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https://issues.apache.org/jira/browse/HADOOP-19737?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18040988#comment-18040988
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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_r2567557596
##########
hadoop-tools/hadoop-azure/src/main/java/org/apache/hadoop/fs/azurebfs/services/AbfsOutputStream.java:
##########
@@ -242,6 +253,18 @@ public AzureIngressHandler getIngressHandler() {
private volatile boolean switchCompleted = false;
+ /**
+ * Starts CPU monitoring in the thread pool size manager if it
+ * is initialized and not already monitoring.
+ */
+ private void initializeMonitoringIfNeeded() {
+ if (poolSizeManager != null && !poolSizeManager.isMonitoringStarted()) {
+ synchronized (this) {
+ poolSizeManager.startCPUMonitoring();
+ }
+ }
+ }
Review Comment:
Yes, once the common shared pool design is ready, we will accomodate this
change as part of that
> 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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