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Posted to issues@beam.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2020/01/03 20:26:00 UTC
[jira] [Work logged] (BEAM-8745) More fine-grained controls for the
size of a BigQuery Load job
[ https://issues.apache.org/jira/browse/BEAM-8745?focusedWorklogId=366003&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-366003 ]
ASF GitHub Bot logged work on BEAM-8745:
----------------------------------------
Author: ASF GitHub Bot
Created on: 03/Jan/20 20:25
Start Date: 03/Jan/20 20:25
Worklog Time Spent: 10m
Work Description: jklukas commented on pull request #10500: BEAM-8745 More fine-grained controls for the size of a BigQuery Load job
URL: https://github.com/apache/beam/pull/10500
Users have hit problems where load jobs into very wide tables (100s of columns)
are very slow, and sometimes fail. Feedback from BigQuery is that for very wide
tables, smaller load jobs can avoid failures, and slowdowns.
`BigQueryIO` already has the plumbing to support `maxBytesPerPartition`, though
there is no public interface to change that parameter from the default.
This PR simply promotes this parameter to be public and adds documentation
for it.
------------------------
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Issue Time Tracking
-------------------
Worklog Id: (was: 366003)
Remaining Estimate: 0h
Time Spent: 10m
> More fine-grained controls for the size of a BigQuery Load job
> --------------------------------------------------------------
>
> Key: BEAM-8745
> URL: https://issues.apache.org/jira/browse/BEAM-8745
> Project: Beam
> Issue Type: Improvement
> Components: io-java-gcp
> Reporter: Pablo Estrada
> Assignee: Jeff Klukas
> Priority: Major
> Time Spent: 10m
> Remaining Estimate: 0h
>
> Users have hit problems where load jobs into very wide tables (100s of columns) are very slow, and sometimes fail. Feedback from BigQuery is that for very wide tables, smaller load jobs can avoid failures, and slowdowns.
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