bison # for swig
curl # snappy
file # for libunwind
libssl-dev # for libevent
libgmp-dev
gperf # for proxygen
git # for fbthrift
)
TOOLCHAIN_RUN_DEPS=(
make # generic build tools
tar gzip bzip2 xz-utils # used for archive unpacking
zlib1g # zlib library used for all builds
libexpat1 liblzma5 python3 # for gdb
libcurl4 # for cmake
file # for CPack
libreadline8 # for cmake and llvm
libffi7 libxml2 # for llvm
libssl-dev # for libevent
)
MEMGRAPH_BUILD_DEPS=(
git # source code control
make pkg-config # build system
curl wget # for downloading libs
uuid-dev default-jre-headless # required by antlr
libreadline-dev # for memgraph console
libpython3-dev python3-dev # for query modules
libssl-dev
libseccomp-dev
netcat # tests are using nc to wait for memgraph
python3 virtualenv python3-virtualenv python3-pip # for qa, macro_benchmark and stress tests
python3-yaml # for the configuration generator
libcurl4-openssl-dev # mg-requests
sbcl # for custom Lisp C++ preprocessing
doxygen graphviz # source documentation generators
mono-runtime mono-mcs zip unzip default-jdk-headless # for driver tests
golang nodejs npm
autoconf # for jemalloc code generation
libtool # for protobuf code generation
)
list() {
echo "$1"
}
check() {
check_all_dpkg "$1"
}
install() {
cat >/etc/apt/sources.list <<EOF
deb http://deb.debian.org/debian bullseye main
deb-src http://deb.debian.org/debian bullseye main
deb http://deb.debian.org/debian-security/ bullseye-security main
deb-src http://deb.debian.org/debian-security/ bullseye-security main
deb http://deb.debian.org/debian bullseye-updates main
deb-src http://deb.debian.org/debian bullseye-updates main
EOF
cd "$DIR"
apt update
# If GitHub Actions runner is installed, append LANG to the environment.
# Python related tests doesn't work the LANG export.
if [ -d "/home/gh/actions-runner" ]; then
echo "LANG=en_US.utf8" >> /home/gh/actions-runner/.env
else
echo "NOTE: export LANG=en_US.utf8"
fi
apt install -y wget
for pkg in $1; do
apt install -y "$pkg"
done
}
deps=$2"[*]"
"$1" "${!deps}"

View File

@@ -1,107 +0,0 @@
#!/bin/bash
set -Eeuo pipefail
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
source "$DIR/../util.sh"
check_operating_system "debian-11"
check_architecture "x86_64"
TOOLCHAIN_BUILD_DEPS=(
coreutils gcc g++ build-essential make # generic build tools
wget # used for archive download
gnupg # used for archive signature verification
tar gzip bzip2 xz-utils unzip # used for archive unpacking
zlib1g-dev # zlib library used for all builds
libexpat1-dev libipt-dev libbabeltrace-dev liblzma-dev python3-dev texinfo # for gdb
libcurl4-openssl-dev # for cmake
libreadline-dev # for cmake and llvm
libffi-dev libxml2-dev # for llvm
libedit-dev libpcre3-dev automake bison # for swig
curl # snappy
file # for libunwind
libssl-dev # for libevent
libgmp-dev
gperf # for proxygen
git # for fbthrift
)
TOOLCHAIN_RUN_DEPS=(
make # generic build tools
tar gzip bzip2 xz-utils # used for archive unpacking
zlib1g # zlib library used for all builds
libexpat1 libipt2 libbabeltrace1 liblzma5 python3 # for gdb
libcurl4 # for cmake
file # for CPack
libreadline8 # for cmake and llvm
libffi7 libxml2 # for llvm
libssl-dev # for libevent
)
MEMGRAPH_BUILD_DEPS=(
git # source code control
make pkg-config # build system
curl wget # for downloading libs
uuid-dev default-jre-headless # required by antlr
libreadline-dev # for memgraph console
libpython3-dev python3-dev # for query modules
libssl-dev
libseccomp-dev
netcat # tests are using nc to wait for memgraph
python3 virtualenv python3-virtualenv python3-pip # for qa, macro_benchmark and stress tests
python3-yaml # for the configuration generator
libcurl4-openssl-dev # mg-requests
sbcl # for custom Lisp C++ preprocessing
doxygen graphviz # source documentation generators
mono-runtime mono-mcs zip unzip default-jdk-headless # for driver tests
dotnet-sdk-3.1 golang nodejs npm
autoconf # for jemalloc code generation
libtool # for protobuf code generation
)
list() {
echo "$1"
}
check() {
check_all_dpkg "$1"
}
install() {
cat >/etc/apt/sources.list <<EOF
deb http://deb.debian.org/debian bullseye main
deb-src http://deb.debian.org/debian bullseye main
deb http://deb.debian.org/debian-security/ bullseye-security main
deb-src http://deb.debian.org/debian-security/ bullseye-security main
deb http://deb.debian.org/debian bullseye-updates main
deb-src http://deb.debian.org/debian bullseye-updates main
EOF
cd "$DIR"
