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https://issues.apache.org/jira/browse/BEAM-6443?focusedWorklogId=205448&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-205448
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ASF GitHub Bot logged work on BEAM-6443:
----------------------------------------
Author: ASF GitHub Bot
Created on: 27/Feb/19 23:04
Start Date: 27/Feb/19 23:04
Worklog Time Spent: 10m
Work Description: reuvenlax 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_r260980228
##########
File path:
sdks/java/io/google-cloud-platform/src/main/java/org/apache/beam/sdk/io/gcp/bigquery/BigQueryServicesImpl.java
##########
@@ -678,7 +683,8 @@ public void deleteDataset(String projectId, String
datasetId)
throws IOException, InterruptedException {
checkNotNull(ref, "ref");
if (executor == null) {
- this.executor = options.as(GcsOptions.class).getExecutorService();
+ this.executor =
+ new
BoundedExecutorService(options.as(GcsOptions.class).getExecutorService(), 3);
Review comment:
I meant the number of threads
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Issue Time Tracking
-------------------
Worklog Id: (was: 205448)
Time Spent: 3h 40m (was: 3.5h)
> 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 40m
> 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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