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https://issues.apache.org/jira/browse/HADOOP-19737?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18040973#comment-18040973
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ASF GitHub Bot commented on HADOOP-19737:
-----------------------------------------
anmolanmol1234 commented on code in PR #8056:
URL: https://github.com/apache/hadoop/pull/8056#discussion_r2567382383
##########
hadoop-tools/hadoop-azure/src/main/java/org/apache/hadoop/fs/azurebfs/services/AbfsDfsClient.java:
##########
@@ -1080,7 +1080,12 @@ public AbfsRestOperation read(final String path,
String sasTokenForReuse = appendSASTokenToQuery(path,
SASTokenProvider.READ_OPERATION,
abfsUriQueryBuilder, cachedSasToken);
-
+ // Retrieve the read thread pool metrics from the ABFS counters.
+ AbfsReadResourceUtilizationMetrics readResourceUtilizationMetrics =
retrieveReadResourceUtilizationMetrics();
Review Comment:
already defined the common method retrieveReadResourceUtilizationMetrics in
abfs client class, tracing context changes we always do in respective client
methods only as per the previous API's. Can take this up if still needed
> ABFS: Add metrics to identify improvements with read and write aggressiveness
> -----------------------------------------------------------------------------
>
> Key: HADOOP-19737
> URL: https://issues.apache.org/jira/browse/HADOOP-19737
> Project: Hadoop Common
> Issue Type: Sub-task
> Components: fs/azure
> Affects Versions: 3.5.0, 3.4.2
> Reporter: Anmol Asrani
> Assignee: Anmol Asrani
> Priority: Major
> Labels: pull-request-available
>
> Introduces new performance metrics in the ABFS driver to monitor and evaluate
> the effectiveness of read and write aggressiveness tuning. These metrics help
> in understanding how thread pool behavior, CPU utilization, and heap
> availability impact overall I/O throughput and latency. By capturing detailed
> statistics such as active thread count, pool size, and system resource
> utilization, this enhancement enables data-driven analysis of optimizations
> made to improve ABFS read and write performance under varying workloads.
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