[jira] [Created] (SPARK-18536) Failed to save to hive table when case class with empty field

["pin_zhang (JIRA)" <ji...@apache.org>]

pin_zhang created SPARK-18536:
---------------------------------

             Summary: 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



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
 



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