[
https://issues.apache.org/jira/browse/SPARK-18536?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Reynold Xin updated SPARK-18536:
--------------------------------
Description:
{code}import scala.collection.mutable.Queue
import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.spark.sql.SaveMode
import org.apache.spark.sql.SparkSession
import org.apache.spark.streaming.Seconds
import org.apache.spark.streaming.StreamingContext
{code}
1. Test code
{code}
case class EmptyC()
case class EmptyCTable(dimensions: EmptyC, timebin: java.lang.Long)
object EmptyTest {
def main(args: Array[String]): Unit = {
val conf = new SparkConf().setAppName("scala").setMaster("local[2]")
val ctx = new SparkContext(conf)
val spark =
SparkSession.builder().enableHiveSupport().config(conf).getOrCreate()
val seq = Seq(EmptyCTable(EmptyC(), 1000000L))
val rdd = ctx.makeRDD[EmptyCTable](seq)
val ssc = new StreamingContext(ctx, Seconds(1))
val queue = Queue(rdd)
val s = ssc.queueStream(queue, false);
s.foreachRDD((rdd, time) => {
if (!rdd.isEmpty) {
import spark.sqlContext.implicits._
rdd.toDF.write.mode(SaveMode.Overwrite).saveAsTable("empty_table")
}
})
ssc.start()
ssc.awaitTermination()
}
}
{code}
2. Exception
{noformat}
Caused by: java.lang.IllegalStateException: Cannot build an empty group
at org.apache.parquet.Preconditions.checkState(Preconditions.java:91)
at org.apache.parquet.schema.Types$GroupBuilder.build(Types.java:554)
at org.apache.parquet.schema.Types$GroupBuilder.build(Types.java:426)
at org.apache.parquet.schema.Types$Builder.named(Types.java:228)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convertField(ParquetSchemaConverter.scala:527)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convertField(ParquetSchemaConverter.scala:321)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$convert$1.apply(ParquetSchemaConverter.scala:313)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$convert$1.apply(ParquetSchemaConverter.scala:313)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at org.apache.spark.sql.types.StructType.foreach(StructType.scala:95)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at org.apache.spark.sql.types.StructType.map(StructType.scala:95)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convert(ParquetSchemaConverter.scala:313)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.init(ParquetWriteSupport.scala:85)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:288)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:262)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetFileFormat.scala:562)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anon$1.newInstance(ParquetFileFormat.scala:139)
at
org.apache.spark.sql.execution.datasources.BaseWriterContainer.newOutputWriter(WriterContainer.scala:131)
at
org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:247)
at
org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(InsertIntoHadoopFsRelationCommand.scala:143)
at
org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(InsertIntoHadoopFsRelationCommand.scala:143)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
... 3 more
{noformat}
was:
import scala.collection.mutable.Queue
import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.spark.sql.SaveMode
import org.apache.spark.sql.SparkSession
import org.apache.spark.streaming.Seconds
import org.apache.spark.streaming.StreamingContext
1. Test code
case class EmptyC()
case class EmptyCTable(dimensions: EmptyC, timebin: java.lang.Long)
object EmptyTest {
def main(args: Array[String]): Unit = {
val conf = new SparkConf().setAppName("scala").setMaster("local[2]")
val ctx = new SparkContext(conf)
val spark =
SparkSession.builder().enableHiveSupport().config(conf).getOrCreate()
val seq = Seq(EmptyCTable(EmptyC(), 1000000L))
val rdd = ctx.makeRDD[EmptyCTable](seq)
val ssc = new StreamingContext(ctx, Seconds(1))
val queue = Queue(rdd)
val s = ssc.queueStream(queue, false);
s.foreachRDD((rdd, time) => {
if (!rdd.isEmpty) {
import spark.sqlContext.implicits._
rdd.toDF.write.mode(SaveMode.Overwrite).saveAsTable("empty_table")
}
})
ssc.start()
ssc.awaitTermination()
}
}
2. Exception
Caused by: java.lang.IllegalStateException: Cannot build an empty group
at org.apache.parquet.Preconditions.checkState(Preconditions.java:91)
at org.apache.parquet.schema.Types$GroupBuilder.build(Types.java:554)
at org.apache.parquet.schema.Types$GroupBuilder.build(Types.java:426)
