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# 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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