apt update
# If GitHub Actions runner is installed, append LANG to the environment.
# Python related tests doesn't work the LANG export.
if [ -d "/home/gh/actions-runner" ]; then
echo "LANG=en_US.utf8" >> /home/gh/actions-runner/.env
else
echo "NOTE: export LANG=en_US.utf8"
fi
apt install -y wget
for pkg in $1; do
if [ "$pkg" == dotnet-sdk-3.1 ]; then
if ! dpkg -s "$pkg" 2>/dev/null >/dev/null; then
wget -nv https://packages.microsoft.com/config/debian/10/packages-microsoft-prod.deb -O packages-microsoft-prod.deb
dpkg -i packages-microsoft-prod.deb
apt-get update
apt-get install -y apt-transport-https dotnet-sdk-3.1
fi
continue
fi
apt install -y "$pkg"
done
}
deps=$2"[*]"
"$1" "${!deps}"

View File

@@ -1,38 +0,0 @@
#!/bin/bash
set -Eeuo pipefail
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
source "$DIR/../util.sh"
check_operating_system "todo-os-name"
TOOLCHAIN_BUILD_DEPS=(
pkg
)
TOOLCHAIN_RUN_DEPS=(
pkg
)
MEMGRAPH_BUILD_DEPS=(
pkg
)
list() {
echo "$1"
}
check() {
echo "TODO: Implement ${FUNCNAME[0]}."
exit 1
}
install() {
echo "TODO: Implement ${FUNCNAME[0]}."
exit 1
}
# http://ahmed.amayem.com/bash-indirect-expansion-exploration
deps=$2"[*]"
"$1" "${!deps}"

View File

@@ -1,74 +0,0 @@
#!/bin/bash
set -Eeuo pipefail
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
source "$DIR/../util.sh"
check_operating_system "ubuntu-18.04"
check_architecture "x86_64"
TOOLCHAIN_BUILD_DEPS=(
coreutils gcc g++ build-essential make # generic build tools
wget # archive download
gnupg # archive signature verification
tar gzip bzip2 xz-utils unzip # archive unpacking
zlib1g-dev # zlib library used for all builds
libexpat1-dev libipt-dev libbabeltrace-dev liblzma-dev python3-dev # gdb
texinfo # gdb
libcurl4-openssl-dev # cmake
libreadline-dev # cmake and llvm
libffi-dev libxml2-dev # llvm
curl # snappy
file
git # for thrift
libgmp-dev # for gdb
gperf # for proxygen
libssl-dev
libedit-dev libpcre3-dev automake bison # swig
)
TOOLCHAIN_RUN_DEPS=(
make # generic build tools
tar gzip bzip2 xz-utils # used for archive unpacking
zlib1g # zlib library used for all builds
libexpat1 libipt1 libbabeltrace1 liblzma5 python3 # for gdb
libcurl4 # for cmake
libreadline7 # for cmake and llvm
libffi6 libxml2 # for llvm
libssl-dev # for libevent
)
MEMGRAPH_BUILD_DEPS=(
git # source code control
make pkg-config # build system
curl wget # downloading libs
uuid-dev default-jre-headless # required by antlr
libreadline-dev # memgraph console
libpython3-dev python3-dev # for query modules
