[jira] [Updated] (SPARK-6360) For Spark 1.1 and 1.2, after any RDD transformations, calling saveAsParquetFile over a SchemaRDD with decimal or UDT column throws

2015-08-07 Thread Sean Owen (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-6360?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Sean Owen updated SPARK-6360:
-
Assignee: Davies Liu

> For Spark 1.1 and 1.2, after any RDD transformations, calling 
> saveAsParquetFile over a SchemaRDD with decimal or UDT column throws
> --
>
> Key: SPARK-6360
> URL: https://issues.apache.org/jira/browse/SPARK-6360
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 1.1.0, 1.2.0
>Reporter: Cheng Lian
>Assignee: Davies Liu
> Fix For: 1.5.0
>
>
> Spark shell session for reproduction (use {{:paste}}):
> {noformat}
> import org.apache.spark.sql.SQLContext
> import org.apache.spark.sql.catalyst.types.decimal._
> import org.apache.spark.sql.catalyst.types._
> import org.apache.hadoop.fs._
> val sqlContext = new SQLContext(sc)
> val fs = FileSystem.get(sc.hadoopConfiguration)
> fs.delete(new Path("a.parquet"))
> fs.delete(new Path("b.parquet"))
> import sc._
> import sqlContext._
> val r1 = parallelize(1 to 10).map(i => Tuple1(Decimal(i, 10, 0))).select('_1 
> cast DecimalType(10, 0))
> // OK
> r1.saveAsParquetFile("a.parquet")
> val r2 = parallelize(1 to 10).map(i => Tuple1(Decimal(i, 10, 0))).select('_1 
> cast DecimalType(10, 0))
> val r3 = r2.coalesce(1)
> // Error
> r3.saveAsParquetFile("b.parquet")
> {noformat}
> Exception thrown:
> {noformat}
> java.lang.ClassCastException: scala.math.BigDecimal cannot be cast to 
> org.apache.spark.sql.catalyst.types.decimal.Decimal
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.consumeType(ParquetTableSupport.scala:359)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:328)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:314)
> 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.InsertIntoParquetTable.org$apache$spark$sql$parquet$InsertIntoParquetTable$$writeShard$1(ParquetTableOperations.scala:308)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at 
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
> at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> 15/03/17 00:04:13 WARN TaskSetManager: Lost task 0.0 in stage 2.0 (TID 2, 
> localhost): java.lang.ClassCastException: scala.math.BigDecimal cannot be 
> cast to org.apache.spark.sql.catalyst.types.decimal.Decimal
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.consumeType(ParquetTableSupport.scala:359)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:328)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:314)
> at 
> parquet.hadoop.InternalParquetRecordWriter.write(InternalParquetRecordWriter.java:120)
> at 
> parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:81)
> at 
> parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:37)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable.org$apache$spark$sql$parquet$InsertIntoParquetTable$$writeShard$1(ParquetTableOperations.scala:308)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at 
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
> at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> {noformat

[jira] [Updated] (SPARK-6360) For Spark 1.1 and 1.2, after any RDD transformations, calling saveAsParquetFile over a SchemaRDD with decimal or UDT column throws

2015-08-06 Thread Davies Liu (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-6360?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Davies Liu updated SPARK-6360:
--
Target Version/s:   (was: 1.2.3)

