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https://issues.apache.org/jira/browse/BEAM-6443?focusedWorklogId=186518&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-186518
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ASF GitHub Bot logged work on BEAM-6443:
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Author: ASF GitHub Bot
Created on: 17/Jan/19 19:53
Start Date: 17/Jan/19 19:53
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-455309592
@reuvenlax From my observation, the level of parallelism is just too high
(50 shards * dozens of futures executed by unlimited thread pool). That's why
we're getting lots of quota exceeded errors even with exponential backoffs.
I've compared the numbers from four different scenarios (unlimited pool + high
volume, unlimited pool + high data size, single pool + high volume, single pool
+ high data size) and couldn't find any performance impact while removing
almost 75% of unnecessary requests). The link to the benchmark doc is here:
https://lists.apache.org/thread.html/b3586773e21fcdc80ad646dc548264f8690e99bbd289fc4973548658@%3Cdev.beam.apache.org%3E
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Issue Time Tracking
-------------------
Worklog Id: (was: 186518)
Time Spent: 1h (was: 50m)
> 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
> Time Spent: 1h
> 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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