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https://issues.apache.org/jira/browse/BEAM-8910?focusedWorklogId=409965&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-409965
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ASF GitHub Bot logged work on BEAM-8910:
----------------------------------------
Author: ASF GitHub Bot
Created on: 25/Mar/20 23:29
Start Date: 25/Mar/20 23:29
Worklog Time Spent: 10m
Work Description: tvalentyn commented on pull request #11086: [BEAM-8910]
Make custom BQ source read from Avro
URL: https://github.com/apache/beam/pull/11086#discussion_r398232108
##########
File path: sdks/python/apache_beam/io/gcp/bigquery_read_it_test.py
##########
@@ -236,11 +251,12 @@ def create_table(cls, table_name):
cls.bigquery_client.insert_rows(
cls.project, cls.dataset_id, table_name, table_data)
- def get_expected_data(self):
+ def get_expected_data(self, native=True):
+ byts = b'\xab\xac'
expected_row = {
'float': 0.33,
'numeric': Decimal('10'),
- 'bytes': base64.b64encode(b'\xab\xac'),
+ 'bytes': base64.b64encode(byts) if native else byts,
Review comment:
Bytes treatment should be called out in IO doc, we do mention it:
https://github.com/apache/beam/blob/8bc2880cca40c00a96623b3ce96ea0b856af76c9/sdks/python/apache_beam/io/gcp/bigquery.py#L227.
b64encoding may be unnecessary, and less efficient. I think the reason
native IO encodes bytes with b64 is because that was the behavior in Java SDK.
We can argue that's not necessary. However I am concerned about the consistency
of the UX here. Different UX for two transforms means the transforms will not
be interchangeable, and users might overlook this. This might also cause
friction in cross-language pipelines.
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Issue Time Tracking
-------------------
Worklog Id: (was: 409965)
Time Spent: 3h 10m (was: 3h)
> Use AVRO instead of JSON in BigQuery bounded source.
> ----------------------------------------------------
>
> Key: BEAM-8910
> URL: https://issues.apache.org/jira/browse/BEAM-8910
> Project: Beam
> Issue Type: Improvement
> Components: sdk-py-core
> Reporter: Kamil Wasilewski
> Assignee: Pablo Estrada
> Priority: Minor
> Time Spent: 3h 10m
> Remaining Estimate: 0h
>
> The proposed BigQuery bounded source in Python SDK (see PR:
> [https://github.com/apache/beam/pull/9772)] uses a BigQuery export job to
> take a snapshot of the table and read from each produced JSON file. A
> performance improvement can be gain by switching to AVRO instead.
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