> For Spark 1.1 and 1.2, after any RDD transformations, calling 
> saveAsParquetFile over a SchemaRDD with decimal or UDT column throws
> --
>
> Key: SPARK-6360
> URL: https://issues.apache.org/jira/browse/SPARK-6360
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 1.1.0, 1.2.0
>Reporter: Cheng Lian
> Fix For: 1.5.0
>
>
> Spark shell session for reproduction (use {{:paste}}):
> {noformat}
> import org.apache.spark.sql.SQLContext
> import org.apache.spark.sql.catalyst.types.decimal._
> import org.apache.spark.sql.catalyst.types._
> import org.apache.hadoop.fs._
> val sqlContext = new SQLContext(sc)
> val fs = FileSystem.get(sc.hadoopConfiguration)
> fs.delete(new Path("a.parquet"))
> fs.delete(new Path("b.parquet"))
> import sc._
> import sqlContext._
> val r1 = parallelize(1 to 10).map(i => Tuple1(Decimal(i, 10, 0))).select('_1 
> cast DecimalType(10, 0))
> // OK
> r1.saveAsParquetFile("a.parquet")
> val r2 = parallelize(1 to 10).map(i => Tuple1(Decimal(i, 10, 0))).select('_1 
> cast DecimalType(10, 0))
> val r3 = r2.coalesce(1)
> // Error
> r3.saveAsParquetFile("b.parquet")
> {noformat}
> Exception thrown:
> {noformat}
> java.lang.ClassCastException: scala.math.BigDecimal cannot be cast to 
> org.apache.spark.sql.catalyst.types.decimal.Decimal
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.consumeType(ParquetTableSupport.scala:359)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:328)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:314)
> 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.InsertIntoParquetTable.org$apache$spark$sql$parquet$InsertIntoParquetTable$$writeShard$1(ParquetTableOperations.scala:308)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at 
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
> at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> 15/03/17 00:04:13 WARN TaskSetManager: Lost task 0.0 in stage 2.0 (TID 2, 
> localhost): java.lang.ClassCastException: scala.math.BigDecimal cannot be 
> cast to org.apache.spark.sql.catalyst.types.decimal.Decimal
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.consumeType(ParquetTableSupport.scala:359)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:328)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:314)
> at 
> parquet.hadoop.InternalParquetRecordWriter.write(InternalParquetRecordWriter.java:120)
> at 
> parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:81)
> at 
> parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:37)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable.org$apache$spark$sql$parquet$InsertIntoParquetTable$$writeShard$1(ParquetTableOperations.scala:308)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at 
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
> at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> {noformat}
> The query plan o

[jira] [Updated] (SPARK-6360) For Spark 1.1 and 1.2, after any RDD transformations, calling saveAsParquetFile over a SchemaRDD with decimal or UDT column throws

2015-06-30 Thread Davies Liu (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-6360?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Davies Liu updated SPARK-6360:
--
Description: 
Spark shell session for reproduction (use {{:paste}}):
{noformat}
import org.apache.spark.sql.SQLContext
import org.apache.spark.sql.catalyst.types.decimal._
import org.apache.spark.sql.catalyst.types._
import org.apache.hadoop.fs._

val sqlContext = new SQLContext(sc)
val fs = FileSystem.get(sc.hadoopConfiguration)

fs.delete(new Path("a.parquet"))
fs.delete(new Path("b.parquet"))

import sc._
import sqlContext._

val r1 = parallelize(1 to 10).map(i => Tuple1(Decimal(i, 10, 0))).select('_1 
cast DecimalType(10, 0))

// OK
r1.saveAsParquetFile("a.parquet")

val r2 = parallelize(1 to 10).map(i => Tuple1(Decimal(i, 10, 0))).select('_1 
cast DecimalType(10, 0))

val r3 = r2.coalesce(1)

// Error
r3.saveAsParquetFile("b.parquet")
{noformat}
Exception thrown:
{noformat}
java.lang.ClassCastException: scala.math.BigDecimal cannot be cast to 
org.apache.spark.sql.catalyst.types.decimal.Decimal
at 
org.apache.spark.sql.parquet.MutableRowWriteSupport.consumeType(ParquetTableSupport.scala:359)
at 
org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:328)
at 
org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:314)
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.InsertIntoParquetTable.org$apache$spark$sql$parquet$InsertIntoParquetTable$$writeShard$1(ParquetTableOperations.scala:308)
at 
org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
at 
org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:56)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
at 
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at 
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
15/03/17 00:04:13 WARN TaskSetManager: Lost task 0.0 in stage 2.0 (TID 2, 
localhost): java.lang.ClassCastException: scala.math.BigDecimal cannot be cast 
to org.apache.spark.sql.catalyst.types.decimal.Decimal
at 
org.apache.spark.sql.parquet.MutableRowWriteSupport.consumeType(ParquetTableSupport.scala:359)
at 
org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:328)
at 
org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:314)
at 
parquet.hadoop.InternalParquetRecordWriter.write(InternalParquetRecordWriter.java:120)
at parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:81)
at parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:37)
at 
org.apache.spark.sql.parquet.InsertIntoParquetTable.org$apache$spark$sql$parquet$InsertIntoParquetTable$$writeShard$1(ParquetTableOperations.scala:308)
at 
org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
at 
org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:56)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
at 
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at 
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
{noformat}
The query plan of {{r1}} is:
{noformat}
== Parsed Logical Plan ==
'Project [CAST('_1, DecimalType(10,0)) AS c0#60]
 LogicalRDD [_1#59], MapPartitionsRDD[71] at mapPartitions at 
ExistingRDD.scala:36

