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#!/usr/bin/env python2.7
# Copyright 2015 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.
import argparse
import json
import uuid
import httplib2
from apiclient import discovery
from apiclient.errors import HttpError
from oauth2client.client import GoogleCredentials
# 30 days in milliseconds
_EXPIRATION_MS = 30 * 24 * 60 * 60 * 1000
NUM_RETRIES = 3
def create_big_query():
"""Authenticates with cloud platform and gets a BiqQuery service object
"""
creds = GoogleCredentials.get_application_default()
return discovery.build('bigquery', 'v2', credentials=creds, cache_discovery=False)
def create_dataset(biq_query, project_id, dataset_id):
is_success = True
body = {
'datasetReference': {
'projectId': project_id,
'datasetId': dataset_id
}
}
try:
dataset_req = biq_query.datasets().insert(projectId=project_id, body=body)
dataset_req.execute(num_retries=NUM_RETRIES)
except HttpError as http_error:
if http_error.resp.status == 409:
print 'Warning: The dataset %s already exists' % dataset_id
else:
# Note: For more debugging info, print "http_error.content"
print 'Error in creating dataset: %s. Err: %s' % (dataset_id, http_error)
is_success = False
return is_success
def create_table(big_query, project_id, dataset_id, table_id, table_schema,
description):
fields = [{'name': field_name,
'type': field_type,
'description': field_description
} for (field_name, field_type, field_description) in table_schema]
return create_table2(big_query, project_id, dataset_id, table_id,
fields, description)
def create_partitioned_table(big_query, project_id, dataset_id, table_id, table_schema,
description, partition_type='DAY', expiration_ms=_EXPIRATION_MS):
"""Creates a partitioned table. By default, a date-paritioned table is created with
each partition lasting 30 days after it was last modified.
"""
fields = [{'name': field_name,
'type': field_type,
'description': field_description
} for (field_name, field_type, field_description) in table_schema]
return create_table2(big_query, project_id, dataset_id, table_id,
fields, description, partition_type, expiration_ms)
def create_table2(big_query, project_id, dataset_id, table_id, fields_schema,
description, partition_type=None, expiration_ms=None):
is_success = True
body = {
'description': description,
'schema': {
'fields': fields_schema
},
'tableReference': {
'datasetId': dataset_id,
'projectId': project_id,
'tableId': table_id
}
}
if partition_type and expiration_ms:
body["timePartitioning"] = {
"type": partition_type,
"expirationMs": expiration_ms
}
try:
table_req = big_query.tables().insert(projectId=project_id,
datasetId=dataset_id,
body=body)
res = table_req.execute(num_retries=NUM_RETRIES)
print 'Successfully created %s "%s"' % (res['kind'], res['id'])
except HttpError as http_error:
if http_error.resp.status == 409:
print 'Warning: Table %s already exists' % table_id
else:
print 'Error in creating table: %s. Err: %s' % (table_id, http_error)
is_success = False
return is_success
def patch_table(big_query, project_id, dataset_id, table_id, fields_schema):
is_success = True
body = {
'schema': {
'fields': fields_schema
},
'tableReference': {
'datasetId': dataset_id,
'projectId': project_id,
'tableId': table_id
}
}
try:
table_req = big_query.tables().patch(projectId=project_id,
datasetId=dataset_id,
tableId=table_id,
body=body)
res = table_req.execute(num_retries=NUM_RETRIES)
print 'Successfully patched %s "%s"' % (res['kind'], res['id'])
except HttpError as http_error:
print 'Error in creating table: %s. Err: %s' % (table_id, http_error)
is_success = False
return is_success
def insert_rows(big_query, project_id, dataset_id, table_id, rows_list):
is_success = True
body = {'rows': rows_list}
try:
insert_req = big_query.tabledata().insertAll(projectId=project_id,
datasetId=dataset_id,
tableId=table_id,
body=body)
res = insert_req.execute(num_retries=NUM_RETRIES)
if res.get('insertErrors', None):
print 'Error inserting rows! Response: %s' % res
is_success = False
except HttpError as http_error:
print 'Error inserting rows to the table %s' % table_id
is_success = False
return is_success
def sync_query_job(big_query, project_id, query, timeout=5000):
query_data = {'query': query, 'timeoutMs': timeout}
query_job = None
try:
query_job = big_query.jobs().query(
projectId=project_id,
body=query_data).execute(num_retries=NUM_RETRIES)
except HttpError as http_error:
print 'Query execute job failed with error: %s' % http_error
print http_error.content
return query_job
# List of (column name, column type, description) tuples
def make_row(unique_row_id, row_values_dict):
"""row_values_dict is a dictionary of column name and column value.
"""
return {'insertId': unique_row_id, 'json': row_values_dict}
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