at org.apache.parquet.schema.Types$Builder.named(Types.java:228)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convertField(ParquetSchemaConverter.scala:527)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convertField(ParquetSchemaConverter.scala:321)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$convert$1.apply(ParquetSchemaConverter.scala:313)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$convert$1.apply(ParquetSchemaConverter.scala:313)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at org.apache.spark.sql.types.StructType.foreach(StructType.scala:95)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at org.apache.spark.sql.types.StructType.map(StructType.scala:95)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convert(ParquetSchemaConverter.scala:313)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.init(ParquetWriteSupport.scala:85)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:288)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:262)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetFileFormat.scala:562)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anon$1.newInstance(ParquetFileFormat.scala:139)
at
org.apache.spark.sql.execution.datasources.BaseWriterContainer.newOutputWriter(WriterContainer.scala:131)
at
org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:247)
at
org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(InsertIntoHadoopFsRelationCommand.scala:143)
at
org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(InsertIntoHadoopFsRelationCommand.scala:143)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
... 3 more
> Failed to save to hive table when case class with empty field
> -------------------------------------------------------------
>
> Key: SPARK-18536
> URL: https://issues.apache.org/jira/browse/SPARK-18536
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.1
> Reporter: pin_zhang
>
> {code}import scala.collection.mutable.Queue
> import org.apache.spark.SparkConf
> import org.apache.spark.SparkContext
> import org.apache.spark.sql.SaveMode
> import org.apache.spark.sql.SparkSession
> import org.apache.spark.streaming.Seconds
> import org.apache.spark.streaming.StreamingContext
> {code}
> 1. Test code
> {code}
> case class EmptyC()
> case class EmptyCTable(dimensions: EmptyC, timebin: java.lang.Long)
> object EmptyTest {
> def main(args: Array[String]): Unit = {
> val conf = new SparkConf().setAppName("scala").setMaster("local[2]")
> val ctx = new SparkContext(conf)
> val spark =
> SparkSession.builder().enableHiveSupport().config(conf).getOrCreate()
> val seq = Seq(EmptyCTable(EmptyC(), 1000000L))
> val rdd = ctx.makeRDD[EmptyCTable](seq)
> val ssc = new StreamingContext(ctx, Seconds(1))
> val queue = Queue(rdd)
> val s = ssc.queueStream(queue, false);
> s.foreachRDD((rdd, time) => {
> if (!rdd.isEmpty) {
> import spark.sqlContext.implicits._
> rdd.toDF.write.mode(SaveMode.Overwrite).saveAsTable("empty_table")
> }
> })
> ssc.start()
> ssc.awaitTermination()
> }
> }
> {code}
> 2. Exception
> {noformat}
> Caused by: java.lang.IllegalStateException: Cannot build an empty group
> at org.apache.parquet.Preconditions.checkState(Preconditions.java:91)
> at org.apache.parquet.schema.Types$GroupBuilder.build(Types.java:554)
> at org.apache.parquet.schema.Types$GroupBuilder.build(Types.java:426)
> at org.apache.parquet.schema.Types$Builder.named(Types.java:228)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convertField(ParquetSchemaConverter.scala:527)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convertField(ParquetSchemaConverter.scala:321)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$convert$1.apply(ParquetSchemaConverter.scala:313)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$convert$1.apply(ParquetSchemaConverter.scala:313)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.Iterator$class.foreach(Iterator.scala:893)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
> at org.apache.spark.sql.types.StructType.foreach(StructType.scala:95)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> at org.apache.spark.sql.types.StructType.map(StructType.scala:95)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convert(ParquetSchemaConverter.scala:313)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.init(ParquetWriteSupport.scala:85)
> at
> org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:288)
> at
> org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:262)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetFileFormat.scala:562)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anon$1.newInstance(ParquetFileFormat.scala:139)
> at
> org.apache.spark.sql.execution.datasources.BaseWriterContainer.newOutputWriter(WriterContainer.scala:131)
> at
> org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:247)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(InsertIntoHadoopFsRelationCommand.scala:143)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(InsertIntoHadoopFsRelationCommand.scala:143)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
> at org.apache.spark.scheduler.Task.run(Task.scala:86)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
> ... 3 more
> {noformat}
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