== Analyzed Logical Plan ==
Project [CAST(_1#59, DecimalType(10,0)) AS c0#60]
 LogicalRDD [_1#59], MapPartitionsRDD[71] at mapPartitions at 
ExistingRDD.scala:36

== Optimized Logical Plan ==
Project [CAST(_1#59, DecimalType(10,0)) AS c0#60]
 LogicalRDD [_1#59], MapPartitionsRDD[71] at mapPartitions at 
ExistingRDD.scala:36

== Physical Plan ==
Project [CAST(_1#59, DecimalType(10,0)) AS c0#60]
 PhysicalRDD [_1#59], MapPartitionsRDD[71] at mapPartitions at 
ExistingRDD.scala:36

Code Generation: false
== RDD ==
{noformat}
while {{r3}}'s query plan is:
{noformat}

[jira] [Updated] (SPARK-6360) For Spark 1.1 and 1.2, after any RDD transformations, calling saveAsParquetFile over a SchemaRDD with decimal or UDT column throws

2015-05-04 Thread Cheng Lian (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-6360?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Cheng Lian updated SPARK-6360:
--
Target Version/s: 1.2.3  (was: 1.2.2)

> For Spark 1.1 and 1.2, after any RDD transformations, calling 
> saveAsParquetFile over a SchemaRDD with decimal or UDT column throws
> --
>
> Key: SPARK-6360
> URL: https://issues.apache.org/jira/browse/SPARK-6360
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 1.1.0, 1.2.0
>Reporter: Cheng Lian
>
> Spark shell session for reproduction (use {{:paste}}):
> {noformat}
> import org.apache.spark.sql.SQLContext
> import org.apache.spark.sql.catalyst.types.decimal._
> import org.apache.spark.sql.catalyst.types._
> import org.apache.hadoop.fs._
> val sqlContext = new SQLContext(sc)
> val fs = FileSystem.get(sc.hadoopConfiguration)
> fs.delete(new Path("a.parquet"))
> fs.delete(new Path("b.parquet"))
> import sc._
> import sqlContext._
> val r1 = parallelize(1 to 10)
>   .map(i => Tuple1(Decimal(i, 10, 0)))
>   .select('_1 cast DecimalType(10, 0))
> // OK
> r1.saveAsParquetFile("a.parquet")
> val r2 = parallelize(1 to 10)
>   .map(i => Tuple1(Decimal(i, 10, 0)))
>   .select('_1 cast DecimalType(10, 0))
> val r3 = r2.coalesce(1)
> // Error
> r3.saveAsParquetFile("b.parquet")
> {noformat}
> Exception thrown:
> {noformat}
> java.lang.ClassCastException: scala.math.BigDecimal cannot be cast to 
> org.apache.spark.sql.catalyst.types.decimal.Decimal
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.consumeType(ParquetTableSupport.scala:359)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:328)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:314)
> 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.InsertIntoParquetTable.org$apache$spark$sql$parquet$InsertIntoParquetTable$$writeShard$1(ParquetTableOperations.scala:308)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at 
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
> at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> 15/03/17 00:04:13 WARN TaskSetManager: Lost task 0.0 in stage 2.0 (TID 2, 
> localhost): java.lang.ClassCastException: scala.math.BigDecimal cannot be 
> cast to org.apache.spark.sql.catalyst.types.decimal.Decimal
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.consumeType(ParquetTableSupport.scala:359)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:328)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:314)
> at 
> parquet.hadoop.InternalParquetRecordWriter.write(InternalParquetRecordWriter.java:120)
> at 
> parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:81)
> at 
> parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:37)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable.org$apache$spark$sql$parquet$InsertIntoParquetTable$$writeShard$1(ParquetTableOperations.scala:308)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at 
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
> at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> {noformat}
> The query plan of {{r1}} is:

