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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2016/04/07 14:27:25 UTC
[jira] [Resolved] (SPARK-13966) Regression using .withColumn() on a
parquet
[ https://issues.apache.org/jira/browse/SPARK-13966?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen resolved SPARK-13966.
-------------------------------
Resolution: Cannot Reproduce
(Unless we know a particular change fixed it, we use another resolution like can't reproduce)
> Regression using .withColumn() on a parquet
> -------------------------------------------
>
> Key: SPARK-13966
> URL: https://issues.apache.org/jira/browse/SPARK-13966
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.0
> Environment: Linux 3.16.0-4-amd64 #1 SMP Debian 3.16.7-ckt20-1+deb8u3 (2016-01-17) x86_64 GNU/Linux
> Reporter: Federico Ponzi
> Assignee: Davies Liu
> Priority: Critical
>
> If we load a parquet, add a column with {{withcolumn()}} with a date type and try to select a join of himself, we get a {{java.util.NoSuchElementException: key not found: key#6}}
> Here is a simple program to reproduce it:
> {code}
> from pyspark.sql import SQLContext, Row
> from pyspark import SparkContext
> from pyspark.sql.functions import from_unixtime, lit
> sc = SparkContext()
> sqlContext = SQLContext(sc)
> df = sqlContext.createDataFrame(sc.parallelize([Row(x=123)]))
> df.write.parquet("/tmp/testcase", mode="overwrite")
> df = sqlContext.read.parquet("/tmp/testcase")
> # df = df.unionAll(df.limit(0)) # WORKAROUND
> df = df.withColumn("key", from_unixtime(lit(1457650800))) # also happens with a .cast("timestamp")
> df.registerTempTable("test")
> res = sqlContext.sql("SELECT COUNT(1) from test t1, test t2 where t1.key = t2.key")
> res.show()
> {code}
> This only occurs when the added columns is of type timestamp, and dosen't happen in Spark 1.6.x
> {noformat}
> Traceback (most recent call last):
> File "/tmp/bug.py", line 17, in <module>
> res.show()
> File "/usr/local/spark/python/lib/pyspark.zip/pyspark/sql/dataframe.py", line 217, in show
> File "/usr/local/spark/python/lib/py4j-0.9.2-src.zip/py4j/java_gateway.py", line 836, in __call__
> File "/usr/local/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 45, in deco
> File "/usr/local/spark/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 o67.showString.
> : java.util.NoSuchElementException: key not found: key#6
> at scala.collection.MapLike$class.default(MapLike.scala:228)
> at org.apache.spark.sql.catalyst.expressions.AttributeMap.default(AttributeMap.scala:38)
> at scala.collection.MapLike$class.apply(MapLike.scala:141)
> at org.apache.spark.sql.catalyst.expressions.AttributeMap.apply(AttributeMap.scala:38)
> at org.apache.spark.sql.execution.datasources.DataSourceStrategy$$anonfun$35$$anonfun$apply$2.applyOrElse(DataSourceStrategy.scala:566)
> at org.apache.spark.sql.execution.datasources.DataSourceStrategy$$anonfun$35$$anonfun$apply$2.applyOrElse(DataSourceStrategy.scala:565)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:259)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:259)
> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:67)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:258)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:264)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:264)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:301)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:370)
> at scala.collection.Iterator$class.foreach(Iterator.scala:742)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1194)
> 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$class.to(TraversableOnce.scala:308)
> at scala.collection.AbstractIterator.to(Iterator.scala:1194)
> at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:300)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1194)
> at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:287)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1194)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:350)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:264)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:248)
> at org.apache.spark.sql.execution.datasources.DataSourceStrategy$$anonfun$35.apply(DataSourceStrategy.scala:565)
> at org.apache.spark.sql.execution.datasources.DataSourceStrategy$$anonfun$35.apply(DataSourceStrategy.scala:565)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> at scala.collection.immutable.List.map(List.scala:285)
> at org.apache.spark.sql.execution.datasources.DataSourceStrategy$.pruneFilterProjectRaw(DataSourceStrategy.scala:565)
> at org.apache.spark.sql.execution.datasources.DataSourceStrategy$.pruneFilterProject(DataSourceStrategy.scala:533)
> at org.apache.spark.sql.execution.datasources.DataSourceStrategy$.apply(DataSourceStrategy.scala:225)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:396)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at org.apache.spark.sql.execution.SparkStrategies$EquiJoinSelection$.apply(SparkStrategies.scala:114)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:396)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at org.apache.spark.sql.execution.SparkStrategies$BasicOperators$.apply(SparkStrategies.scala:342)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:396)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at org.apache.spark.sql.execution.SparkStrategies$Aggregation$.apply(SparkStrategies.scala:234)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:396)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at org.apache.spark.sql.execution.SparkStrategies$SpecialLimits$.apply(SparkStrategies.scala:52)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:396)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:52)
> at org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:50)
> at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:57)
> at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:57)
> at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2085)
> at org.apache.spark.sql.Dataset.head(Dataset.scala:1621)
> at org.apache.spark.sql.Dataset.take(Dataset.scala:1765)
> at org.apache.spark.sql.Dataset.showString(Dataset.scala:189)
> 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: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)
> {noformat}
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