[ https://issues.apache.org/jira/browse/SPARK-22249?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen resolved SPARK-22249. ------------------------------- Resolution: Fixed Resolved by https://github.com/apache/spark/pull/19494 > UnsupportedOperationException: empty.reduceLeft when caching a dataframe > ------------------------------------------------------------------------ > > Key: SPARK-22249 > URL: https://issues.apache.org/jira/browse/SPARK-22249 > Project: Spark > Issue Type: Bug > Components: PySpark > Affects Versions: 2.1.1, 2.2.0 > Environment: $ uname -a > Darwin MAC-UM-024.local 16.7.0 Darwin Kernel Version 16.7.0: Thu Jun 15 > 17:36:27 PDT 2017; root:xnu-3789.70.16~2/RELEASE_X86_64 x86_64 > $ pyspark --version > Welcome to > ____ __ > / __/__ ___ _____/ /__ > _\ \/ _ \/ _ `/ __/ '_/ > /___/ .__/\_,_/_/ /_/\_\ version 2.2.0 > /_/ > > Using Scala version 2.11.8, Java HotSpot(TM) 64-Bit Server VM, 1.8.0_92 > Branch > Compiled by user jenkins on 2017-06-30T22:58:04Z > Revision > Url > Reporter: Andreas Maier > Assignee: Marco Gaido > Fix For: 2.2.1, 2.3.0 > > > It seems that the {{isin()}} method with an empty list as argument only > works, if the dataframe is not cached. If it is cached, it results in an > exception. To reproduce > {code:java} > $ pyspark > >>> df = spark.createDataFrame([pyspark.Row(KEY="value")]) > >>> df.where(df["KEY"].isin([])).show() > +---+ > |KEY| > +---+ > +---+ > >>> df.cache() > DataFrame[KEY: string] > >>> df.where(df["KEY"].isin([])).show() > Traceback (most recent call last): > File "<stdin>", line 1, in <module> > File > "/usr/local/anaconda3/envs/<myenv>/lib/python3.6/site-packages/pyspark/sql/dataframe.py", > line 336, in show > print(self._jdf.showString(n, 20)) > File > "/usr/local/anaconda3/envs/<myenv>/lib/python3.6/site-packages/pyspark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", > line 1133, in __call__ > File > "/usr/local/anaconda3/envs/<myenv>/lib/python3.6/site-packages/pyspark/sql/utils.py", > line 63, in deco > return f(*a, **kw) > File > "/usr/local/anaconda3/envs/<myenv>/lib/python3.6/site-packages/pyspark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py", > line 319, in get_return_value > py4j.protocol.Py4JJavaError: An error occurred while calling o302.showString. > : java.lang.UnsupportedOperationException: empty.reduceLeft > at > scala.collection.TraversableOnce$class.reduceLeft(TraversableOnce.scala:180) > at > scala.collection.mutable.ArrayBuffer.scala$collection$IndexedSeqOptimized$$super$reduceLeft(ArrayBuffer.scala:48) > at > scala.collection.IndexedSeqOptimized$class.reduceLeft(IndexedSeqOptimized.scala:74) > at scala.collection.mutable.ArrayBuffer.reduceLeft(ArrayBuffer.scala:48) > at > scala.collection.TraversableOnce$class.reduce(TraversableOnce.scala:208) > at scala.collection.AbstractTraversable.reduce(Traversable.scala:104) > at > org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$1.applyOrElse(InMemoryTableScanExec.scala:107) > at > org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$1.applyOrElse(InMemoryTableScanExec.scala:71) > at scala.PartialFunction$Lifted.apply(PartialFunction.scala:223) > at scala.PartialFunction$Lifted.apply(PartialFunction.scala:219) > at > org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$2.apply(InMemoryTableScanExec.scala:112) > at > org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$2.apply(InMemoryTableScanExec.scala:111) > at > scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241) > at > scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241) > at scala.collection.immutable.List.foreach(List.scala:381) > at > scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241) > at scala.collection.immutable.List.flatMap(List.scala:344) > at > org.apache.spark.sql.execution.columnar.InMemoryTableScanExec.<init>(InMemoryTableScanExec.scala:111) > at > org.apache.spark.sql.execution.SparkStrategies$InMemoryScans$$anonfun$3.apply(SparkStrategies.scala:307) > at > org.apache.spark.sql.execution.SparkStrategies$InMemoryScans$$anonfun$3.apply(SparkStrategies.scala:307) > at > org.apache.spark.sql.execution.SparkPlanner.pruneFilterProject(SparkPlanner.scala:99) > at > org.apache.spark.sql.execution.SparkStrategies$InMemoryScans$.apply(SparkStrategies.scala:303) > at > org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:62) > at > org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:62) > at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434) > at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440) > at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439) > at > org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:92) > at > org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2$$anonfun$apply$2.apply(QueryPlanner.scala:77) > at > org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2$$anonfun$apply$2.apply(QueryPlanner.scala:74) > at > scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157) > at > scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157) > at scala.collection.Iterator$class.foreach(Iterator.scala:893) > at scala.collection.AbstractIterator.foreach(Iterator.scala:1336) > at > scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:157) > at scala.collection.AbstractIterator.foldLeft(Iterator.scala:1336) > at > org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2.apply(QueryPlanner.scala:74) > at > org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2.apply(QueryPlanner.scala:66) > at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434) > at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440) > at > org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:92) > at > org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:84) > at > org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:80) > at > org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:89) > at > org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:89) > at org.apache.spark.sql.Dataset.withAction(Dataset.scala:2832) > at org.apache.spark.sql.Dataset.head(Dataset.scala:2153) > at org.apache.spark.sql.Dataset.take(Dataset.scala:2366) > at org.apache.spark.sql.Dataset.showString(Dataset.scala:245) > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) > at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) > at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) > at java.lang.reflect.Method.invoke(Method.java:498) > at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) > at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) > at py4j.Gateway.invoke(Gateway.java:280) > at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) > at py4j.commands.CallCommand.execute(CallCommand.java:79) > at py4j.GatewayConnection.run(GatewayConnection.java:214) > at java.lang.Thread.run(Thread.java:745) > {code} -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org