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https://issues.apache.org/jira/browse/HADOOP-19737?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18040975#comment-18040975
]
ASF GitHub Bot commented on HADOOP-19737:
-----------------------------------------
anmolanmol1234 commented on code in PR #8056:
URL: https://github.com/apache/hadoop/pull/8056#discussion_r2567387362
##########
hadoop-tools/hadoop-azure/src/main/java/org/apache/hadoop/fs/azurebfs/utils/TracingContext.java:
##########
@@ -226,28 +236,22 @@ public void constructHeader(AbfsHttpOperation
httpOperation, String previousFail
+ position + COLON
+ operatedBlobCount + COLON
+ getOperationSpecificHeader(opType) + COLON
- + httpOperation.getTracingContextSuffix();
-
- metricHeader += !(metricResults.trim().isEmpty()) ? metricResults :
EMPTY_STRING;
+ + httpOperation.getTracingContextSuffix() + COLON
+ + metricResults + COLON + resourceUtilizationMetricResults;
break;
case TWO_ID_FORMAT:
header = TracingHeaderVersion.getCurrentVersion() + COLON
+ clientCorrelationID + COLON + clientRequestId;
- metricHeader += !(metricResults.trim().isEmpty()) ? metricResults :
EMPTY_STRING;
Review Comment:
So, the metricResults would be empty string unless anything added to it. As
per latest version changes it should either be some string, else emptyString.
Hence, I made this change:- metricResults + COLON +
resourceUtilizationMetricResults;
> 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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