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https://issues.apache.org/jira/browse/SPARK-4740?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14245040#comment-14245040
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Jie Huang commented on SPARK-4740:
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At the very beginning, we also suspected if it was an concurrent issue. On
Friday, [~liyezhang556520] has re-conducted the test with 8 executors (Each
node has 2 executos with 48 cores respectively). So that all those 8 HDDs on a
single node can have more IO request concurrently. Unfortunately, there is no
difference(even with more IO loads). The only thing we found is the waitio is
higher than before(single executor case). That's why we are asking about if
there is any IO access pattern change.
> Netty's network throughput is about 1/2 of NIO's in spark-perf sortByKey
> ------------------------------------------------------------------------
>
> Key: SPARK-4740
> URL: https://issues.apache.org/jira/browse/SPARK-4740
> Project: Spark
> Issue Type: Improvement
> Components: Shuffle, Spark Core
> Affects Versions: 1.2.0
> Reporter: Zhang, Liye
> Assignee: Reynold Xin
> Attachments: (rxin patch better executor)TestRunner sort-by-key -
> Thread dump for executor 3_files.zip, (rxin patch normal executor)TestRunner
> sort-by-key - Thread dump for executor 0 _files.zip, Spark-perf Test Report
> 16 Cores per Executor.pdf, Spark-perf Test Report.pdf, TestRunner
> sort-by-key - Thread dump for executor 1_files (Netty-48 Cores per node).zip,
> TestRunner sort-by-key - Thread dump for executor 1_files (Nio-48 cores per
> node).zip, rxin_patch-on_4_node_cluster_48CoresPerNode(Unbalance).7z
>
>
> When testing current spark master (1.3.0-snapshot) with spark-perf
> (sort-by-key, aggregate-by-key, etc), Netty based shuffle transferService
> takes much longer time than NIO based shuffle transferService. The network
> throughput of Netty is only about half of that of NIO.
> We tested with standalone mode, and the data set we used for test is 20
> billion records, and the total size is about 400GB. Spark-perf test is
> Running on a 4 node cluster with 10G NIC, 48 cpu cores per node and each
> executor memory is 64GB. The reduce tasks number is set to 1000.
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