def print_culprit_finder_pipeline(project_name, tasks, good_bazel_commit,
bad_bazel_commit, needs_clean, repeat_times):
pipeline_steps = []
for task_name in tasks:
platform_name = get_platform(project_name, task_name)
label = bazelci.PLATFORMS[platform_name][
"emoji-name"] + " Bisecting for {0}".format(project_name)
command = (
'%s culprit_finder.py runner --project_name="%s" --task_name=%s --good_bazel_commit=%s --bad_bazel_commit=%s %s %s'
% (
bazelci.PLATFORMS[platform_name]["python"],
project_name,
task_name,
good_bazel_commit,
bad_bazel_commit,
"--needs_clean" if needs_clean else "",
("--repeat_times=" +
str(repeat_times)) if repeat_times else "",
))
commands = [
bazelci.fetch_bazelcipy_command(),
fetch_culprit_finder_py_command(), command
]
pipeline_steps.append(
bazelci.create_step(label, commands, platform_name))
print(yaml.dump({"steps": pipeline_steps}))
def print_culprit_finder_pipeline(project_name, platform_name,
good_bazel_commit, bad_bazel_commit):
host_platform = PLATFORMS[platform_name].get("host-platform",
platform_name)
pipeline_steps = []
command = (
'%s culprit_finder.py runner --project_name="%s" --platform_name=%s --good_bazel_commit=%s --bad_bazel_commit=%s'
% (
bazelci.python_binary(platform_name),
project_name,
platform_name,
good_bazel_commit,
bad_bazel_commit,
))
pipeline_steps.append({
"label":
PLATFORMS[platform_name]["emoji-name"] +
" Bisecting for {0}".format(project_name),
"command": [
bazelci.fetch_bazelcipy_command(),
fetch_culprit_finder_py_command(),
command,
],
"agents": {
"kind":
"worker",
"java":
PLATFORMS[platform_name]["java"],
"os":
bazelci.rchop(host_platform, "_nojava", "_java8", "_java9",
"_java10"),
},
})
print(yaml.dump({"steps": pipeline_steps}))
def print_culprit_finder_pipeline(
project_name, platform_name, good_bazel_commit, bad_bazel_commit, needs_clean
):
label = PLATFORMS[platform_name]["emoji-name"] + " Bisecting for {0}".format(project_name)
command = (
'%s culprit_finder.py runner --project_name="%s" --platform_name=%s --good_bazel_commit=%s --bad_bazel_commit=%s %s'
% (
bazelci.python_binary(platform_name),
project_name,
platform_name,
good_bazel_commit,
bad_bazel_commit,
"--needs_clean" if needs_clean else "",
)
)
commands = [bazelci.fetch_bazelcipy_command(), fetch_culprit_finder_py_command(), command]
pipeline_steps = []
pipeline_steps.append(bazelci.create_step(label, commands, platform_name))
print(yaml.dump({"steps": pipeline_steps}))
def _ci_step_for_platform_and_commits(bazel_commits, platform, project,
extra_options):
"""Perform bazel-bench for the platform-project combination.
Uploads results to BigQuery.
Args:
bazel_commits: a list of strings: bazel commits to be benchmarked.
platform: a string: the platform to benchmark on.
project: an object: contains the information of the project to be
tested on.
extra_options: a string: extra bazel-bench options.
Return:
An object: the result of applying bazelci.create_step to wrap the
command to be executed by buildkite-agent.
