[
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.
------------------------
Thank you for your contribution! Follow this checklist to help us
incorporate your contribution quickly and easily:
- [ ] [**Choose
reviewer(s)**](https://beam.apache.org/contribute/#make-your-change) and
mention them in a comment (`R: @username`).
- [ ] Format the pull request title like `[BEAM-XXX] Fixes bug in
ApproximateQuantiles`, where you replace `BEAM-XXX` with the appropriate JIRA
issue, if applicable. This will automatically link the pull request to the
issue.
- [ ] If this contribution is large, please file an Apache [Individual
Contributor License Agreement](https://www.apache.org/licenses/icla.pdf).
See the [Contributor Guide](https://beam.apache.org/contribute) for more
tips on [how to make review process
smoother](https://beam.apache.org/contribute/#make-reviewers-job-easier).
Post-Commit Tests Status (on master branch)
------------------------------------------------------------------------------------------------
Lang | SDK | Apex | Dataflow | Flink | Gearpump | Samza | Spark
--- | --- | --- | --- | --- | --- | --- | ---
Go | [](https://builds.apache.org/job/beam_PostCommit_Go/lastCompletedBuild/)
| --- | --- | [](https://builds.apache.org/job/beam_PostCommit_Go_VR_Flink/lastCompletedBuild/)
| --- | --- | [](https://builds.apache.org/job/beam_PostCommit_Go_VR_Spark/lastCompletedBuild/)
Java | [](https://builds.apache.org/job/beam_PostCommit_Java/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PostCommit_Java_ValidatesRunner_Apex/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PostCommit_Java_ValidatesRunner_Dataflow/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PostCommit_Java_ValidatesRunner_Flink/lastCompletedBuild/)<br>[](https://builds.apache.org/job/beam_PostCommit_Java_PVR_Flink_Batch/lastCompletedBuild/)<br>[](https://builds.apache.org/job/beam_PostCommit_Java_PVR_Flink_Streaming/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PostCommit_Java_ValidatesRunner_Gearpump/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PostCommit_Java_ValidatesRunner_Samza/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PostCommit_Java_ValidatesRunner_Spark/lastCompletedBuild/)<br>[](https://builds.apache.org/job/beam_PostCommit_Java_PVR_Spark_Batch/lastCompletedBuild/)<br>[](https://builds.apache.org/job/beam_PostCommit_Java_ValidatesRunner_SparkStructuredStreaming/lastCompletedBuild/)
Python | [](https://builds.apache.org/job/beam_PostCommit_Python2/lastCompletedBuild/)<br>[](https://builds.apache.org/job/beam_PostCommit_Python35/lastCompletedBuild/)<br>[](https://builds.apache.org/job/beam_PostCommit_Python36/lastCompletedBuild/)<br>[](https://builds.apache.org/job/beam_PostCommit_Python37/lastCompletedBuild/)
| --- | [](https://builds.apache.org/job/beam_PostCommit_Py_VR_Dataflow/lastCompletedBuild/)<br>[](https://builds.apache.org/job/beam_PostCommit_Py_ValCont/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PreCommit_Python2_PVR_Flink_Cron/lastCompletedBuild/)<br>[](https://builds.apache.org/job/beam_PostCommit_Python35_VR_Flink/lastCompletedBuild/)
| --- | --- | [](https://builds.apache.org/job/beam_PostCommit_Python_VR_Spark/lastCompletedBuild/)
XLang | --- | --- | --- | [](https://builds.apache.org/job/beam_PostCommit_XVR_Flink/lastCompletedBuild/)
| --- | --- | ---
Pre-Commit Tests Status (on master branch)
------------------------------------------------------------------------------------------------
--- |Java | Python | Go | Website
--- | --- | --- | --- | ---
Non-portable | [](https://builds.apache.org/job/beam_PreCommit_Java_Cron/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PreCommit_Python_Cron/lastCompletedBuild/)<br>[](https://builds.apache.org/job/beam_PreCommit_PythonLint_Cron/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PreCommit_Go_Cron/lastCompletedBuild/)
| [](https://builds.apache.org/job/beam_PreCommit_Website_Cron/lastCompletedBuild/)
Portable | --- | [](https://builds.apache.org/job/beam_PreCommit_Portable_Python_Cron/lastCompletedBuild/)
| --- | ---
See
[.test-infra/jenkins/README](https://github.com/apache/beam/blob/master/.test-infra/jenkins/README.md)
for trigger phrase, status and link of all Jenkins jobs.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
[email protected]
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.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
