[
https://issues.apache.org/jira/browse/SPARK-4852?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14356173#comment-14356173
]
Kannan Rajah commented on SPARK-4852:
-------------------------------------
We are hitting this issue in a production case, not just test. spark-sql UDF
queries seem to trigger this code path. We are not using spark's version of
hive in this setup.
Example:
spark-sql> FROM src SELECT nvl(key, ' '), value;
15/03/09 18:28:23 ERROR SparkSQLDriver: Failed in [FROM src SELECT nvl(key, '
'), value]
java.lang.NoSuchMethodException:
org.apache.hadoop.hive.ql.exec.Utilities.deserializeObjectByKryo(com.esotericsoftware.kryo.Kryo,
java.io.InputStream, java.lang.Class)
at java.lang.Class.getDeclaredMethod(Class.java:2009)
at org.apache.spark.sql.hive.HiveFunctionWrapper.<init>(Shim13.scala:67)
org.apache.spark.sql.hive.HiveFunctionRegistry.lookupFunction(hiveUdfs.scala:59)
at
org.apache.spark.sql.hive.HiveContext$$anon$2.org$apache$spark$sql$catalyst$analysis$OverrideFunctionRegistry$$super$lookupFunction(HiveContext.scala:258)
at
org.apache.spark.sql.catalyst.analysis.OverrideFunctionRegistry$$anonfun$lookupFunction$2.apply(FunctionRegistry.scala:41)
at
org.apache.spark.sql.catalyst.analysis.OverrideFunctionRegistry$$anonfun$lookupFunction$2.apply(FunctionRegistry.scala:41)
at scala.Option.getOrElse(Option.scala:120)
at
org.apache.spark.sql.catalyst.analysis.OverrideFunctionRegistry$class.lookupFunction(FunctionRegistry.scala:41)
at
org.apache.spark.sql.hive.HiveContext$$anon$2.lookupFunction(HiveContext.scala:258)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$10$$anonfun$applyOrElse$2.applyOrElse(Analyzer.scala:220)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$10$$anonfun$applyOrElse$2.applyOrElse(Analyzer.scala:218)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:144)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:162)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at
scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
at
scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
at
scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at
scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
at
scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:191)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:147)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$transformExpressionDown$1(QueryPlan.scala:71)
at
org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$1$$anonfun$apply$1.apply(QueryPlan.scala:85)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at
scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.AbstractTraversable.map(Traversable.scala:105)
at
org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$1.apply(QueryPlan.scala:84)
at scala.collection.Iterator$$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)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
at
scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsDown(QueryPlan.scala:89)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressions(QueryPlan.scala:60)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$10.applyOrElse(Analyzer.scala:218)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$10.applyOrElse(Analyzer.scala:216)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:144)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:135)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$.apply(Analyzer.scala:216)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$.apply(Analyzer.scala:215)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:61)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:59)
at
scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111)
at scala.collection.immutable.List.foldLeft(List.scala:84)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:59)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:51)
at scala.collection.immutable.List.foreach(List.scala:318)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor.apply(RuleExecutor.scala:51)
at
org.apache.spark.sql.SQLContext$QueryExecution.analyzed$lzycompute(SQLContext.scala:411)
at
org.apache.spark.sql.SQLContext$QueryExecution.analyzed(SQLContext.scala:411)
at
org.apache.spark.sql.SQLContext$QueryExecution.withCachedData$lzycompute(SQLContext.scala:412)
at
org.apache.spark.sql.SQLContext$QueryExecution.withCachedData(SQLContext.scala:412)
at
org.apache.spark.sql.SQLContext$QueryExecution.optimizedPlan$lzycompute(SQLContext.scala:413)
at
org.apache.spark.sql.SQLContext$QueryExecution.optimizedPlan(SQLContext.scala:413)
at
org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan$lzycompute(SQLContext.scala:418)
at
org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan(SQLContext.scala:416)
at
org.apache.spark.sql.SQLContext$QueryExecution.executedPlan$lzycompute(SQLContext.scala:422)
at
org.apache.spark.sql.SQLContext$QueryExecution.executedPlan(SQLContext.scala:422)
at
org.apache.spark.sql.hive.HiveContext$QueryExecution.stringResult(HiveContext.scala:371)
at
org.apache.spark.sql.hive.thriftserver.AbstractSparkSQLDriver.run(AbstractSparkSQLDriver.scala:57)
at
org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:275)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:423)
at
org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.main(SparkSQLCLIDriver.scala:211)
at
org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.main(SparkSQLCLIDriver.scala)
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 org.apache.spark.deploy.SparkSubmit$.launch(SparkSubmit.scala:358)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:75)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
> Hive query plan deserialization failure caused by shaded hive-exec jar file
> when generating golden answers
> ----------------------------------------------------------------------------------------------------------
>
> Key: SPARK-4852
> URL: https://issues.apache.org/jira/browse/SPARK-4852
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.2.0
> Reporter: Cheng Lian
> Priority: Minor
>
> When adding Hive 0.13.1 support for Spark SQL Thrift server in PR
> [2685|https://github.com/apache/spark/pull/2685], Kryo 2.22 used by original
> hive-exec-0.13.1.jar was shaded by Kryo 2.21 used by Spark SQL because of
> dependency hell. Unfortunately, Kryo 2.21 has a known bug that may cause Hive
> query plan deserialization failure. This bug was fixed in Kryo 2.22.
> Normally, this issue doesn't affect Spark SQL because we don't even generate
> Hive query plan. But when running Hive test suites like
> {{HiveCompatibilitySuite}}, golden answer files must be generated by Hive,
> and thus triggers this issue. A workaround is to replace
> {{hive-exec-0.13.1.jar}} under {{$HIVE_HOME/lib}} with Spark's
> {{hive-exec-0.13.1a.jar}} and {{kryo-2.21.jar}} under
> {{$SPARK_DEV_HOME/lib_managed/jars}}. Then add {{$HIVE_HOME/lib}} to
> {{$HADOOP_CLASSPATH}}.
> Upgrading to some newer version of Kryo which is binary compatible with Kryo
> 2.22 (if there is one) may fix this issue.
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