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The C based gRPC (C++, Python, Ruby, Objective-C, PHP, C#)
https://grpc.io/
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204 lines
6.9 KiB
204 lines
6.9 KiB
# Copyright 2015 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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from __future__ import print_function |
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import argparse |
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import json |
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import uuid |
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from apiclient import discovery |
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from apiclient.errors import HttpError |
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import httplib2 |
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from oauth2client.client import GoogleCredentials |
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# 30 days in milliseconds |
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_EXPIRATION_MS = 30 * 24 * 60 * 60 * 1000 |
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NUM_RETRIES = 3 |
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def create_big_query(): |
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"""Authenticates with cloud platform and gets a BiqQuery service object |
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""" |
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creds = GoogleCredentials.get_application_default() |
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return discovery.build('bigquery', |
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'v2', |
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credentials=creds, |
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cache_discovery=False) |
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def create_dataset(biq_query, project_id, dataset_id): |
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is_success = True |
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body = { |
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'datasetReference': { |
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'projectId': project_id, |
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'datasetId': dataset_id |
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} |
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} |
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try: |
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dataset_req = biq_query.datasets().insert(projectId=project_id, |
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body=body) |
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dataset_req.execute(num_retries=NUM_RETRIES) |
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except HttpError as http_error: |
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if http_error.resp.status == 409: |
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print('Warning: The dataset %s already exists' % dataset_id) |
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else: |
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# Note: For more debugging info, print "http_error.content" |
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print('Error in creating dataset: %s. Err: %s' % |
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(dataset_id, http_error)) |
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is_success = False |
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return is_success |
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def create_table(big_query, project_id, dataset_id, table_id, table_schema, |
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description): |
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fields = [{ |
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'name': field_name, |
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'type': field_type, |
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'description': field_description |
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} for (field_name, field_type, field_description) in table_schema] |
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return create_table2(big_query, project_id, dataset_id, table_id, fields, |
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description) |
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def create_partitioned_table(big_query, |
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project_id, |
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dataset_id, |
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table_id, |
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table_schema, |
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description, |
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partition_type='DAY', |
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expiration_ms=_EXPIRATION_MS): |
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"""Creates a partitioned table. By default, a date-paritioned table is created with |
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each partition lasting 30 days after it was last modified. |
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""" |
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fields = [{ |
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'name': field_name, |
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'type': field_type, |
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'description': field_description |
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} for (field_name, field_type, field_description) in table_schema] |
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return create_table2(big_query, project_id, dataset_id, table_id, fields, |
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description, partition_type, expiration_ms) |
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def create_table2(big_query, |
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project_id, |
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dataset_id, |
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table_id, |
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fields_schema, |
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description, |
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partition_type=None, |
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expiration_ms=None): |
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is_success = True |
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body = { |
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'description': description, |
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'schema': { |
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'fields': fields_schema |
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}, |
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'tableReference': { |
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'datasetId': dataset_id, |
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'projectId': project_id, |
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'tableId': table_id |
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} |
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} |
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if partition_type and expiration_ms: |
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body["timePartitioning"] = { |
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"type": partition_type, |
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"expirationMs": expiration_ms |
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} |
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try: |
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table_req = big_query.tables().insert(projectId=project_id, |
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datasetId=dataset_id, |
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body=body) |
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res = table_req.execute(num_retries=NUM_RETRIES) |
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print('Successfully created %s "%s"' % (res['kind'], res['id'])) |
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except HttpError as http_error: |
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if http_error.resp.status == 409: |
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print('Warning: Table %s already exists' % table_id) |
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else: |
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print('Error in creating table: %s. Err: %s' % |
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(table_id, http_error)) |
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is_success = False |
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return is_success |
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def patch_table(big_query, project_id, dataset_id, table_id, fields_schema): |
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is_success = True |
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body = { |
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'schema': { |
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'fields': fields_schema |
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}, |
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'tableReference': { |
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'datasetId': dataset_id, |
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'projectId': project_id, |
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'tableId': table_id |
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} |
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} |
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try: |
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table_req = big_query.tables().patch(projectId=project_id, |
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datasetId=dataset_id, |
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tableId=table_id, |
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body=body) |
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res = table_req.execute(num_retries=NUM_RETRIES) |
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print('Successfully patched %s "%s"' % (res['kind'], res['id'])) |
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except HttpError as http_error: |
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print('Error in creating table: %s. Err: %s' % (table_id, http_error)) |
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is_success = False |
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return is_success |
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def insert_rows(big_query, project_id, dataset_id, table_id, rows_list): |
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is_success = True |
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body = {'rows': rows_list} |
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try: |
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insert_req = big_query.tabledata().insertAll(projectId=project_id, |
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datasetId=dataset_id, |
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tableId=table_id, |
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body=body) |
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res = insert_req.execute(num_retries=NUM_RETRIES) |
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if res.get('insertErrors', None): |
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print('Error inserting rows! Response: %s' % res) |
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is_success = False |
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except HttpError as http_error: |
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print('Error inserting rows to the table %s' % table_id) |
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print('Error message: %s' % http_error) |
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is_success = False |
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return is_success |
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def sync_query_job(big_query, project_id, query, timeout=5000): |
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query_data = {'query': query, 'timeoutMs': timeout} |
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query_job = None |
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try: |
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query_job = big_query.jobs().query( |
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projectId=project_id, |
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body=query_data).execute(num_retries=NUM_RETRIES) |
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except HttpError as http_error: |
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print('Query execute job failed with error: %s' % http_error) |
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print(http_error.content) |
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return query_job |
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# List of (column name, column type, description) tuples |
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def make_row(unique_row_id, row_values_dict): |
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"""row_values_dict is a dictionary of column name and column value. |
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""" |
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return {'insertId': unique_row_id, 'json': row_values_dict}
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