"""
project_clone_path = _get_clone_path(project["git_repository"], platform)
bazel_clone_path = _get_clone_path(BAZEL_REPOSITORY, platform)
bazel_bench_command = " ".join([
"bazel",
"run",
"benchmark",
"--",
"--bazel_commits=%s" % ",".join(bazel_commits),
"--bazel_source=%s" % bazel_clone_path,
"--project_source=%s" % project_clone_path,
"--platform=%s" % platform,
"--collect_memory",
"--data_directory=%s" % DATA_DIRECTORY,
extra_options,
"--",
project["bazel_command"],
])
commands = (
[bazelci.fetch_bazelcipy_command()] +
_bazel_bench_env_setup_command(platform, ",".join(bazel_commits)) +
[bazel_bench_command])
label = (bazelci.PLATFORMS[platform]["emoji-name"] +
" Running bazel-bench on project: %s" % project["name"])
return bazelci.create_step(label, commands, platform)
def add_presubmit_jobs(module_name, module_version, task_config,
pipeline_steps):
for task_name in task_config:
platform_name = bazelci.get_platform_for_task(task_name, task_config)
label = bazelci.PLATFORMS[platform_name][
"emoji-name"] + " {0}@{1}".format(module_name, module_version)
command = (
'%s bcr_presubmit.py runner --module_name="%s" --module_version="%s" --task=%s'
% (
bazelci.PLATFORMS[platform_name]["python"],
module_name,
module_version,
task_name,
))
commands = [
bazelci.fetch_bazelcipy_command(),
fetch_bcr_presubmit_py_command(), command
]
pipeline_steps.append(
bazelci.create_step(label, commands, platform_name))
def _ci_step_for_platform_and_commits(bazel_commits, platform, project,
extra_options, date, bucket,
bigquery_table):
"""Perform bazel-bench for the platform-project combination.
Uploads results to BigQuery.
Args:
bazel_commits: a list of strings: bazel commits to be benchmarked.
platform: a string: the platform to benchmark on.
project: an object: contains the information of the project to be
tested on.
extra_options: a string: extra bazel-bench options.
date: the date of the commits.
bucket: the GCP Storage bucket to upload data to.
bigquery_table: the table to upload data to. In the form `project:table_identifier`.
Return:
An object: the result of applying bazelci.create_step to wrap the
command to be executed by buildkite-agent.
"""
project_clone_path = _get_clone_path(project["git_repository"], platform)
bazel_clone_path = _get_clone_path(BAZEL_REPOSITORY, platform)
bazel_bench_command = " ".join([
"bazel",
"run",
"benchmark",
"--",
"--bazel_commits=%s" % ",".join(bazel_commits),
"--bazel_source=%s" % bazel_clone_path,
"--project_source=%s" % project_clone_path,
"--project_label=%s" % project["project_label"],
"--platform=%s" % platform,
"--collect_memory",
"--data_directory=%s" % DATA_DIRECTORY,
"--csv_file_name=%s" % BAZEL_BENCH_RESULT_FILENAME,
"--collect_json_profile",
"--aggregate_json_profiles",
extra_options,
"--",
project["bazel_command"],
])
# TODO(leba): Use GCP Python client instead of gsutil.
# TODO(https://github.com/bazelbuild/bazel-bench/issues/46): Include task-specific shell commands and build flags.
# Upload everything under DATA_DIRECTORY to Storage.
# This includes the raw data, aggr JSON profile and the JSON profiles
# themselves.
storage_subdir = "{}/{}/{}/".format(project["storage_subdir"],
date.strftime("%Y/%m/%d"), platform)
upload_output_files_storage_command = " ".join([
"gsutil",
"-m",
"cp",
"-r",
"{}/*".format(DATA_DIRECTORY),
"gs://{}/{}".format(bucket, storage_subdir),
])
upload_to_big_query_command = " ".join([
"bq",
"load",
"--skip_leading_rows=1",
"--source_format=CSV",
bigquery_table,
"{}/perf_data.csv".format(DATA_DIRECTORY),
])
commands = (
[bazelci.fetch_bazelcipy_command()] +
_bazel_bench_env_setup_command(platform, ",".join(bazel_commits)) + [
bazel_bench_command, upload_output_files_storage_command,
upload_to_big_query_command
])
label = bazelci.PLATFORMS[platform]["emoji-name"] + project["project_label"]
return bazelci.create_step(label, commands, platform)
