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https://issues.apache.org/jira/browse/BEAM-10917?focusedWorklogId=633211&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-633211
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ASF GitHub Bot logged work on BEAM-10917:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 03/Aug/21 22:46
Start Date: 03/Aug/21 22:46
Worklog Time Spent: 10m
Work Description: satybald commented on pull request #15185:
URL: https://github.com/apache/beam/pull/15185#issuecomment-892214935
> @satybald it also looks like you're using `fastavro` with the export-based
source, which isn't implemented for the storage API source yet. Out of
curiosity, how fast is your **v1** pipeline if you don't specify `use_fastavro`
as an experiment?
Yes, the pipeline that I am running is using `fast_avro` library with
export-based source. However, I didn't specify `use_avro` experiment flag. The
SDK automatically set this flag on.
> how fast is your **v1** pipeline if you don't specify `use_fastavro` as an
experiment?
Sorry for confusion, I believe you mean **v3** the one with export-based
source. To my knowledge, there's no option to turn off `fast_avro` usage as
it's hard-coded for export based source i.e.
[_CustomBigQuerySource](https://github.com/apache/beam/blob/master/sdks/python/apache_beam/io/gcp/bigquery.py#L765)
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Issue Time Tracking
-------------------
Worklog Id: (was: 633211)
Time Spent: 10h (was: 9h 50m)
> Implement a BigQuery bounded source using the BigQuery storage API
> ------------------------------------------------------------------
>
> Key: BEAM-10917
> URL: https://issues.apache.org/jira/browse/BEAM-10917
> Project: Beam
> Issue Type: New Feature
> Components: io-py-gcp
> Reporter: Kenneth Jung
> Assignee: Kanthi Subramanian
> Priority: P3
> Time Spent: 10h
> Remaining Estimate: 0h
>
> The Java SDK contains a bounded source implementation which uses the BigQuery
> storage API to read from BigQuery. We should implement the same for Python.
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