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Running tox using self hosted runner. maxmemory check fix on client-runner (#189)
* tox using self hosted runner. maxmemory check fix * Updated tox workflow description * Updated badge
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‎.github/workflows/tox-self-hosted.yml‎

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name: Run tox on Ubuntu 22.04
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on:
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push:
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paths-ignore:
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- 'docs/**'
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- '**/*.rst'
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- '**/*.md'
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branches:
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- master
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- main
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- '[0-9].[0-9]'
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pull_request:
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branches:
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- master
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- main
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jobs:
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start-runner:
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name: Start self-hosted EC2 runner
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runs-on: ubuntu-latest
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outputs:
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label: ${{ steps.start-ec2-runner.outputs.label }}
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ec2-instance-id: ${{ steps.start-ec2-runner.outputs.ec2-instance-id }}
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steps:
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- name: Configure AWS credentials
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uses: aws-actions/configure-aws-credentials@v1
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with:
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aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
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aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
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aws-region: ${{ secrets.AWS_REGION }}
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- name: Start EC2 runner
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id: start-ec2-runner
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uses: machulav/ec2-github-runner@v2
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with:
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mode: start
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github-token: ${{ secrets.GH_PERSONAL_ACCESS_TOKEN }}
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# Ubuntu 22.04 region AMI
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ec2-image-id: ami-050b6fdb9f05d7b32
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ec2-instance-type: c5.9xlarge
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subnet-id: ${{ secrets.AWS_EC2_SUBNET_ID }}
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security-group-id: ${{ secrets.AWS_EC2_SG_ID }}
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tox:
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name: Run tox on the runner
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needs: start-runner # required to start the main job when the runner is ready
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runs-on: ${{ needs.start-runner.outputs.label }} # run the job on the newly created runner
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steps:
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- name: checkout
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uses: actions/checkout@v3
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- name: Print runner info
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run: |
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printf "Runner lscpu:\n$(lscpu)\n"
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printf "Runner lsmem:\n$(lsmem)\n"
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printf "Runner nproc:\n$(nproc)\n"
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printf "Runner uname:\n$(uname -a)\n"
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- name: Install benchmark dependencies
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run: |
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sudo apt update -y
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sudo apt install python3-pip -y
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sudo pip3 install --upgrade pip
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sudo apt install docker.io -y
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pip3 install -r dev_requirements.txt
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- name: Install Poetry
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run: |
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curl -sSL https://install.python-poetry.org | python3 -
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- name: Install Dev requirements
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run: |
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pip install -U setuptools wheel
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pip install -r dev_requirements.txt
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- name: Run tox
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run: |
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tox
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- name: Upload coverage to Codecov
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uses: codecov/codecov-action@v2
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with:
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token: ${{secrets.CODECOV_TOKEN}}
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fail_ci_if_error: true
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stop-runner:
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name: Stop self-hosted EC2 runner
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needs:
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- start-runner # required to get output from the start-runner job
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- tox # required to wait when the main job is done
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runs-on: ubuntu-latest
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if: ${{ always() }} # required to stop the runner even if the error happened in the previous jobs
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steps:
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- name: Configure AWS credentials
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uses: aws-actions/configure-aws-credentials@v1
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with:
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aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
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aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
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aws-region: ${{ secrets.AWS_REGION }}
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- name: Stop EC2 runner
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uses: machulav/ec2-github-runner@v2
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with:
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mode: stop
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github-token: ${{ secrets.GH_PERSONAL_ACCESS_TOKEN }}
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label: ${{ needs.start-runner.outputs.label }}
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ec2-instance-id: ${{ needs.start-runner.outputs.ec2-instance-id }}

