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https://issues.apache.org/jira/browse/HADOOP-19737?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18039103#comment-18039103
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ASF GitHub Bot commented on HADOOP-19737:
-----------------------------------------
manika137 commented on code in PR #8056:
URL: https://github.com/apache/hadoop/pull/8056#discussion_r2537271997
##########
hadoop-tools/hadoop-azure/src/main/java/org/apache/hadoop/fs/azurebfs/WriteThreadPoolSizeManager.java:
##########
@@ -363,11 +443,18 @@ public ScheduledExecutorService getCpuMonitorExecutor() {
return cpuMonitorExecutor;
}
+ /**
+ * Checks if monitoring has started.
+ *
+ * @return true if monitoring has started, false otherwise.
+ */
+ public synchronized boolean isMonitoringStarted() {
+ return isMonitoringStarted;
+ }
+
/**
* Closes this manager by shutting down executors and cleaning up resources.
* Removes the instance from the active manager map.
- *
- * @throws IOException if an error occurs during shutdown.
Review Comment:
we are throwing this exception right?
> 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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