/
quickstart.py
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/
quickstart.py
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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.
import argparse
def main(project_id="your-project-id", snapshot_millis=0):
# [START bigquerystorage_quickstart]
from google.cloud import bigquery_storage_v1beta1
# TODO(developer): Set the project_id variable.
# project_id = 'your-project-id'
#
# The read session is created in this project. This project can be
# different from that which contains the table.
client = bigquery_storage_v1beta1.BigQueryStorageClient()
# This example reads baby name data from the public datasets.
table_ref = bigquery_storage_v1beta1.types.TableReference()
table_ref.project_id = "bigquery-public-data"
table_ref.dataset_id = "usa_names"
table_ref.table_id = "usa_1910_current"
# We limit the output columns to a subset of those allowed in the table,
# and set a simple filter to only report names from the state of
# Washington (WA).
read_options = bigquery_storage_v1beta1.types.TableReadOptions()
read_options.selected_fields.append("name")
read_options.selected_fields.append("number")
read_options.selected_fields.append("state")
read_options.row_restriction = 'state = "WA"'
# Set a snapshot time if it's been specified.
modifiers = None
if snapshot_millis > 0:
modifiers = bigquery_storage_v1beta1.types.TableModifiers()
modifiers.snapshot_time.FromMilliseconds(snapshot_millis)
parent = "projects/{}".format(project_id)
session = client.create_read_session(
table_ref,
parent,
table_modifiers=modifiers,
read_options=read_options,
# This API can also deliver data serialized in Apache Arrow format.
# This example leverages Apache Avro.
format_=bigquery_storage_v1beta1.enums.DataFormat.AVRO,
# We use a LIQUID strategy in this example because we only read from a
# single stream. Consider BALANCED if you're consuming multiple streams
# concurrently and want more consistent stream sizes.
sharding_strategy=(bigquery_storage_v1beta1.enums.ShardingStrategy.LIQUID),
) # API request.
# We'll use only a single stream for reading data from the table. Because
# of dynamic sharding, this will yield all the rows in the table. However,
# if you wanted to fan out multiple readers you could do so by having a
# reader process each individual stream.
reader = client.read_rows(
bigquery_storage_v1beta1.types.StreamPosition(stream=session.streams[0])
)
# The read stream contains blocks of Avro-encoded bytes. The rows() method
# uses the fastavro library to parse these blocks as an interable of Python
# dictionaries. Install fastavro with the following command:
#
# pip install google-cloud-bigquery-storage[fastavro]
rows = reader.rows(session)
# Do any local processing by iterating over the rows. The
# google-cloud-bigquery-storage client reconnects to the API after any
# transient network errors or timeouts.
names = set()
states = set()
for row in rows:
names.add(row["name"])
states.add(row["state"])
print("Got {} unique names in states: {}".format(len(names), states))
# [END bigquerystorage_quickstart]
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("project_id")
parser.add_argument("--snapshot_millis", default=0, type=int)
args = parser.parse_args()
main(project_id=args.project_id)