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5f5a11525c
Mainly because it has better support for installing the packages from different python versions. It also has better dependency resolver than Pipenv. And supports modern standard for python dependency management. This includes usage of pyproject.toml for project specific configuration instead of per tool conf files. See following links for details: https://pip.pypa.io/en/stable/reference/build-system/pyproject-toml/ https://www.python.org/dev/peps/pep-0518/
100 lines
4.2 KiB
YAML
100 lines
4.2 KiB
YAML
name: benchmarking
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on:
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# uncomment to run on push for debugging your PR
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# push:
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# branches: [ mybranch ]
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schedule:
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# * is a special character in YAML so you have to quote this string
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# ┌───────────── minute (0 - 59)
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# │ ┌───────────── hour (0 - 23)
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# │ │ ┌───────────── day of the month (1 - 31)
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# │ │ │ ┌───────────── month (1 - 12 or JAN-DEC)
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# │ │ │ │ ┌───────────── day of the week (0 - 6 or SUN-SAT)
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- cron: '36 7 * * *' # run once a day, timezone is utc
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workflow_dispatch: # adds ability to run this manually
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jobs:
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bench:
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# this workflow runs on self hosteed runner
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# it's environment is quite different from usual guthub runner
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# probably the most important difference is that it doesnt start from clean workspace each time
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# e g if you install system packages they are not cleaned up since you install them directly in host machine
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# not a container or something
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# See documentation for more info: https://docs.github.com/en/actions/hosting-your-own-runners/about-self-hosted-runners
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runs-on: [self-hosted, zenith-benchmarker]
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env:
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PG_BIN: "/usr/pgsql-13/bin"
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steps:
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- name: Checkout zenith repo
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uses: actions/checkout@v2
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# actions/setup-python@v2 is not working correctly on self-hosted runners
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# see https://github.com/actions/setup-python/issues/162
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# and probably https://github.com/actions/setup-python/issues/162#issuecomment-865387976 in particular
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# so the simplest solution to me is to use already installed system python and spin virtualenvs for job runs.
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# there is Python 3.7.10 already installed on the machine so use it to install poetry and then use poetry's virtuealenvs
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- name: Install poetry & deps
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run: |
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python3 -m pip install --upgrade poetry wheel
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# since pip/poetry caches are reused there shouldn't be any troubles with install every time
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poetry install
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- name: Show versions
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run: |
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echo Python
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python3 --version
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poetry run python3 --version
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echo Pipenv
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poetry --version
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echo Pgbench
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$PG_BIN/pgbench --version
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# FIXME cluster setup is skipped due to various changes in console API
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# for now pre created cluster is used. When API gain some stability
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# after massive changes dynamic cluster setup will be revived.
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# So use pre created cluster. It needs to be started manually, but stop is automatic after 5 minutes of inactivity
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- name: Setup cluster
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env:
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BENCHMARK_CONNSTR: "${{ secrets.BENCHMARK_STAGING_CONNSTR }}"
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shell: bash
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run: |
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set -e
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echo "Starting cluster"
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# wake up the cluster
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$PG_BIN/psql $BENCHMARK_CONNSTR -c "SELECT 1"
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- name: Run benchmark
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# pgbench is installed system wide from official repo
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# https://download.postgresql.org/pub/repos/yum/13/redhat/rhel-7-x86_64/
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# via
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# sudo tee /etc/yum.repos.d/pgdg.repo<<EOF
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# [pgdg13]
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# name=PostgreSQL 13 for RHEL/CentOS 7 - x86_64
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# baseurl=https://download.postgresql.org/pub/repos/yum/13/redhat/rhel-7-x86_64/
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# enabled=1
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# gpgcheck=0
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# EOF
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# sudo yum makecache
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# sudo yum install postgresql13-contrib
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# actual binaries are located in /usr/pgsql-13/bin/
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env:
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TEST_PG_BENCH_TRANSACTIONS_MATRIX: "5000,10000,20000"
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TEST_PG_BENCH_SCALES_MATRIX: "10,15"
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PLATFORM: "zenith-staging"
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BENCHMARK_CONNSTR: "${{ secrets.BENCHMARK_STAGING_CONNSTR }}"
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REMOTE_ENV: "1" # indicate to test harness that we do not have zenith binaries locally
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run: |
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mkdir -p perf-report-staging
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./scripts/pytest test_runner/performance/ -v -m "remote_cluster" --skip-interfering-proc-check --out-dir perf-report-staging
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- name: Submit result
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env:
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VIP_VAP_ACCESS_TOKEN: "${{ secrets.VIP_VAP_ACCESS_TOKEN }}"
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run: |
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REPORT_FROM=$(realpath perf-report-staging) REPORT_TO=staging scripts/generate_and_push_perf_report.sh
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