libssl-dev
libseccomp-dev
python3 virtualenv python3-virtualenv python3-pip # qa, macro bench and stress tests
python3-yaml # the configuration generator
libcurl4-openssl-dev # mg-requests
sbcl # custom Lisp C++ preprocessing
doxygen graphviz # source documentation generators
mono-runtime mono-mcs nodejs zip unzip default-jdk-headless # driver tests
autoconf # for jemalloc code generation
libtool # for protobuf code generation
)
list() {
echo "$1"
}
check() {
check_all_dpkg "$1"
}
install() {
apt install -y $1
}
deps=$2"[*]"
"$1" "${!deps}"

View File

@@ -1,96 +0,0 @@
#!/bin/bash
set -Eeuo pipefail
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
source "$DIR/../util.sh"
check_operating_system "ubuntu-20.04"
check_architecture "x86_64"
TOOLCHAIN_BUILD_DEPS=(
coreutils gcc g++ build-essential make # generic build tools
wget # used for archive download
gnupg # used for archive signature verification
tar gzip bzip2 xz-utils unzip # used for archive unpacking
zlib1g-dev # zlib library used for all builds
libexpat1-dev libipt-dev libbabeltrace-dev liblzma-dev python3-dev texinfo # for gdb
libcurl4-openssl-dev # for cmake
libreadline-dev # for cmake and llvm
libffi-dev libxml2-dev # for llvm
curl # snappy
file
git # for thrift
libgmp-dev # for gdb
gperf # for proxygen
libssl-dev
libedit-dev libpcre3-dev automake bison # for swig
)
TOOLCHAIN_RUN_DEPS=(
make # generic build tools
tar gzip bzip2 xz-utils # used for archive unpacking
zlib1g # zlib library used for all builds
libexpat1 libipt2 libbabeltrace1 liblzma5 python3 # for gdb
libcurl4 # for cmake
libreadline8 # for cmake and llvm
libffi7 libxml2 # for llvm
libssl-dev # for libevent
)
MEMGRAPH_BUILD_DEPS=(
git # source code control
make pkg-config # build system
curl wget # for downloading libs
uuid-dev default-jre-headless # required by antlr
libreadline-dev # for memgraph console
libpython3-dev python3-dev # for query modules
libssl-dev
libseccomp-dev
netcat # tests are using nc to wait for memgraph
python3 python3-virtualenv python3-pip # for qa, macro_benchmark and stress tests
python3-yaml # for the configuration generator
libcurl4-openssl-dev # mg-requests
sbcl # for custom Lisp C++ preprocessing
doxygen graphviz # source documentation generators
mono-runtime mono-mcs zip unzip default-jdk-headless # for driver tests
dotnet-sdk-3.1 golang nodejs npm
autoconf # for jemalloc code generation
libtool # for protobuf code generation
)
list() {
echo "$1"
}
check() {
check_all_dpkg "$1"
}
install() {
cd "$DIR"
