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BigQuery Storage: Update to use faster Arrow data format. #2269

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Merged
tswast merged 1 commit into from
Jul 12, 2019
Merged

BigQuery Storage: Update to use faster Arrow data format. #2269

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20 changes: 13 additions & 7 deletions bigquery_storage/to_dataframe/main_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,7 @@ def clients():
# Make clients.
bqclient = bigquery.Client(
credentials=credentials,
project=your_project_id
project=your_project_id,
)
bqstorageclient = bigquery_storage_v1beta1.BigQueryStorageClient(
credentials=credentials
Expand Down Expand Up @@ -90,11 +90,6 @@ def test_query_to_dataframe(capsys, clients):
dataframe = (
bqclient.query(query_string)
.result()

# Note: The BigQuery Storage API cannot be used to download small query
# results, but as of google-cloud-bigquery version 1.11.1, the
# to_dataframe method will fallback to the tabledata.list API when the
# BigQuery Storage API fails to read the query results.
.to_dataframe(bqstorage_client=bqstorageclient)
)
print(dataframe.head())
Expand Down Expand Up @@ -126,7 +121,18 @@ def test_session_to_dataframe(capsys, clients):

parent = "projects/{}".format(your_project_id)
session = bqstorageclient.create_read_session(
table, parent, read_options=read_options
table,
parent,
read_options=read_options,
# This API can also deliver data serialized in Apache Avro format.
# This example leverages Apache Arrow.
format_=bigquery_storage_v1beta1.enums.DataFormat.ARROW,
# 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
),
)

# This example reads from only a single stream. Read from multiple streams
Expand Down
8 changes: 4 additions & 4 deletions bigquery_storage/to_dataframe/requirements.txt
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
google-auth==1.6.2
google-cloud-bigquery-storage==0.3.0
google-cloud-bigquery==1.11.1
fastavro==0.21.17
google-cloud-bigquery-storage==0.6.0
google-cloud-bigquery==1.17.0
pyarrow==0.13.0
ipython==7.2.0
pandas==0.24.0
pandas==0.24.2