You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Reynold Xin (JIRA)" <ji...@apache.org> on 2015/07/21 04:07:04 UTC
[jira] [Updated] (SPARK-9183) NPE / confusing error message when
looking up missing function in Spark SQL
[ https://issues.apache.org/jira/browse/SPARK-9183?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Reynold Xin updated SPARK-9183:
-------------------------------
Priority: Blocker (was: Major)
> NPE / confusing error message when looking up missing function in Spark SQL
> ---------------------------------------------------------------------------
>
> Key: SPARK-9183
> URL: https://issues.apache.org/jira/browse/SPARK-9183
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.4.1, 1.5.0
> Reporter: Josh Rosen
> Priority: Blocker
>
> Try running the following query in Spark Shell with Hive enabled:
> {code}
> sqlContext.sql("""select substr("abc", 0, len("ab") - 1)""")
> {code}
> This query is malformed since there's no {{len}} UDF. Unfortunately, though, this gives a really confusing error as of Spark 1.4:
> {code}
> : java.lang.NullPointerException
> at org.apache.hadoop.hive.ql.exec.FunctionRegistry.getFunctionInfo(FunctionRegistry.java:643)
> at org.apache.hadoop.hive.ql.exec.FunctionRegistry.getFunctionInfo(FunctionRegistry.java:652)
> at org.apache.spark.sql.hive.HiveFunctionRegistry.lookupFunction(hiveUdfs.scala:54)
> at org.apache.spark.sql.hive.HiveContext$$anon$3.org$apache$spark$sql$catalyst$analysis$OverrideFunctionRegistry$$super$lookupFunction(HiveContext.scala:380)
> at org.apache.spark.sql.catalyst.analysis.OverrideFunctionRegistry$$anonfun$lookupFunction$2.apply(FunctionRegistry.scala:44)
> at org.apache.spark.sql.catalyst.analysis.OverrideFunctionRegistry$$anonfun$lookupFunction$2.apply(FunctionRegistry.scala:44)
> at scala.Option.getOrElse(Option.scala:120)
> at org.apache.spark.sql.catalyst.analysis.OverrideFunctionRegistry$class.lookupFunction(FunctionRegistry.scala:44)
> at org.apache.spark.sql.hive.HiveContext$$anon$3.lookupFunction(HiveContext.scala:380)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$13$$anonfun$applyOrElse$5.applyOrElse(Analyzer.scala:465)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$13$$anonfun$applyOrElse$5.applyOrElse(Analyzer.scala:463)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:222)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:222)
> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:51)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:221)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:242)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> [...]
> {code}
> In Spark 1.3, on the other hand, this gives a helpful message:
> {code}
> : java.lang.RuntimeException: Couldn't find function len
> at scala.sys.package$.error(package.scala:27)
> at org.apache.spark.sql.hive.HiveFunctionRegistry$$anonfun$1.apply(hiveUdfs.scala:55)
> at org.apache.spark.sql.hive.HiveFunctionRegistry$$anonfun$1.apply(hiveUdfs.scala:55)
> at scala.Option.getOrElse(Option.scala:120)
> at org.apache.spark.sql.hive.HiveFunctionRegistry.lookupFunction(hiveUdfs.scala:54)
> at org.apache.spark.sql.hive.HiveContext$$anon$4.org$apache$spark$sql$catalyst$analysis$OverrideFunctionRegistry$$super$lookupFunction(HiveContext.scala:267)
> at org.apache.spark.sql.catalyst.analysis.OverrideFunctionRegistry$$anonfun$lookupFunction$2.apply(FunctionRegistry.scala:43)
> at org.apache.spark.sql.catalyst.analysis.OverrideFunctionRegistry$$anonfun$lookupFunction$2.apply(FunctionRegistry.scala:43)
> at scala.Option.getOrElse(Option.scala:120)
> at org.apache.spark.sql.catalyst.analysis.OverrideFunctionRegistry$class.lookupFunction(FunctionRegistry.scala:43)
> at org.apache.spark.sql.hive.HiveContext$$anon$4.lookupFunction(HiveContext.scala:267)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$12$$anonfun$applyOrElse$3.applyOrElse(Analyzer.scala:431)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$12$$anonfun$applyOrElse$3.applyOrElse(Analyzer.scala:429)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:188)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:188)
> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:51)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:187)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:208)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> [...]
> {code}
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org