[jira] [Created] (SPARK-3349) [Spark SQL] Incorrect partitioning after LIMIT operator

["Eric Liang (JIRA)" <ji...@apache.org>]

Eric Liang created SPARK-3349:
---------------------------------

             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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