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c61e0be | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 | # Copyright 2019 Google LLC
#
# 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
#
# https://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 typing
if typing.TYPE_CHECKING:
from google.cloud import bigquery
def client_query_batch() -> "bigquery.QueryJob":
# [START bigquery_query_batch]
from google.cloud import bigquery
# Construct a BigQuery client object.
client = bigquery.Client()
job_config = bigquery.QueryJobConfig(
# Run at batch priority, which won't count toward concurrent rate limit.
priority=bigquery.QueryPriority.BATCH
)
sql = """
SELECT corpus
FROM `bigquery-public-data.samples.shakespeare`
GROUP BY corpus;
"""
# Start the query, passing in the extra configuration.
query_job = client.query(sql, job_config=job_config) # Make an API request.
# Check on the progress by getting the job's updated state. Once the state
# is `DONE`, the results are ready.
query_job = typing.cast(
"bigquery.QueryJob",
client.get_job(
query_job.job_id, location=query_job.location
), # Make an API request.
)
print("Job {} is currently in state {}".format(query_job.job_id, query_job.state))
# [END bigquery_query_batch]
return query_job
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