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Mingliang Liu commented on SPARK-20608: --------------------------------------- Quick question [~charliechen] : I think [~vanzin] is suggesting that we simply use the logical HDFS namespace instead of specific NNs. Say {{dfs.nameservices=mycluster}}, then {{hdfs://mycluster}} is what you need as NN endpoint, instead of the specific namenodes (e.g. {{dfs.ha.namenodes.mycluste=nn1,nn2}}, you want to use {{hdfs://nn1}} and {{hdfs://nn2}} directly). > Standby namenodes should be allowed to included in > yarn.spark.access.namenodes to support HDFS HA > ------------------------------------------------------------------------------------------------- > > Key: SPARK-20608 > URL: https://issues.apache.org/jira/browse/SPARK-20608 > Project: Spark > Issue Type: Improvement > Components: Spark Submit, YARN > Affects Versions: 2.0.1, 2.1.0 > Reporter: Yuechen Chen > Priority: Minor > Original Estimate: 672h > Remaining Estimate: 672h > > If one Spark Application need to access remote namenodes, > yarn.spark.access.namenodes should be only be configged in spark-submit > scripts, and Spark Client(On Yarn) would fetch HDFS credential periodically. > If one hadoop cluster is configured by HA, there would be one active namenode > and at least one standby namenode. > However, if yarn.spark.access.namenodes includes both active and standby > namenodes, Spark Application will be failed for the reason that the standby > namenode would not access by Spark for org.apache.hadoop.ipc.StandbyException. > I think it won't cause any bad effect to config standby namenodes in > yarn.spark.access.namenodes, and my Spark Application can be able to sustain > the failover of Hadoop namenode. > HA Examples: > Spark-submit script: > yarn.spark.access.namenodes=hdfs://namenode01,hdfs://namenode02 > Spark Application Codes: > dataframe.write.parquet(getActiveNameNode(...) + hdfsPath) -- This message was sent by Atlassian JIRA (v6.3.15#6346) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org