apt update
# If GitHub Actions runner is installed, append LANG to the environment.
# Python related tests doesn't work the LANG export.
if [ -d "/home/gh/actions-runner" ]; then
echo "LANG=en_US.utf8" >> /home/gh/actions-runner/.env
else
echo "NOTE: export LANG=en_US.utf8"
fi
apt install -y wget
for pkg in $1; do
if [ "$pkg" == dotnet-sdk-3.1 ]; then
if ! dpkg -s dotnet-sdk-3.1 2>/dev/null >/dev/null; then
wget -nv https://packages.microsoft.com/config/ubuntu/20.04/packages-microsoft-prod.deb -O packages-microsoft-prod.deb
dpkg -i packages-microsoft-prod.deb
apt-get update
apt-get install -y apt-transport-https dotnet-sdk-3.1
fi
continue
fi
apt install -y "$pkg"
done
}
deps=$2"[*]"
"$1" "${!deps}"

View File

@@ -1,96 +0,0 @@
#!/bin/bash
set -Eeuo pipefail
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
source "$DIR/../util.sh"
check_operating_system "ubuntu-22.04"
check_architecture "x86_64"
TOOLCHAIN_BUILD_DEPS=(
coreutils gcc g++ build-essential make # generic build tools
wget # used for archive download
gnupg # used for archive signature verification
tar gzip bzip2 xz-utils unzip # used for archive unpacking
zlib1g-dev # zlib library used for all builds
libexpat1-dev libipt-dev libbabeltrace-dev liblzma-dev python3-dev texinfo # for gdb
libcurl4-openssl-dev # for cmake
libreadline-dev # for cmake and llvm
libffi-dev libxml2-dev # for llvm
curl # snappy
file
git # for thrift
libgmp-dev # for gdb
gperf # for proxygen
libssl-dev
libedit-dev libpcre3-dev automake bison # for swig
)
TOOLCHAIN_RUN_DEPS=(
make # generic build tools
tar gzip bzip2 xz-utils # used for archive unpacking
zlib1g # zlib library used for all builds
libexpat1 libipt2 libbabeltrace1 liblzma5 python3 # for gdb
libcurl4 # for cmake
libreadline8 # for cmake and llvm
libffi7 libxml2 # for llvm
libssl-dev # for libevent
)
MEMGRAPH_BUILD_DEPS=(
git # source code control
make pkg-config # build system
curl wget # for downloading libs
uuid-dev default-jre-headless # required by antlr
libreadline-dev # for memgraph console
libpython3-dev python3-dev # for query modules
libssl-dev
libseccomp-dev
netcat # tests are using nc to wait for memgraph
python3 python3-virtualenv python3-pip # for qa, macro_benchmark and stress tests
python3-yaml # for the configuration generator
libcurl4-openssl-dev # mg-requests
sbcl # for custom Lisp C++ preprocessing
doxygen graphviz # source documentation generators
mono-runtime mono-mcs zip unzip default-jdk-headless # for driver tests
dotnet-sdk-6.0 golang nodejs npm
autoconf # for jemalloc code generation
libtool # for protobuf code generation
)
list() {
echo "$1"
}
check() {
check_all_dpkg "$1"
}
install() {
cd "$DIR"
apt update
# If GitHub Actions runner is installed, append LANG to the environment.
# Python related tests doesn't work the LANG export.
if [ -d "/home/gh/actions-runner" ]; then
echo "LANG=en_US.utf8" >> /home/gh/actions-runner/.env
else
echo "NOTE: export LANG=en_US.utf8"
fi
apt install -y wget
for pkg in $1; do
if [ "$pkg" == dotnet-sdk-6.0 ]; then
if ! dpkg -s dotnet-sdk-6.0 2>/dev/null >/dev/null; then
wget -nv https://packages.microsoft.com/config/ubuntu/22.04/packages-microsoft-prod.deb -O packages-microsoft-prod.deb
dpkg -i packages-microsoft-prod.deb
apt-get update
apt-get install -y apt-transport-https dotnet-sdk-6.0
fi
continue
fi
apt install -y "$pkg"
done
}
deps=$2"[*]"
"$1" "${!deps}"

View File

@@ -4,36 +4,88 @@
pushd () { command pushd "$@" > /dev/null; }
popd () { command popd "$@" > /dev/null; }
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
CPUS=$( grep -c processor < /proc/cpuinfo )
CPUS=$( cat /proc/cpuinfo | grep processor | wc -l )
cd "$DIR"
source "$DIR/../util.sh"
DISTRO="$(operating_system)"
# toolchain version
TOOLCHAIN_VERSION=2
TOOLCHAIN_VERSION=1
# package versions used
GCC_VERSION=10.2.0
BINUTILS_VERSION=2.35.1
case "$DISTRO" in
centos-7) # because GDB >= 9 does NOT compile with readline6.
