Cheng Lian created SPARK-6360:
---------------------------------
Summary: For Spark 1.2, after any RDD transformations, calling
saveAsParquetFile over a SchemaRDD with decimal column throws
Key: SPARK-6360
URL: https://issues.apache.org/jira/browse/SPARK-6360
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.2.0, 1.1.0
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:
{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}
== Parsed Logical Plan ==
LogicalRDD [c0#61], CoalescedRDD[74] at coalesce at SchemaRDD.scala:456
== Analyzed Logical Plan ==
LogicalRDD [c0#61], CoalescedRDD[74] at coalesce at SchemaRDD.scala:456
== Optimized Logical Plan ==
LogicalRDD [c0#61], CoalescedRDD[74] at coalesce at SchemaRDD.scala:456
== Physical Plan ==
PhysicalRDD [c0#61], CoalescedRDD[74] at coalesce at SchemaRDD.scala:456
Code Generation: false
== RDD ==
{noformat}
The key difference here is that, {{r3}} wraps an existing {{SchemaRDD}}
({{r2}}, beneath the {{CoalescedRDD}}). While evaluating {{r3}}, {{r2.compute}}
is called, which calls {{ScalaReflection.convertRowToScala}}. Here, Catalyst
{{Decimal}} values are converted into Java {{BigDecimals}}, and finally causes
the exception.
Note that {{DataFrame}} in Spark 1.3 doesn't suffer this issue.
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