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https://issues.apache.org/jira/browse/BEAM-383?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15463597#comment-15463597
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ASF GitHub Bot commented on BEAM-383:
-------------------------------------
GitHub user dhalperi opened a pull request:
https://github.com/apache/incubator-beam/pull/917
[BEAM-383] BigQuery: limit max job polling time to 1 minute
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---
Before the backoff would grow unboundedly, so we could in principle wait
1.5x to 2x the actual job time. For long running jobs this is hours.
Now, we just back off at most 1 minute between checking the job state.
Note there should be no danger of QPS overload here because we should
have very few concurrent outstanding jobs
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/dhalperi/incubator-beam bigquery-write-backoff
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/incubator-beam/pull/917.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #917
----
commit 0cc46575c32fc5f96b9ec0a488b639d8ea105b99
Author: Dan Halperin <[email protected]>
Date: 2016-09-04T21:54:42Z
BigQuery: limit max job polling time to 1 minute
Before the backoff would grow unboundedly, so we could in principle wait
1.5x to 2x the actual job time. For long running jobs this is hours.
Now, we just back off at most 1 minute between checking the job state.
Note there should be no danger of QPS overload here because we should
have very few concurrent outstanding jobs
----
> BigQueryIO: update sink to shard into multiple write jobs
> ---------------------------------------------------------
>
> Key: BEAM-383
> URL: https://issues.apache.org/jira/browse/BEAM-383
> Project: Beam
> Issue Type: Bug
> Components: sdk-java-gcp
> Reporter: Daniel Halperin
> Assignee: Ian Zhou
> Fix For: 0.3.0-incubating
>
>
> BigQuery has global limits on both the # files that can be written in a
> single job and the total bytes in those files. We should be able to modify
> BigQueryIO.Write to chunk into multiple smaller jobs that meet these limits,
> write to temp tables, and atomically copy into the destination table.
> This functionality will let us safely stay within BQ's load job limits.
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