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#!/usr/bin/env python
# Copyright 2015, Google, Inc.
# 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.
"""Command-line application that loads data into BigQuery from a CSV file in
Google Cloud Storage.
This sample is used on this page:
https://cloud.google.com/bigquery/loading-data-into-bigquery#loaddatagcs
For more information, see the README.rst.
"""
import argparse
import json
import time
import uuid
import googleapiclient.discovery
# [START load_table]
def load_table(bigquery, project_id, dataset_id, table_name, source_schema,
source_path, num_retries=5):
"""
Starts a job to load a bigquery table from CSV
Args:
bigquery: an initialized and authorized bigquery client
google-api-client object
source_schema: a valid bigquery schema,
see https://cloud.google.com/bigquery/docs/reference/v2/tables
source_path: the fully qualified Google Cloud Storage location of
the data to load into your table
Returns: a bigquery load job, see
https://cloud.google.com/bigquery/docs/reference/v2/jobs#configuration.load
"""
# Generate a unique job ID so retries
# don't accidentally duplicate query
job_data = {
'jobReference': {
'projectId': project_id,
'jobId': str(uuid.uuid4())
},
'configuration': {
'load': {
'sourceUris': [source_path],
'schema': {
'fields': source_schema
},
'destinationTable': {
'projectId': project_id,
'datasetId': dataset_id,
'tableId': table_name
}
}
}
}
return bigquery.jobs().insert(
projectId=project_id,
body=job_data).execute(num_retries=num_retries)
# [END load_table]
# [START poll_job]
def poll_job(bigquery, job):
"""Waits for a job to complete."""
print('Waiting for job to finish...')
request = bigquery.jobs().get(
projectId=job['jobReference']['projectId'],
jobId=job['jobReference']['jobId'])
while True:
result = request.execute(num_retries=2)
if result['status']['state'] == 'DONE':
if 'errorResult' in result['status']:
raise RuntimeError(result['status']['errorResult'])
print('Job complete.')
return
time.sleep(1)
# [END poll_job]
# [START run]
def main(project_id, dataset_id, table_name, schema_file, data_path,
poll_interval, num_retries):
# [START build_service]
# Construct the service object for interacting with the BigQuery API.
bigquery = googleapiclient.discovery.build('bigquery', 'v2')
# [END build_service]
with open(schema_file, 'r') as f:
schema = json.load(f)
job = load_table(
bigquery,
project_id,
dataset_id,
table_name,
schema,
data_path,
num_retries)
poll_job(bigquery, job)
# [END run]
# [START main]
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('project_id', help='Your Google Cloud project ID.')
parser.add_argument('dataset_id', help='A BigQuery dataset ID.')
parser.add_argument(
'table_name', help='Name of the table to load data into.')
parser.add_argument(
'schema_file',
help='Path to a schema file describing the table schema.')
parser.add_argument(
'data_path',
help='Google Cloud Storage path to the CSV data, for example: '
'gs://mybucket/in.csv')
parser.add_argument(
'-p', '--poll_interval',
help='How often to poll the query for completion (seconds).',
type=int,
default=1)
parser.add_argument(
'-r', '--num_retries',
help='Number of times to retry in case of 500 error.',
type=int,
default=5)
args = parser.parse_args()
main(
args.project_id,
args.dataset_id,
args.table_name,
args.schema_file,
args.data_path,
args.poll_interval,
args.num_retries)
# [END main]