GDB_VERSION=8.3
;;
*)
GDB_VERSION=10.1
;;
esac
CMAKE_VERSION=3.18.4
CPPCHECK_VERSION=2.2
LLVM_VERSION=11.0.0
SWIG_VERSION=4.0.2 # used only for LLVM compilation
GCC_VERSION=8.3.0
BINUTILS_VERSION=2.32
GDB_VERSION=8.2.1
CMAKE_VERSION=3.14.2
CPPCHECK_VERSION=1.87
LLVM_VERSION=8.0.0
SWIG_VERSION=3.0.12 # used only for LLVM compilation
# Check for the dependencies.
echo "ALL BUILD PACKAGES: $($DIR/../os/$DISTRO.sh list TOOLCHAIN_BUILD_DEPS)"
$DIR/../os/$DISTRO.sh check TOOLCHAIN_BUILD_DEPS
echo "ALL RUN PACKAGES: $($DIR/../os/$DISTRO.sh list TOOLCHAIN_RUN_DEPS)"
$DIR/../os/$DISTRO.sh check TOOLCHAIN_RUN_DEPS
# check for installed dependencies
DISTRO="$( egrep '^(VERSION_)?ID=' /etc/os-release | sort | cut -d '=' -f 2- | sed 's/"//g' | paste -s -d '-' )"
if [ "$DISTRO" == "debian-9" ] || [ "$DISTRO" == "ubuntu-18.04" ]; then
DEPS_MANAGER=apt-get
DEPS_COMPILE=(
coreutils gcc g++ build-essential make # generic build tools
wget # used for archive download
gnupg # used for archive signature verification
tar gzip bzip2 xz-utils # used for archive unpacking
zlib1g-dev # zlib library used for all builds
libexpat1-dev libipt-dev libbabeltrace-dev liblzma-dev python3-dev texinfo # for gdb
libreadline-dev # for cmake and llvm
libffi-dev libxml2-dev # for llvm
libedit-dev libpcre3-dev automake bison # for swig
)
DEPS_RUN=(
make # generic build tools
tar gzip bzip2 xz-utils # used for archive unpacking
zlib1g # zlib library used for all builds
libexpat1 libipt1 libbabeltrace1 liblzma5 python3 # for gdb
libreadline7 # for cmake and llvm
libffi6 libxml2 # for llvm
)
elif [ "$DISTRO" == "centos-7" ]; then
DEPS_MANAGER=yum
DEPS_COMPILE=(
coreutils gcc gcc-c++ make # generic build tools
wget # used for archive download
gnupg2 # used for archive signature verification
tar gzip bzip2 xz # used for archive unpacking
zlib-devel # zlib library used for all builds
expat-devel libipt-devel libbabeltrace-devel xz-devel python36-devel texinfo # for gdb
readline-devel # for cmake and llvm
libffi-devel libxml2-devel # for llvm
libedit-devel pcre-devel automake bison # for swig
)
DEPS_RUN=(
make # generic build tools
tar gzip bzip2 xz # used for archive unpacking
zlib # zlib library used for all builds
expat libipt libbabeltrace xz-libs python36 # for gdb
readline # for cmake and llvm
libffi libxml2 # for llvm
)
else
echo "Unknown distribution: $DISTRO!"
exit 1
fi
missing=""
for dep in ${DEPS_COMPILE[@]}; do
if [ "$DEPS_MANAGER" == "apt-get" ]; then
if ! dpkg -s $dep >/dev/null 2>/dev/null; then
missing="$dep $missing"
fi
elif [ "$DEPS_MANAGER" == "yum" ]; then
if ! yum list installed $dep >/dev/null 2>/dev/null; then
missing="$dep $missing"
fi
else
echo "Invalid package manager: $DEPS_MANAGER!"
