Eric Liang created SPARK-3349:
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Summary: [Spark SQL] Incorrect partitioning after LIMIT operator
Key: SPARK-3349
URL: https://issues.apache.org/jira/browse/SPARK-3349
Project: Spark
Issue Type: Bug
Reporter: Eric Liang
Reproduced by the following example:
import org.apache.spark.sql.catalyst.plans.Inner
import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute
import org.apache.spark.sql.catalyst.expressions._
val series = sql("select distinct year from sales order by year asc limit 10")
val results = sql("select * from sales")
series.registerTempTable("series")
results.registerTempTable("results")
sql("select * from results inner join series where results.year =
series.year").count
-----------
java.lang.IllegalArgumentException: Can't zip RDDs with unequal numbers of
partitions
at
org.apache.spark.rdd.ZippedPartitionsBaseRDD.getPartitions(ZippedPartitionsRDD.scala:56)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:204)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:202)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:202)
at
org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:204)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:202)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:202)
at
org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:204)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:202)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:202)
at
org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:204)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:202)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:202)
at org.apache.spark.ShuffleDependency.<init>(Dependency.scala:79)
at
org.apache.spark.rdd.ShuffledRDD.getDependencies(ShuffledRDD.scala:80)
at org.apache.spark.rdd.RDD$$anonfun$dependencies$2.apply(RDD.scala:191)
at org.apache.spark.rdd.RDD$$anonfun$dependencies$2.apply(RDD.scala:189)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.dependencies(RDD.scala:189)
at
org.apache.spark.scheduler.DAGScheduler.visit$1(DAGScheduler.scala:298)
at
org.apache.spark.scheduler.DAGScheduler.getParentStages(DAGScheduler.scala:310)
at
org.apache.spark.scheduler.DAGScheduler.newStage(DAGScheduler.scala:246)
at
org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:723)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1333)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at
akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at
scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at
scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at
scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
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