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Posted to common-issues@hadoop.apache.org by "Sunil Govindan (JIRA)" <ji...@apache.org> on 2018/11/06 08:48:01 UTC
[jira] [Commented] (HADOOP-15703) ABFS - Implement client-side
throttling
[ https://issues.apache.org/jira/browse/HADOOP-15703?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16676358#comment-16676358 ]
Sunil Govindan commented on HADOOP-15703:
-----------------------------------------
Updated fixed version to 3.2.0 as HADOOP-15407 branch is merged to trunk
> ABFS - Implement client-side throttling
> ----------------------------------------
>
> Key: HADOOP-15703
> URL: https://issues.apache.org/jira/browse/HADOOP-15703
> Project: Hadoop Common
> Issue Type: Sub-task
> Reporter: Sneha Varma
> Assignee: Thomas Marquardt
> Priority: Major
> Fix For: 3.2.0
>
> Attachments: HADOOP-15703-HADOOP-15407-001.patch, HADOOP-15703-HADOOP-15407-002.patch, HADOOP-15703-HADOOP-15407-003.patch, HADOOP-15703-HADOOP-15407-004.patch
>
>
> Big data workloads frequently exceed the AzureBlobFS max ingress and egress limits (https://docs.microsoft.com/en-us/azure/storage/common/storage-scalability-targets). For example, the max ingress limit for a GRS account in the United States is currently 10 Gbps. When the limit is exceeded, the AzureBlobFS service fails a percentage of incoming requests, and this causes the client to initiate the retry policy. The retry policy delays requests by sleeping, but the sleep duration is independent of the client throughput and account limit. This results in low throughput, due to the high number of failed requests and thrashing causes by the retry policy.
> To fix this, we introduce a client-side throttle which minimizes failed requests and maximizes throughput.
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