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https://issues.apache.org/jira/browse/BEAM-6443?focusedWorklogId=211352&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-211352
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ASF GitHub Bot logged work on BEAM-6443:
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Author: ASF GitHub Bot
Created on: 11/Mar/19 22:24
Start Date: 11/Mar/19 22:24
Worklog Time Spent: 10m
Work Description: ihji commented on issue #7547: [BEAM-6443] decrease the
number of thread for BigQuery streaming inse…
URL: https://github.com/apache/beam/pull/7547#issuecomment-471763651
> Can you describe how this PR has been tested at scale?
I created UnboundedSource that generates very small (9 bytes) and maximum
(1MB streaming insert row size limit) sized elements and ran a BigQuery
inserting pipeline on DataflowRunner with multiple threadpool configurations
(unlimited, single, 1 semaphored, 3 semaphored). Running time was about 20
minutes each. You can find exact numbers in a benchmark note:
https://docs.google.com/document/d/1EhRNWLevm86GD_QtvlrTauHITVMwQBzuemyp-w4Z_ck/edit#heading=h.c0angyd9tn21
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Issue Time Tracking
-------------------
Worklog Id: (was: 211352)
Time Spent: 4h 50m (was: 4h 40m)
> decrease the number of threads for BigQuery streaming insertAll
> ---------------------------------------------------------------
>
> Key: BEAM-6443
> URL: https://issues.apache.org/jira/browse/BEAM-6443
> Project: Beam
> Issue Type: Improvement
> Components: io-java-gcp
> Reporter: Heejong Lee
> Assignee: Heejong Lee
> Priority: Major
> Labels: triaged
> Time Spent: 4h 50m
> Remaining Estimate: 0h
>
> When inserting (a large number of ) very small elements into BigQuery via
> streaming insertAll, BigQueryIO causes lots of quota exceeded errors. This
> implies that 1) BigQueryIO puts unnecessary overheads on BigQuery API layer
> by sending requests too fast 2) log file becomes very big because of repeated
> same error messages. Currently we use 50 shards for writing data into
> BigQuery and in each bundle 20-30 futures are executed simultaneously with
> unlimited thread pool. It would be worth investigating whether just single
> thread pool is sufficient for running concurrent insertAll.
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