exit 1
fi
done
if [ "$missing" != "" ]; then
echo "Missing dependencies: $missing"
exit 1
fi
# check installation directory
NAME=toolchain-v$TOOLCHAIN_VERSION
@@ -84,14 +136,10 @@ if [ ! -f cppcheck-$CPPCHECK_VERSION.tar.gz ]; then
wget https://github.com/danmar/cppcheck/archive/$CPPCHECK_VERSION.tar.gz -O cppcheck-$CPPCHECK_VERSION.tar.gz
fi
if [ ! -f llvm-$LLVM_VERSION.src.tar.xz ]; then
wget https://github.com/llvm/llvm-project/releases/download/llvmorg-$LLVM_VERSION/llvm-$LLVM_VERSION.src.tar.xz
wget https://github.com/llvm/llvm-project/releases/download/llvmorg-$LLVM_VERSION/clang-$LLVM_VERSION.src.tar.xz
wget https://github.com/llvm/llvm-project/releases/download/llvmorg-$LLVM_VERSION/lld-$LLVM_VERSION.src.tar.xz
wget https://github.com/llvm/llvm-project/releases/download/llvmorg-$LLVM_VERSION/clang-tools-extra-$LLVM_VERSION.src.tar.xz
wget https://github.com/llvm/llvm-project/releases/download/llvmorg-$LLVM_VERSION/compiler-rt-$LLVM_VERSION.src.tar.xz
fi
if [ ! -f pahole-gdb-master.zip ]; then
wget https://github.com/PhilArmstrong/pahole-gdb/archive/master.zip -O pahole-gdb-master.zip
wget http://releases.llvm.org/$LLVM_VERSION/llvm-$LLVM_VERSION.src.tar.xz
wget http://releases.llvm.org/$LLVM_VERSION/cfe-$LLVM_VERSION.src.tar.xz
wget http://releases.llvm.org/$LLVM_VERSION/lld-$LLVM_VERSION.src.tar.xz
wget http://releases.llvm.org/$LLVM_VERSION/clang-tools-extra-$LLVM_VERSION.src.tar.xz
fi
# verify all archives
@@ -108,7 +156,7 @@ if [ ! -f gcc-$GCC_VERSION.tar.gz.sig ]; then
wget https://ftp.gnu.org/gnu/gcc/gcc-$GCC_VERSION/gcc-$GCC_VERSION.tar.gz.sig
fi
# list of valid gcc gnupg keys: https://gcc.gnu.org/mirrors.html
$GPG --keyserver $KEYSERVER --recv-keys 0x3AB00996FC26A641
$GPG --keyserver $KEYSERVER --recv-keys 0xC3C45C06
$GPG --verify gcc-$GCC_VERSION.tar.gz.sig gcc-$GCC_VERSION.tar.gz
# verify binutils
if [ ! -f binutils-$BINUTILS_VERSION.tar.gz.sig ]; then
@@ -126,28 +174,23 @@ $GPG --verify gdb-$GDB_VERSION.tar.gz.sig gdb-$GDB_VERSION.tar.gz
if [ ! -f cmake-$CMAKE_VERSION-SHA-256.txt ] || [ ! -f cmake-$CMAKE_VERSION-SHA-256.txt.asc ]; then
wget https://github.com/Kitware/CMake/releases/download/v$CMAKE_VERSION/cmake-$CMAKE_VERSION-SHA-256.txt
wget https://github.com/Kitware/CMake/releases/download/v$CMAKE_VERSION/cmake-$CMAKE_VERSION-SHA-256.txt.asc
# Because CentOS 7 doesn't have the `--ignore-missing` flag for `sha256sum`
# we filter out the missing files from the sums here manually.
cat cmake-$CMAKE_VERSION-SHA-256.txt | grep "cmake-$CMAKE_VERSION.tar.gz" > cmake-$CMAKE_VERSION-SHA-256-filtered.txt
fi
$GPG --keyserver $KEYSERVER --recv-keys 0xC6C265324BBEBDC350B513D02D2CEF1034921684
sha256sum -c cmake-$CMAKE_VERSION-SHA-256-filtered.txt
$GPG --keyserver $KEYSERVER --recv-keys 0x7BFB4EDA
sha256sum --ignore-missing -c cmake-$CMAKE_VERSION-SHA-256.txt
