Hi Michael & Ayan, Thank you for your response to my problem.
Michael do we have a tentative release date for Spark version 1.4? Regards, Ishwardeep From: Michael Armbrust [mailto:[email protected]] Sent: Wednesday, May 13, 2015 10:54 PM To: ayan guha Cc: Ishwardeep Singh; user Subject: Re: [Spark SQL 1.3.1] data frame saveAsTable returns exception I think this is a bug in our date handling that should be fixed in Spark 1.4. On Wed, May 13, 2015 at 8:23 AM, ayan guha <[email protected]<mailto:[email protected]>> wrote: Your stack trace says it can't convert date to integer. You sure about column positions? On 13 May 2015 21:32, "Ishwardeep Singh" <[email protected]<mailto:[email protected]>> wrote: Hi , I am using Spark SQL 1.3.1. I have created a dataFrame using jdbc data source and am using saveAsTable() method but got the following 2 exceptions: java.lang.RuntimeException: Unsupported datatype DecimalType() at scala.sys.package$.error(package.scala:27) at org.apache.spark.sql.parquet.ParquetTypesConverter$$anonfun$fromDataType$2.apply(ParquetTypes.scala:372) at org.apache.spark.sql.parquet.ParquetTypesConverter$$anonfun$fromDataType$2.apply(ParquetTypes.scala:316) at scala.Option.getOrElse(Option.scala:120) at org.apache.spark.sql.parquet.ParquetTypesConverter$.fromDataType(ParquetTypes.scala:315) at org.apache.spark.sql.parquet.ParquetTypesConverter$$anonfun$4.apply(ParquetTypes.scala:395) at org.apache.spark.sql.parquet.ParquetTypesConverter$$anonfun$4.apply(ParquetTypes.scala:394) at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) at scala.collection.immutable.List.foreach(List.scala:318) at scala.collection.TraversableLike$class.map(TraversableLike.scala:244) at scala.collection.AbstractTraversable.map(Traversable.scala:105) at org.apache.spark.sql.parquet.ParquetTypesConverter$.convertFromAttributes(ParquetTypes.scala:393) at org.apache.spark.sql.parquet.ParquetTypesConverter$.writeMetaData(ParquetTypes.scala:440) at org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache.prepareMetadata(newParquet.scala:260) at org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache$$anonfun$6.apply(newParquet.scala:276) at org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache$$anonfun$6.apply(newParquet.scala:269) at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) at scala.collection.immutable.List.foreach(List.scala:318) at scala.collection.TraversableLike$class.map(TraversableLike.scala:244) at scala.collection.AbstractTraversable.map(Traversable.scala:105) at org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache.refresh(newParquet.scala:269) at org.apache.spark.sql.parquet.ParquetRelation2.<init>(newParquet.scala:391) at org.apache.spark.sql.parquet.DefaultSource.createRelation(newParquet.scala:98) at org.apache.spark.sql.parquet.DefaultSource.createRelation(newParquet.scala:128) at org.apache.spark.sql.sources.ResolvedDataSource$.apply(ddl.scala:240) at org.apache.spark.sql.hive.execution.CreateMetastoreDataSourceAsSelect.run(commands.scala:218) at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:54) at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:54) at org.apache.spark.sql.execution.ExecutedCommand.execute(commands.scala:64) at org.apache.spark.sql.SQLContext$QueryExecution.toRdd$lzycompute(SQLContext.scala:1099) at org.apache.spark.sql.SQLContext$QueryExecution.toRdd(SQLContext.scala:1099) at org.apache.spark.sql.DataFrame.saveAsTable(DataFrame.scala:1121) at org.apache.spark.sql.DataFrame.saveAsTable(DataFrame.scala:1071) at org.apache.spark.sql.DataFrame.saveAsTable(DataFrame.scala:1037) at org.apache.spark.sql.DataFrame.saveAsTable(DataFrame.scala:1015) java.lang.ClassCastException: java.sql.Date cannot be cast to java.lang.Integer at scala.runtime.BoxesRunTime.unboxToInt(BoxesRunTime.java:106) at org.apache.spark.sql.parquet.RowWriteSupport.writePrimitive(ParquetTableSupport.scala:215) at org.apache.spark.sql.parquet.RowWriteSupport.writeValue(ParquetTableSupport.scala:192) at org.apache.spark.sql.parquet.RowWriteSupport.write(ParquetTableSupport.scala:171) at org.apache.spark.sql.parquet.RowWriteSupport.write(ParquetTableSupport.scala:134) at parquet.hadoop.InternalParquetRecordWriter.write(InternalParquetRecordWriter.java:120) at parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:81) at parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:37) at org.apache.spark.sql.parquet.ParquetRelation2.org<http://org.apache.spark.sql.parquet.ParquetRelation2.org>$apache$spark$sql$parquet$ParquetRelation2$$writeShard$1(newParquet.scala:671) at org.apache.spark.sql.parquet.ParquetRelation2$$anonfun$insert$2.apply(newParquet.scala:689) at org.apache.spark.sql.parquet.ParquetRelation2$$anonfun$insert$2.apply(newParquet.scala:689) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61) at org.apache.spark.scheduler.Task.run(Task.scala:64) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:722) Earlier I was using Spark SQL 1.3.0 and was getting some other exception so I upgraded to 1.3.1 but got a different exception. Any help would be appreciated Regards, Ishwardeep -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Spark-SQL-1-3-1-data-frame-saveAsTable-returns-exception-tp22867.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected]<mailto:[email protected]> For additional commands, e-mail: [email protected]<mailto:[email protected]> ________________________________ NOTE: This message may contain information that is confidential, proprietary, privileged or otherwise protected by law. The message is intended solely for the named addressee. If received in error, please destroy and notify the sender. Any use of this email is prohibited when received in error. 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