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# 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.
def client_load_partitioned_table(table_id: str) -> None:
# [START bigquery_load_table_partitioned]
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(
schema=[
bigquery.SchemaField("name", "STRING"),
bigquery.SchemaField("post_abbr", "STRING"),
bigquery.SchemaField("date", "DATE"),
],
skip_leading_rows=1,
time_partitioning=bigquery.TimePartitioning(
type_=bigquery.TimePartitioningType.DAY,
field="date", # Name of the column to use for partitioning.
expiration_ms=7776000000, # 90 days.
),
)
uri = "gs://cloud-samples-data/bigquery/us-states/us-states-by-date.csv"
load_job = client.load_table_from_uri(
uri, table_id, job_config=job_config
) # Make an API request.
load_job.result() # Wait for the job to complete.
table = client.get_table(table_id)
print("Loaded {} rows to table {}".format(table.num_rows, table_id))
# [END bigquery_load_table_partitioned]