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Posted to issues@spark.apache.org by "Davies Liu (JIRA)" <ji...@apache.org> on 2015/08/07 01:30:04 UTC
[jira] [Updated] (SPARK-3033) [Hive] java.math.BigDecimal cannot be
cast to org.apache.hadoop.hive.common.type.HiveDecimal
[ https://issues.apache.org/jira/browse/SPARK-3033?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Davies Liu updated SPARK-3033:
------------------------------
Assignee: Yin Huai
> [Hive] java.math.BigDecimal cannot be cast to org.apache.hadoop.hive.common.type.HiveDecimal
> --------------------------------------------------------------------------------------------
>
> Key: SPARK-3033
> URL: https://issues.apache.org/jira/browse/SPARK-3033
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.0.2
> Reporter: pengyanhong
> Assignee: Yin Huai
>
> run a complex HiveQL via yarn-cluster, got error as below:
> {quote}
> 14/08/14 15:05:24 WARN org.apache.spark.Logging$class.logWarning(Logging.scala:70): Loss was due to java.lang.ClassCastException
> java.lang.ClassCastException: java.math.BigDecimal cannot be cast to org.apache.hadoop.hive.common.type.HiveDecimal
> at org.apache.hadoop.hive.serde2.objectinspector.primitive.JavaHiveDecimalObjectInspector.getPrimitiveJavaObject(JavaHiveDecimalObjectInspector.java:51)
> at org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorUtils.getHiveDecimal(PrimitiveObjectInspectorUtils.java:1022)
> at org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorConverter$HiveDecimalConverter.convert(PrimitiveObjectInspectorConverter.java:306)
> at org.apache.hadoop.hive.ql.udf.generic.GenericUDFUtils$ReturnObjectInspectorResolver.convertIfNecessary(GenericUDFUtils.java:179)
> at org.apache.hadoop.hive.ql.udf.generic.GenericUDFIf.evaluate(GenericUDFIf.java:82)
> at org.apache.spark.sql.hive.HiveGenericUdf.eval(hiveUdfs.scala:276)
> at org.apache.spark.sql.catalyst.expressions.Alias.eval(namedExpressions.scala:84)
> at org.apache.spark.sql.catalyst.expressions.MutableProjection.apply(Projection.scala:62)
> at org.apache.spark.sql.catalyst.expressions.MutableProjection.apply(Projection.scala:51)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at org.apache.spark.sql.execution.BroadcastNestedLoopJoin$$anonfun$4.apply(joins.scala:309)
> at org.apache.spark.sql.execution.BroadcastNestedLoopJoin$$anonfun$4.apply(joins.scala:303)
> at org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:571)
> at org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:571)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> at org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
> at org.apache.spark.scheduler.Task.run(Task.scala:51)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:183)
> at java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908)
> at java.lang.Thread.run(Thread.java:662)
> {quote}
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