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192 lines
7.1 KiB
192 lines
7.1 KiB
#!/usr/bin/env python |
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# Copyright 2017 gRPC authors. |
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# |
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# Licensed under the Apache License, Version 2.0 (the "License"); |
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# you may not use this file except in compliance with the License. |
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# You may obtain a copy of the License at |
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# |
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# http://www.apache.org/licenses/LICENSE-2.0 |
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# |
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# Unless required by applicable law or agreed to in writing, software |
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# distributed under the License is distributed on an "AS IS" BASIS, |
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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# See the License for the specific language governing permissions and |
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# limitations under the License. |
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"""Uploads RBE results to BigQuery""" |
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import argparse |
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import os |
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import json |
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import sys |
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import urllib2 |
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import uuid |
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gcp_utils_dir = os.path.abspath( |
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os.path.join(os.path.dirname(__file__), '../../gcp/utils')) |
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sys.path.append(gcp_utils_dir) |
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import big_query_utils |
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_DATASET_ID = 'jenkins_test_results' |
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_DESCRIPTION = 'Test results from master RBE builds on Kokoro' |
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# 90 days in milliseconds |
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_EXPIRATION_MS = 90 * 24 * 60 * 60 * 1000 |
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_PARTITION_TYPE = 'DAY' |
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_PROJECT_ID = 'grpc-testing' |
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_RESULTS_SCHEMA = [ |
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('job_name', 'STRING', 'Name of Kokoro job'), |
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('build_id', 'INTEGER', 'Build ID of Kokoro job'), |
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('build_url', 'STRING', 'URL of Kokoro build'), |
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('test_target', 'STRING', 'Bazel target path'), |
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('test_case', 'STRING', 'Name of test case'), |
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('result', 'STRING', 'Test or build result'), |
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('timestamp', 'TIMESTAMP', 'Timestamp of test run'), |
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] |
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_TABLE_ID = 'rbe_test_results' |
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def _get_api_key(): |
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"""Returns string with API key to access ResultStore. |
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Intended to be used in Kokoro envrionment.""" |
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api_key_directory = os.getenv('KOKORO_GFILE_DIR') |
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api_key_file = os.path.join(api_key_directory, 'resultstore_api_key') |
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assert os.path.isfile(api_key_file), 'Must add --api_key arg if not on ' \ |
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'Kokoro or Kokoro envrionment is not set up properly.' |
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with open(api_key_file, 'r') as f: |
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return f.read().replace('\n', '') |
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def _get_invocation_id(): |
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"""Returns String of Bazel invocation ID. Intended to be used in |
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Kokoro envirionment.""" |
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bazel_id_directory = os.getenv('KOKORO_ARTIFACTS_DIR') |
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bazel_id_file = os.path.join(bazel_id_directory, 'bazel_invocation_ids') |
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assert os.path.isfile(bazel_id_file), 'bazel_invocation_ids file, written ' \ |
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'by bazel_wrapper.py, expected but not found.' |
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with open(bazel_id_file, 'r') as f: |
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return f.read().replace('\n', '') |
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def _upload_results_to_bq(rows): |
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"""Upload test results to a BQ table. |
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Args: |
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rows: A list of dictionaries containing data for each row to insert |
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""" |
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bq = big_query_utils.create_big_query() |
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big_query_utils.create_partitioned_table( |
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bq, |
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_PROJECT_ID, |
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_DATASET_ID, |
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_TABLE_ID, |
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_RESULTS_SCHEMA, |
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_DESCRIPTION, |
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partition_type=_PARTITION_TYPE, |
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expiration_ms=_EXPIRATION_MS) |
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max_retries = 3 |
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for attempt in range(max_retries): |
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if big_query_utils.insert_rows(bq, _PROJECT_ID, _DATASET_ID, _TABLE_ID, |
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rows): |
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break |
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else: |
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if attempt < max_retries - 1: |
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print('Error uploading result to bigquery, will retry.') |
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else: |
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print( |
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'Error uploading result to bigquery, all attempts failed.') |
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sys.exit(1) |
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def _get_resultstore_data(api_key, invocation_id): |
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"""Returns dictionary of test results by querying ResultStore API. |
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Args: |
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api_key: String of ResultStore API key |
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invocation_id: String of ResultStore invocation ID to results from |
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""" |
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all_actions = [] |
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page_token = '' |
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# ResultStore's API returns data on a limited number of tests. When we exceed |
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# that limit, the 'nextPageToken' field is included in the request to get |
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# subsequent data, so keep requesting until 'nextPageToken' field is omitted. |
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while True: |
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req = urllib2.Request( |
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url= |
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'https://resultstore.googleapis.com/v2/invocations/%s/targets/-/configuredTargets/-/actions?key=%s&pageToken=%s' |
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% (invocation_id, api_key, page_token), |
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headers={ |
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'Content-Type': 'application/json' |
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}) |
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results = json.loads(urllib2.urlopen(req).read()) |
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all_actions.extend(results['actions']) |
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if 'nextPageToken' not in results: |
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break |
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page_token = results['nextPageToken'] |
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return all_actions |
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if __name__ == "__main__": |
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# Arguments are necessary if running in a non-Kokoro environment. |
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argp = argparse.ArgumentParser(description='Upload RBE results.') |
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argp.add_argument('--api_key', default='', type=str) |
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argp.add_argument('--invocation_id', default='', type=str) |
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args = argp.parse_args() |
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api_key = args.api_key or _get_api_key() |
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invocation_id = args.invocation_id or _get_invocation_id() |
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resultstore_actions = _get_resultstore_data(api_key, invocation_id) |
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bq_rows = [] |
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for action in resultstore_actions: |
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# Filter out non-test related data, such as build results. |
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if 'testAction' not in action: |
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continue |
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# Some test results contain the fileProcessingErrors field, which indicates |
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# an issue with parsing results individual test cases. |
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if 'fileProcessingErrors' in action: |
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test_cases = [{ |
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'testCase': { |
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'caseName': str(action['id']['actionId']), |
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} |
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}] |
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# Test timeouts have a different dictionary structure compared to pass and |
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# fail results. |
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elif action['statusAttributes']['status'] == 'TIMED_OUT': |
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test_cases = [{ |
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'testCase': { |
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'caseName': str(action['id']['actionId']), |
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'timedOut': True |
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} |
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}] |
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else: |
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test_cases = action['testAction']['testSuite']['tests'][0][ |
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'testSuite']['tests'] |
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for test_case in test_cases: |
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if any(s in test_case['testCase'] for s in ['errors', 'failures']): |
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result = 'FAILED' |
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elif 'timedOut' in test_case['testCase']: |
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result = 'TIMEOUT' |
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else: |
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result = 'PASSED' |
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bq_rows.append({ |
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'insertId': str(uuid.uuid4()), |
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'json': { |
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'job_name': |
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os.getenv('KOKORO_JOB_NAME'), |
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'build_id': |
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os.getenv('KOKORO_BUILD_NUMBER'), |
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'build_url': |
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'https://source.cloud.google.com/results/invocations/%s' % |
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invocation_id, |
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'test_target': |
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action['id']['targetId'], |
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'test_case': |
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test_case['testCase']['caseName'], |
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'result': |
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result, |
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'timestamp': |
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action['timing']['startTime'], |
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} |
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}) |
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# BigQuery sometimes fails with large uploads, so batch 1,000 rows at a time. |
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for i in range((len(bq_rows) / 1000) + 1): |
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_upload_results_to_bq(bq_rows[i * 1000:(i + 1) * 1000])
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