[jira] [Updated] (SPARK-6360) For Spark 1.1 and 1.2, after any RDD transformations, calling saveAsParquetFile over a SchemaRDD with decimal or UDT column throws

2015-03-16 Thread Cheng Lian (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-6360?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Cheng Lian updated SPARK-6360:
--
Summary: For Spark 1.1 and 1.2, after any RDD transformations, calling 
saveAsParquetFile over a SchemaRDD with decimal or UDT column throws  (was: For 
Spark 1.2, after any RDD transformations, calling saveAsParquetFile over a 
SchemaRDD with decimal or UDT column throws)

> For Spark 1.1 and 1.2, after any RDD transformations, calling 
> saveAsParquetFile over a SchemaRDD with decimal or UDT column throws
> --
>
> Key: SPARK-6360
> URL: https://issues.apache.org/jira/browse/SPARK-6360
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 1.1.0, 1.2.0
>Reporter: Cheng Lian
>
> Spark shell session for reproduction (use {{:paste}}):
> {noformat}
> import org.apache.spark.sql.SQLContext
> import org.apache.spark.sql.catalyst.types.decimal._
> import org.apache.spark.sql.catalyst.types._
> import org.apache.hadoop.fs._
> val sqlContext = new SQLContext(sc)
> val fs = FileSystem.get(sc.hadoopConfiguration)
> fs.delete(new Path("a.parquet"))
> fs.delete(new Path("b.parquet"))
> import sc._
> import sqlContext._
> val r1 = parallelize(1 to 10)
>   .map(i => Tuple1(Decimal(i, 10, 0)))
>   .select('_1 cast DecimalType(10, 0))
> // OK
> r1.saveAsParquetFile("a.parquet")
> val r2 = parallelize(1 to 10)
>   .map(i => Tuple1(Decimal(i, 10, 0)))
>   .select('_1 cast DecimalType(10, 0))
> val r3 = r2.coalesce(1)
> // Error
> r3.saveAsParquetFile("b.parquet")
> {noformat}
> Exception thrown:
> {noformat}
> java.lang.ClassCastException: scala.math.BigDecimal cannot be cast to 
> org.apache.spark.sql.catalyst.types.decimal.Decimal
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.consumeType(ParquetTableSupport.scala:359)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:328)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:314)
> 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.InsertIntoParquetTable.org$apache$spark$sql$parquet$InsertIntoParquetTable$$writeShard$1(ParquetTableOperations.scala:308)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at 
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
> at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> 15/03/17 00:04:13 WARN TaskSetManager: Lost task 0.0 in stage 2.0 (TID 2, 
> localhost): java.lang.ClassCastException: scala.math.BigDecimal cannot be 
> cast to org.apache.spark.sql.catalyst.types.decimal.Decimal
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.consumeType(ParquetTableSupport.scala:359)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:328)
> at 
> org.apache.spark.sql.parquet.MutableRowWriteSupport.write(ParquetTableSupport.scala:314)
> at 
> parquet.hadoop.InternalParquetRecordWriter.write(InternalParquetRecordWriter.java:120)
> at 
> parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:81)
> at 
> parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:37)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable.org$apache$spark$sql$parquet$InsertIntoParquetTable$$writeShard$1(ParquetTableOperations.scala:308)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at 
> org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:325)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at 
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
> at 
> java.util.concurrent.ThreadPoolExe