$GPG --verify cmake-$CMAKE_VERSION-SHA-256.txt.asc cmake-$CMAKE_VERSION-SHA-256.txt
# verify llvm, cfe, lld, clang-tools-extra
if [ ! -f llvm-$LLVM_VERSION.src.tar.xz.sig ]; then
wget https://github.com/llvm/llvm-project/releases/download/llvmorg-$LLVM_VERSION/llvm-$LLVM_VERSION.src.tar.xz.sig
wget https://github.com/llvm/llvm-project/releases/download/llvmorg-$LLVM_VERSION/clang-$LLVM_VERSION.src.tar.xz.sig
wget https://github.com/llvm/llvm-project/releases/download/llvmorg-$LLVM_VERSION/lld-$LLVM_VERSION.src.tar.xz.sig
wget https://github.com/llvm/llvm-project/releases/download/llvmorg-$LLVM_VERSION/clang-tools-extra-$LLVM_VERSION.src.tar.xz.sig
wget https://github.com/llvm/llvm-project/releases/download/llvmorg-$LLVM_VERSION/compiler-rt-$LLVM_VERSION.src.tar.xz.sig
wget http://releases.llvm.org/$LLVM_VERSION/llvm-$LLVM_VERSION.src.tar.xz.sig
wget http://releases.llvm.org/$LLVM_VERSION/cfe-$LLVM_VERSION.src.tar.xz.sig
wget http://releases.llvm.org/$LLVM_VERSION/lld-$LLVM_VERSION.src.tar.xz.sig
wget http://releases.llvm.org/$LLVM_VERSION/clang-tools-extra-$LLVM_VERSION.src.tar.xz.sig
fi
# list of valid llvm gnupg keys: https://releases.llvm.org/download.html
$GPG --keyserver $KEYSERVER --recv-keys 0x345AD05D
$GPG --verify llvm-$LLVM_VERSION.src.tar.xz.sig llvm-$LLVM_VERSION.src.tar.xz
$GPG --verify clang-$LLVM_VERSION.src.tar.xz.sig clang-$LLVM_VERSION.src.tar.xz
$GPG --verify cfe-$LLVM_VERSION.src.tar.xz.sig cfe-$LLVM_VERSION.src.tar.xz
$GPG --verify lld-$LLVM_VERSION.src.tar.xz.sig lld-$LLVM_VERSION.src.tar.xz
$GPG --verify clang-tools-extra-$LLVM_VERSION.src.tar.xz.sig clang-tools-extra-$LLVM_VERSION.src.tar.xz
$GPG --verify compiler-rt-$LLVM_VERSION.src.tar.xz.sig compiler-rt-$LLVM_VERSION.src.tar.xz
popd
# create build directory
@@ -266,7 +309,6 @@ if [ ! -f $PREFIX/bin/gdb ]; then
--disable-gdbtk \
--disable-shared \
--without-guile \
--with-system-gdbinit=$PREFIX/etc/gdb/gdbinit \
--with-system-readline \
--with-expat \
--with-system-zlib \
@@ -280,38 +322,6 @@ if [ ! -f $PREFIX/bin/gdb ]; then
popd && popd
fi
# install pahole
if [ ! -d $PREFIX/share/pahole-gdb ]; then
unzip ../archives/pahole-gdb-master.zip
mv pahole-gdb-master $PREFIX/share/pahole-gdb
fi
# setup system gdbinit
if [ ! -f $PREFIX/etc/gdb/gdbinit ]; then
mkdir -p $PREFIX/etc/gdb
cat >$PREFIX/etc/gdb/gdbinit <<EOF
# improve formatting
set print pretty on
set print object on
set print static-members on
set print vtbl on
set print demangle on
set demangle-style gnu-v3
set print sevenbit-strings off
# load libstdc++ pretty printers
add-auto-load-scripts-directory $PREFIX/lib64
add-auto-load-safe-path $PREFIX
# load pahole
python
sys.path.insert(0, "$PREFIX/share/pahole-gdb")
import offsets
import pahole
end
EOF
fi
# compile cmake
if [ ! -f $PREFIX/bin/cmake ]; then
if [ -d cmake-$CMAKE_VERSION ]; then
@@ -330,8 +340,7 @@ if [ ! -f $PREFIX/bin/cmake ]; then
