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Posted to issues@spark.apache.org by "Reynold Xin (JIRA)" <ji...@apache.org> on 2016/05/12 20:57:13 UTC
[jira] [Resolved] (SPARK-15293) 'collect_list' function undefined
[ https://issues.apache.org/jira/browse/SPARK-15293?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Reynold Xin resolved SPARK-15293.
---------------------------------
Resolution: Fixed
Assignee: Herman van Hovell
Fix Version/s: 2.0.0
I'm going to mark this one as resolved because it should be fixed by https://github.com/apache/spark/pull/12874
If it doesn't work, please reopen the ticket. Thanks.
> 'collect_list' function undefined
> ---------------------------------
>
> Key: SPARK-15293
> URL: https://issues.apache.org/jira/browse/SPARK-15293
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Affects Versions: 2.0.0
> Reporter: Piotr Milanowski
> Assignee: Herman van Hovell
> Fix For: 2.0.0
>
>
> When using pyspark.sql.functions.collect_list function in sql queries, an error occurs - Undefined function collect_list
> Example:
> {code}
> >>> from pyspark.sql import Row
> >>> #The same with SQLContext
> >>> from pyspark.sql import HiveContext
> >>> from pyspark.sql.functions import collect_list
> >>> sql = HiveContext(sc)
> >>> rows = [Row(age=20, job='Programmer', name='Alice'), Row(age=21, job='Programmer', name='Bob'), Row(age=30, job='Hacker', name='Fred'), Row(age=29, job='PM', name='Tom'), Row(age=50, job='CEO', name='Daisy')]
> >>> df = sql.createDataFrame(rows)
> >>> df.groupby(df.job).agg(df.job, collect_list(df.age))
> Traceback (most recent call last):
> File "/mnt/mfs/spark-2.0/python/pyspark/sql/utils.py", line 57, in deco
> return f(*a, **kw)
> File "/mnt/mfs/spark-2.0/python/lib/py4j-0.9.2-src.zip/py4j/protocol.py", line 310, in get_return_value
> py4j.protocol.Py4JJavaError: An error occurred while calling o193.agg.
> : org.apache.spark.sql.AnalysisException: Undefined function: 'collect_list'. This function is neither a registered temporary function nor a permanent function registered in the database 'default'.;
> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.failFunctionLookup(SessionCatalog.scala:719)
> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.lookupFunction(SessionCatalog.scala:781)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$13$$anonfun$applyOrElse$6$$anonfun$applyOrElse$38.apply(Analyzer.scala:907)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$13$$anonfun$applyOrElse$6$$anonfun$applyOrElse$38.apply(Analyzer.scala:907)
> at org.apache.spark.sql.catalyst.analysis.package$.withPosition(package.scala:48)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$13$$anonfun$applyOrElse$6.applyOrElse(Analyzer.scala:906)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$13$$anonfun$applyOrElse$6.applyOrElse(Analyzer.scala:894)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:265)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:265)
> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:68)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:264)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:270)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:270)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:307)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
> at scala.collection.Iterator$class.foreach(Iterator.scala:893)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
> at scala.collection.AbstractIterator.to(Iterator.scala:1336)
> at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1336)
> at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1336)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:356)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:270)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionDown$1(QueryPlan.scala:156)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1(QueryPlan.scala:166)
> at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1$1.apply(QueryPlan.scala:170)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> at scala.collection.AbstractTraversable.map(Traversable.scala:104)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1(QueryPlan.scala:170)
> at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$4.apply(QueryPlan.scala:175)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
> at scala.collection.Iterator$class.foreach(Iterator.scala:893)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
> at scala.collection.AbstractIterator.to(Iterator.scala:1336)
> at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1336)
> at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1336)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsDown(QueryPlan.scala:175)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressions(QueryPlan.scala:144)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$13.applyOrElse(Analyzer.scala:894)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$13.applyOrElse(Analyzer.scala:892)
> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:68)
> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$.apply(Analyzer.scala:892)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$.apply(Analyzer.scala:891)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:85)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:82)
> at scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:82)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:74)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74)
> at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:64)
> at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:62)
> at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:50)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:61)
> at org.apache.spark.sql.RelationalGroupedDataset.toDF(RelationalGroupedDataset.scala:55)
> at org.apache.spark.sql.RelationalGroupedDataset.agg(RelationalGroupedDataset.scala:211)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
> at py4j.Gateway.invoke(Gateway.java:290)
> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
> at py4j.commands.CallCommand.execute(CallCommand.java:79)
> at py4j.GatewayConnection.run(GatewayConnection.java:209)
> at java.lang.Thread.run(Thread.java:745)
> During handling of the above exception, another exception occurred:
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File "/mnt/mfs/spark-2.0/python/pyspark/sql/group.py", line 91, in agg
> _to_seq(self.sql_ctx._sc, [c._jc for c in exprs[1:]]))
> File "/mnt/mfs/spark-2.0/python/lib/py4j-0.9.2-src.zip/py4j/java_gateway.py", line 836, in __call__
> File "/mnt/mfs/spark-2.0/python/pyspark/sql/utils.py", line 63, in deco
> raise AnalysisException(s.split(': ', 1)[1], stackTrace)
> pyspark.sql.utils.AnalysisException: "Undefined function: 'collect_list'. This function is neither a registered temporary function nor a permanent function registered in the database 'default'.;"
> {code}
> Using branch-2.0, works with spark 1.6
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