forked from googleapis/python-bigquery
/
load_table_clustered.py
55 lines (46 loc) · 1.93 KB
/
load_table_clustered.py
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# Copyright 2020 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
#
# 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.
def load_table_clustered(table_id):
# [START bigquery_load_table_clustered]
from google.cloud import bigquery
# Construct a BigQuery client object.
client = bigquery.Client()
# TODO(developer): Set table_id to the ID of the table to create.
# table_id = "your-project.your_dataset.your_table_name"
job_config = bigquery.LoadJobConfig(
skip_leading_rows=1,
source_format=bigquery.SourceFormat.CSV,
schema=[
bigquery.SchemaField("timestamp", bigquery.SqlTypeNames.TIMESTAMP),
bigquery.SchemaField("origin", bigquery.SqlTypeNames.STRING),
bigquery.SchemaField("destination", bigquery.SqlTypeNames.STRING),
bigquery.SchemaField("amount", bigquery.SqlTypeNames.NUMERIC),
],
time_partitioning=bigquery.TimePartitioning(field="timestamp"),
clustering_fields=["origin", "destination"],
)
job = client.load_table_from_uri(
["gs://cloud-samples-data/bigquery/sample-transactions/transactions.csv"],
table_id,
job_config=job_config,
)
job.result() # Waits for the job to complete.
table = client.get_table(table_id) # Make an API request.
print(
"Loaded {} rows and {} columns to {}".format(
table.num_rows, len(table.schema), table_id
)
)
# [END bigquery_load_table_clustered]
return table