../bootstrap \
--prefix=$PREFIX \
--init=../build-flags.cmake \
--parallel=$CPUS \
--system-curl
--parallel=$CPUS
make -j$CPUS
# make test # run test suite
make install
@@ -349,14 +358,12 @@ if [ ! -f $PREFIX/bin/cppcheck ]; then
CC=gcc \
CXX=g++ \
PREFIX=$PREFIX \
FILESDIR=$PREFIX/share/cppcheck \
CFGDIR=$PREFIX/share/cppcheck/cfg \
make -j$CPUS
env \
CC=gcc \
CXX=g++ \
PREFIX=$PREFIX \
FILESDIR=$PREFIX/share/cppcheck \
CFGDIR=$PREFIX/share/cppcheck/cfg \
make install
popd
@@ -385,20 +392,19 @@ if [ ! -f $PREFIX/bin/clang ]; then
fi
tar -xvf ../archives/llvm-$LLVM_VERSION.src.tar.xz
mv llvm-$LLVM_VERSION.src llvm-$LLVM_VERSION
tar -xvf ../archives/clang-$LLVM_VERSION.src.tar.xz
mv clang-$LLVM_VERSION.src llvm-$LLVM_VERSION/tools/clang
tar -xvf ../archives/cfe-$LLVM_VERSION.src.tar.xz
mv cfe-$LLVM_VERSION.src llvm-$LLVM_VERSION/tools/clang
tar -xvf ../archives/lld-$LLVM_VERSION.src.tar.xz
mv lld-$LLVM_VERSION.src/ llvm-$LLVM_VERSION/tools/lld
tar -xvf ../archives/clang-tools-extra-$LLVM_VERSION.src.tar.xz
mv clang-tools-extra-$LLVM_VERSION.src/ llvm-$LLVM_VERSION/tools/clang/tools/extra
tar -xvf ../archives/compiler-rt-$LLVM_VERSION.src.tar.xz
mv compiler-rt-$LLVM_VERSION.src/ llvm-$LLVM_VERSION/projects/compiler-rt
pushd llvm-$LLVM_VERSION
mkdir build && pushd build
# activate swig
export PATH=$DIR/build/swig-$SWIG_VERSION/install/bin:$PATH
# influenced by: https://buildd.debian.org/status/fetch.php?pkg=llvm-toolchain-7&arch=amd64&ver=1%3A7.0.1%7E%2Brc2-1%7Eexp1&stamp=1541506173&raw=0
cmake .. \
-DGCC_INSTALL_PREFIX=$PREFIX \
-DCMAKE_C_COMPILER=$PREFIX/bin/gcc \
-DCMAKE_CXX_COMPILER=$PREFIX/bin/g++ \
-DCMAKE_CXX_LINK_FLAGS="-L$PREFIX/lib64 -Wl,-rpath,$PREFIX/lib64" \
@@ -414,7 +420,9 @@ if [ ! -f $PREFIX/bin/clang ]; then
-DLLVM_ENABLE_RTTI=ON \
-DLLVM_ENABLE_FFI=ON \
-DLLVM_BINUTILS_INCDIR=$PREFIX/include/ \
-DLLVM_USE_PERF=yes
-DLLVM_USE_PERF=yes \
-DLIBCLANG_LIBRARY_VERSION=1 \
-DCLANG_ENABLE_BOOTSTRAP=ON
make -j$CPUS
make -j$CPUS check-clang # run clang test suite
make -j$CPUS check-lld # run lld test suite
@@ -434,7 +442,7 @@ if [ ! -f $PREFIX/README.md ]; then
- GDB $GDB_VERSION
- CMake $CMAKE_VERSION
- Cppcheck $CPPCHECK_VERSION
- LLVM (Clang, LLD, compiler-rt, Clang tools extra) $LLVM_VERSION
- LLVM (Clang, LLD, Clang tools extra) $LLVM_VERSION
## Required libraries
@@ -442,7 +450,7 @@ In order to be able to run all of these tools you should install the following
packages:
\`\`\`
$($DIR/../os/$DISTRO.sh list TOOLCHAIN_RUN_DEPS)
$DEPS_MANAGER install ${DEPS_RUN[@]}
\`\`\`
## Usage
@@ -480,7 +488,7 @@ export ORIG_LD_LIBRARY_PATH=\$LD_LIBRARY_PATH
# activate new environment
export PATH=$PREFIX/bin:\$PATH
export PS1="($NAME) \$PS1"
export PS1="(TOOLCHAIN) \$PS1"
export LD_LIBRARY_PATH=$PREFIX/lib:$PREFIX/lib64
# disable root

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