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Rui Li commented on HIVE-8722: ------------------------------ Hi [~jxiang], yes I think data locality can have dramatic impact on performance. I saw nearly 2.5X difference in previous work (SPARK-1937). But I think we don't have to make {{CombineHiveInputSplit}} as {{InputSplitWithLocationInfo}} to get location info. {{CombineHiveInputSplit.getLocations}} can get what we need. {{InputSplitWithLocationInfo}} is only an enhancement to make cached replicas appear first in the location list (SPARK-1767). > Enhance InputSplitShims to extend InputSplitWithLocationInfo [Spark Branch] > --------------------------------------------------------------------------- > > Key: HIVE-8722 > URL: https://issues.apache.org/jira/browse/HIVE-8722 > Project: Hive > Issue Type: Sub-task > Reporter: Jimmy Xiang > > We got thie following exception in hive.log: > {noformat} > 2014-11-03 11:45:49,865 DEBUG rdd.HadoopRDD > (Logging.scala:logDebug(84)) - Failed to use InputSplitWithLocations. > java.lang.ClassCastException: Cannot cast > org.apache.hadoop.hive.ql.io.CombineHiveInputFormat$CombineHiveInputSplit > to org.apache.hadoop.mapred.InputSplitWithLocationInfo > at java.lang.Class.cast(Class.java:3094) > at > org.apache.spark.rdd.HadoopRDD.getPreferredLocations(HadoopRDD.scala:278) > at > org.apache.spark.rdd.RDD$$anonfun$preferredLocations$2.apply(RDD.scala:216) > at > org.apache.spark.rdd.RDD$$anonfun$preferredLocations$2.apply(RDD.scala:216) > at scala.Option.getOrElse(Option.scala:120) > at org.apache.spark.rdd.RDD.preferredLocations(RDD.scala:215) > at > org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal(DAGScheduler.scala:1303) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$2.apply$mcVI$sp(DAGScheduler.scala:1313) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$2.apply(DAGScheduler.scala:1312) > {noformat} > My understanding is that the split location info helps Spark to execute tasks > more efficiently. This could help other execution engine too. So we should > consider to enhance InputSplitShim to implement InputSplitWithLocationInfo if > possible. -- This message was sent by Atlassian JIRA (v6.3.4#6332)