perfkitbenchmarker/linux_benchmarks/example_preprovision_benchmark.py

# Copyright 2018 PerfKitBenchmarker Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Sample benchmark which uses a VM & preprovisioned data."""

import posixpath
from typing import Any

from perfkitbenchmarker import benchmark_spec as bm_spec
from perfkitbenchmarker import configs
from perfkitbenchmarker import sample
from perfkitbenchmarker import vm_util

BENCHMARK_NAME = 'example_preprovision'
BENCHMARK_CONFIG = """
example_preprovision:
  description: Runs a sample benchmark.
  vm_groups:
    default:
      vm_spec: *default_dual_core
      vm_count: null
"""

# This benchmark uses preprovisioned data. Before running this benchmark on a
# given cloud, you must add the file 'sample_preprovisioned_data.txt' to that
# cloud by following the cloud-specific instructions. To create this file, run
# the following command:
#   echo "1234567890" > sample_preprovisioned_data.txt
#
# The value in this dict is the sha256sum hash for the file.
#
# The benchmark defines the constant BENCHMARK_DATA to contain the name of the
# file (which is prepended by the benchmark name followed by an underscore)
# mapped to the sha256sum hash. This ensures that when we change versions of the
# benchmark data or binaries, we update the code.
BENCHMARK_DATA = {
    'preprovisioned_data.txt': (
        '4795a1c2517089e4df569afd77c04e949139cf299c87f012b894fccf91df4594'
    )
}


def GetConfig(user_config: dict[str, Any]) -> dict[str, Any]:
  """Returns the configuration of a benchmark."""
  return configs.LoadConfig(BENCHMARK_CONFIG, user_config, BENCHMARK_NAME)


def Prepare(benchmark_spec: bm_spec.BenchmarkSpec):
  """Prepares the VMs and other resources for running the benchmark.

  This is a good place to download binaries onto the VMs, create any data files
  needed for a benchmark run, etc.

  Args:
    benchmark_spec: The benchmark spec for this sample benchmark.
  """
  vm = benchmark_spec.vms[0]
  vm.InstallPreprovisionedBenchmarkData(
      BENCHMARK_NAME, BENCHMARK_DATA, vm_util.VM_TMP_DIR
  )

  stdout, _ = vm.RemoteCommand(
      'cat %s' % (posixpath.join(vm_util.VM_TMP_DIR, 'preprovisioned_data.txt'))
  )
  assert stdout.strip() == '1234567890'


def Run(benchmark_spec: bm_spec.BenchmarkSpec) -> list[sample.Sample]:
  """Runs the benchmark and returns a dict of performance data.

  It must be possible to run the benchmark multiple times after the Prepare
  stage.

  Args:
    benchmark_spec: The benchmark spec for this sample benchmark.

  Returns:
    A list of performance samples.
  """
  del benchmark_spec
  # This is a sample benchmark that produces no meaningful data, but we return
  # a single sample as an example.
  metadata = dict()
  metadata['sample_metadata'] = 'sample'
  return [sample.Sample('sample_metric', 123.456, 'sec', metadata)]


def Cleanup(benchmark_spec: bm_spec.BenchmarkSpec):
  """Cleans up after the benchmark completes.

  The state of the VMs should be equivalent to the state before Prepare was
  called.

  Args:
    benchmark_spec: The benchmark spec for this sample benchmark.
  """
  del benchmark_spec