[
https://issues.apache.org/jira/browse/SPARK-4740?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Zhang, Liye updated SPARK-4740:
-------------------------------
Attachment: Spark-perf Test Report 16 Cores per Executor.pdf
Hi [~rxin] [~adav], the difference between Netty and NIO is not that much when
each executor with 16 cores. Still Nio outperforms Netty, both in network
throughput and reduce running time. (In this case, Nio performance seems
limited to the CPU computing capacity, it's CPU bound)
> 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
> Attachments: 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
>
>
> 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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
