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https://issues.apache.org/jira/browse/BEAM-6443?focusedWorklogId=197311&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-197311
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ASF GitHub Bot logged work on BEAM-6443:
----------------------------------------
Author: ASF GitHub Bot
Created on: 12/Feb/19 01:56
Start Date: 12/Feb/19 01:56
Worklog Time Spent: 10m
Work Description: ihji commented on pull request #7547: [BEAM-6443]
decrease the number of thread for BigQuery streaming inse…
URL: https://github.com/apache/beam/pull/7547#discussion_r255773236
##########
File path:
sdks/java/io/google-cloud-platform/src/main/java/org/apache/beam/sdk/io/gcp/bigquery/BigQueryServicesImpl.java
##########
@@ -945,4 +951,132 @@ public static CustomHttpErrors
createBigQueryClientCustomErrors() {
+
"https://cloud.google.com/service-infrastructure/docs/rate-limiting#configure";);
return builder.build();
}
+
+ private static class BoundedExecutorService implements ExecutorService {
+ private ExecutorService executor;
+ private Semaphore semaphore;
Review comment:
Thanks!
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Issue Time Tracking
-------------------
Worklog Id: (was: 197311)
Time Spent: 3h (was: 2h 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
> Labels: triaged
> Time Spent: 3h
> 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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