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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 to perform an asynchronous query in BigQuery.

This sample is used on this page:

https://cloud.google.com/bigquery/querying-data#asyncqueries

For more information, see the README.md under /bigquery.

"""

import argparse

import json

import time

import uuid

from googleapiclient import discovery

from oauth2client.client import GoogleCredentials

# [START async_query]

def async_query(bigquery, project_id, query, batch=False, num_retries=5):

# Generate a unique job_id so retries

# don't accidentally duplicate query

job_data = {

'jobReference': {

'projectId': project_id,

'job_id': str(uuid.uuid4())

},

'configuration': {

'query': {

'query': query,

'priority': 'BATCH' if batch else 'INTERACTIVE'

}

}

}

return bigquery.jobs().insert(

projectId=project_id,

body=job_data).execute(num_retries=num_retries)

# [END async_query]

# [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, query_string, batch, num_retries, interval):

# [START build_service]

# Grab the application's default credentials from the environment.

credentials = GoogleCredentials.get_application_default()

# Construct the service object for interacting with the BigQuery API.

bigquery = discovery.build('bigquery', 'v2', credentials=credentials)

# [END build_service]

# Submit the job and wait for it to complete.

query_job = async_query(

bigquery,

project_id,

query_string,

batch,

num_retries)

poll_job(bigquery, query_job)

# Page through the result set and print all results.

page_token = None

while True:

page = bigquery.jobs().getQueryResults(

pageToken=page_token,

**query_job['jobReference']).execute(num_retries=2)

print(json.dumps(page['rows']))

page_token = page.get('pageToken')

if not page_token:

break

# [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('query', help='BigQuery SQL Query.')

parser.add_argument(

'-b', '--batch', help='Run query in batch mode.', action='store_true')

parser.add_argument(

'-r', '--num_retries',

help='Number of times to retry in case of 500 error.',

type=int,

default=5)

parser.add_argument(

'-p', '--poll_interval',

help='How often to poll the query for completion (seconds).',

type=int,

default=1)

args = parser.parse_args()

main(

args.project_id,

args.query,

args.batch,

args.num_retries,

args.poll_interval)

# [END main]