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Weiwei Yang resolved YARN-6289. ------------------------------- Resolution: Duplicate Fix Version/s: 2.9.0 3.0.0 > Fail to achieve data locality when runing MapReduce and Spark on HDFS > --------------------------------------------------------------------- > > Key: YARN-6289 > URL: https://issues.apache.org/jira/browse/YARN-6289 > Project: Hadoop YARN > Issue Type: Bug > Components: distributed-scheduling > Environment: Hardware configuration > CPU: 2 x Intel(R) Xeon(R) E5-2620 v2 @ 2.10GHz /15M Cache 6-Core 12-Thread > Memory: 128GB Memory (16x8GB) 1600MHz > Disk: 600GBx2 3.5-inch with RAID-1 > Network bandwidth: 968Mb/s > Software configuration > Spark-1.6.2 Hadoop-2.7.1 > Reporter: Huangkaixuan > Priority: Major > Fix For: 3.0.0, 2.9.0 > > Attachments: Hadoop_Spark_Conf.zip, YARN-DataLocality.docx, > YARN-RackAwareness.docx > > > When running a simple wordcount experiment on YARN, I noticed that the task > failed to achieve data locality, even though there is no other job running on > the cluster at the same time. The experiment was done in a 7-node (1 master, > 6 data nodes/node managers) cluster and the input of the wordcount job (both > Spark and MapReduce) is a single-block file in HDFS which is two-way > replicated (replication factor = 2). I ran wordcount on YARN for 10 times. > The results show that only 30% of tasks can achieve data locality, which > seems like the result of a random placement of tasks. The experiment details > are in the attachment, and feel free to reproduce the experiments. -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org