‎.github/workflows/tox.yml‎

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‎Readme.md‎

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[![codecov](https://codecov.io/gh/redis/redis-benchmarks-specification/branch/main/graph/badge.svg?token=GS64MV1H4W)](https://codecov.io/gh/redis/redis-benchmarks-specification)
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[![CI tests](https://github.com/redis/redis-benchmarks-specification/actions/workflows/tox.yml/badge.svg)](https://github.com/redis/redis-benchmarks-specification/actions/workflows/tox.yml)
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[![Run tox on Ubuntu 22.04](https://github.com/redis/redis-benchmarks-specification/actions/workflows/tox-self-hosted.yml/badge.svg)](https://github.com/redis/redis-benchmarks-specification/actions/workflows/tox-self-hosted.yml)
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[![PyPI version](https://badge.fury.io/py/redis-benchmarks-specification.svg)](https://pypi.org/project/redis-benchmarks-specification)
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<!-- toc -->

‎pyproject.toml‎

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[tool.poetry]
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name = "redis-benchmarks-specification"
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version = "0.1.63"
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version = "0.1.64"
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description = "The Redis benchmarks specification describes the cross-language/tools requirements and expectations to foster performance and observability standards around redis related technologies. Members from both industry and academia, including organizations and individuals are encouraged to contribute."
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authors = ["filipecosta90 <[email protected]>","Redis Performance Group <[email protected]>"]
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readme = "Readme.md"

‎redis_benchmarks_specification/__runner__/runner.py‎

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logging.info("Sending FLUSHALL to the DB")
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r.flushall()
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benchmark_required_memory = 0
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maxmemory = 0
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if "resources" in benchmark_config["dbconfig"]:
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resources = benchmark_config["dbconfig"]["resources"]
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if "requests" in resources:
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resources_requests = benchmark_config["dbconfig"][
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"resources"
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]["requests"]
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if "memory" in resources_requests:
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benchmark_required_memory = resources_requests["memory"]
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benchmark_required_memory = parse_size(
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benchmark_required_memory
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)
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logging.info(
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"Benchmark required memory: {} Bytes".format(
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benchmark_required_memory
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)
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)
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maxmemory = r.info("memory")["maxmemory"]
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if maxmemory == 0:
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total_system_memory = r.info("memory")["total_system_memory"]
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logging.info(
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" Using total system memory as max {}".format(
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total_system_memory
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)
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)
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maxmemory = total_system_memory
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benchmark_required_memory = get_benchmark_required_memory(
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benchmark_config
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)
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maxmemory = get_maxmemory(r)
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if benchmark_required_memory > maxmemory:
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logging.WARN(
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logging.warning(
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"Skipping test {} given maxmemory of server is bellow the benchmark required memory: {} < {}".format(
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test_name, maxmemory, benchmark_required_memory
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)
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)
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def get_maxmemory(r):
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maxmemory = int(r.info("memory")["maxmemory"])
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if maxmemory == 0:
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total_system_memory = int(r.info("memory")["total_system_memory"])
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logging.info(" Using total system memory as max {}".format(total_system_memory))
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maxmemory = total_system_memory
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else:
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logging.info(" Detected redis maxmemory config value {}".format(maxmemory))
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return maxmemory
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def get_benchmark_required_memory(benchmark_config):
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benchmark_required_memory = 0
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if "resources" in benchmark_config["dbconfig"]:
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resources = benchmark_config["dbconfig"]["resources"]
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if "requests" in resources:
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resources_requests = benchmark_config["dbconfig"]["resources"]["requests"]
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if "memory" in resources_requests:
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benchmark_required_memory = resources_requests["memory"]
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benchmark_required_memory = int(parse_size(benchmark_required_memory))
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logging.info(
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"Benchmark required memory: {} Bytes".format(
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benchmark_required_memory
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)
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)
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return benchmark_required_memory
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def used_memory_check(test_name, benchmark_required_memory, r, stage):
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used_memory = r.info("memory")["used_memory"]
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used_memory_gb = int(math.ceil(float(used_memory) / 1024.0 / 1024.0 / 1024.0))

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