The C based gRPC (C++, Python, Ruby, Objective-C, PHP, C#) https://grpc.io/
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#!/usr/bin/env python
# Copyright 2017 gRPC authors.
#
# 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.
"""Uploads RBE results to BigQuery"""
import argparse
import os
import json
import sys
import urllib2
import uuid
gcp_utils_dir = os.path.abspath(
os.path.join(os.path.dirname(__file__), '../../gcp/utils'))
sys.path.append(gcp_utils_dir)
import big_query_utils
_DATASET_ID = 'jenkins_test_results'
_DESCRIPTION = 'Test results from master RBE builds on Kokoro'
# 90 days in milliseconds
_EXPIRATION_MS = 90 * 24 * 60 * 60 * 1000
_PARTITION_TYPE = 'DAY'
_PROJECT_ID = 'grpc-testing'
_RESULTS_SCHEMA = [
('job_name', 'STRING', 'Name of Kokoro job'),
('build_id', 'INTEGER', 'Build ID of Kokoro job'),
('build_url', 'STRING', 'URL of Kokoro build'),
('test_target', 'STRING', 'Bazel target path'),
('test_case', 'STRING', 'Name of test case'),
('result', 'STRING', 'Test or build result'),
('timestamp', 'TIMESTAMP', 'Timestamp of test run'),
]
_TABLE_ID = 'rbe_test_results'
def _get_api_key():
"""Returns string with API key to access ResultStore.
Intended to be used in Kokoro envrionment."""
api_key_directory = os.getenv('KOKORO_GFILE_DIR')
api_key_file = os.path.join(api_key_directory, 'resultstore_api_key')
assert os.path.isfile(api_key_file), 'Must add --api_key arg if not on ' \
'Kokoro or Kokoro envrionment is not set up properly.'
with open(api_key_file, 'r') as f:
return f.read().replace('\n', '')
def _get_invocation_id():
"""Returns String of Bazel invocation ID. Intended to be used in
Kokoro envirionment."""
bazel_id_directory = os.getenv('KOKORO_ARTIFACTS_DIR')
bazel_id_file = os.path.join(bazel_id_directory, 'bazel_invocation_ids')
assert os.path.isfile(bazel_id_file), 'bazel_invocation_ids file, written ' \
'by bazel_wrapper.py, expected but not found.'
with open(bazel_id_file, 'r') as f:
return f.read().replace('\n', '')
def _upload_results_to_bq(rows):
"""Upload test results to a BQ table.
Args:
rows: A list of dictionaries containing data for each row to insert
"""
bq = big_query_utils.create_big_query()
big_query_utils.create_partitioned_table(
bq,
_PROJECT_ID,
_DATASET_ID,
_TABLE_ID,
_RESULTS_SCHEMA,
_DESCRIPTION,
partition_type=_PARTITION_TYPE,
expiration_ms=_EXPIRATION_MS)
max_retries = 3
for attempt in range(max_retries):
if big_query_utils.insert_rows(bq, _PROJECT_ID, _DATASET_ID, _TABLE_ID,
rows):
break
else:
if attempt < max_retries - 1:
print('Error uploading result to bigquery, will retry.')
else:
print(
'Error uploading result to bigquery, all attempts failed.')
sys.exit(1)
def _get_resultstore_data(api_key, invocation_id):
"""Returns dictionary of test results by querying ResultStore API.
Args:
api_key: String of ResultStore API key
invocation_id: String of ResultStore invocation ID to results from
"""
all_actions = []
page_token = ''
# ResultStore's API returns data on a limited number of tests. When we exceed
# that limit, the 'nextPageToken' field is included in the request to get
# subsequent data, so keep requesting until 'nextPageToken' field is omitted.
while True:
req = urllib2.Request(
url=
'https://resultstore.googleapis.com/v2/invocations/%s/targets/-/configuredTargets/-/actions?key=%s&pageToken=%s'
% (invocation_id, api_key, page_token),
headers={
'Content-Type': 'application/json'
})
results = json.loads(urllib2.urlopen(req).read())
all_actions.extend(results['actions'])
if 'nextPageToken' not in results:
break
page_token = results['nextPageToken']
return all_actions
if __name__ == "__main__":
# Arguments are necessary if running in a non-Kokoro environment.
argp = argparse.ArgumentParser(description='Upload RBE results.')
argp.add_argument('--api_key', default='', type=str)
argp.add_argument('--invocation_id', default='', type=str)
args = argp.parse_args()
api_key = args.api_key or _get_api_key()
invocation_id = args.invocation_id or _get_invocation_id()
resultstore_actions = _get_resultstore_data(api_key, invocation_id)
bq_rows = []
for index, action in enumerate(resultstore_actions):
# Filter out non-test related data, such as build results.
if 'testAction' not in action:
continue
# Some test results contain the fileProcessingErrors field, which indicates
# an issue with parsing results individual test cases.
if 'fileProcessingErrors' in action:
test_cases = [{
'testCase': {
'caseName': str(action['id']['actionId']),
}
}]
# Test timeouts have a different dictionary structure compared to pass and
# fail results.
elif action['statusAttributes']['status'] == 'TIMED_OUT':
test_cases = [{
'testCase': {
'caseName': str(action['id']['actionId']),
'timedOut': True
}
}]
# When RBE believes its infrastructure is failing, it will abort and
# mark running tests as UNKNOWN. These infrastructure failures may be
# related to our tests, so we should investigate if specific tests are
# repeatedly being marked as UNKNOWN.
elif action['statusAttributes']['status'] == 'UNKNOWN':
test_cases = [{
'testCase': {
'caseName': str(action['id']['actionId']),
'unknown': True
}
}]
# Take the timestamp from the previous action, which should be
# a close approximation.
action['timing'] = {
'startTime':
resultstore_actions[index - 1]['timing']['startTime']
}
else:
test_cases = action['testAction']['testSuite']['tests'][0][
'testSuite']['tests']
for test_case in test_cases:
if any(s in test_case['testCase'] for s in ['errors', 'failures']):
result = 'FAILED'
elif 'timedOut' in test_case['testCase']:
result = 'TIMEOUT'
elif 'unknown' in test_case['testCase']:
result = 'UNKNOWN'
else:
result = 'PASSED'
try:
bq_rows.append({
'insertId': str(uuid.uuid4()),
'json': {
'job_name':
os.getenv('KOKORO_JOB_NAME'),
'build_id':
os.getenv('KOKORO_BUILD_NUMBER'),
'build_url':
'https://source.cloud.google.com/results/invocations/%s'
% invocation_id,
'test_target':
action['id']['targetId'],
'test_case':
test_case['testCase']['caseName'],
'result':
result,
'timestamp':
action['timing']['startTime'],
}
})
except Exception as e:
print('Failed to parse test result. Error: %s' % str(e))
print(json.dumps(test_case, indent=4))
bq_rows.append({
'insertId': str(uuid.uuid4()),
'json': {
'job_name':
os.getenv('KOKORO_JOB_NAME'),
'build_id':
os.getenv('KOKORO_BUILD_NUMBER'),
'build_url':
'https://source.cloud.google.com/results/invocations/%s'
% invocation_id,
'test_target':
action['id']['targetId'],
'test_case':
'N/A',
'result':
'UNPARSEABLE',
'timestamp':
'N/A',
}
})
# BigQuery sometimes fails with large uploads, so batch 1,000 rows at a time.
for i in range((len(bq_rows) / 1000) + 1):
_upload_results_to_bq(bq_rows[i * 1000:(i + 1) * 1000])