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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 03:59:12 UTC
[jira] [Updated] (SPARK-22474) cannot read a parquet file
containing a Seq[Map[MyCaseClass, String]]
[ https://issues.apache.org/jira/browse/SPARK-22474?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon updated SPARK-22474:
---------------------------------
Labels: bulk-closed (was: )
> cannot read a parquet file containing a Seq[Map[MyCaseClass, String]]
> ---------------------------------------------------------------------
>
> Key: SPARK-22474
> URL: https://issues.apache.org/jira/browse/SPARK-22474
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.1.2, 2.2.0
> Reporter: Mikael Valot
> Priority: Major
> Labels: bulk-closed
>
> The following code run in spark-shell throws an exception. It is working fine in Spark 2.0.2
> {code:java}
> case class MyId(v: String)
> case class MyClass(infos: Seq[Map[MyId, String]])
> val seq = Seq(MyClass(Seq(Map(MyId("1234") -> "blah"))))
> seq.toDS().write.parquet("/tmp/myclass")
> spark.read.parquet("/tmp/myclass").as[MyClass].collect()
> Caused by: org.apache.spark.sql.AnalysisException: Map key type is expected to be a primitive type, but found: required group key {
> optional binary v (UTF8);
> };
> at org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$.checkConversionRequirement(ParquetSchemaConverter.scala:581)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$convertGroupField$2.apply(ParquetSchemaConverter.scala:246)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$convertGroupField$2.apply(ParquetSchemaConverter.scala:201)
> at scala.Option.fold(Option.scala:158)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convertGroupField(ParquetSchemaConverter.scala:201)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convertField(ParquetSchemaConverter.scala:109)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$2.apply(ParquetSchemaConverter.scala:87)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$2.apply(ParquetSchemaConverter.scala:84)
> 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$class.foreach(IterableLike.scala:72)
> at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> at scala.collection.AbstractTraversable.map(Traversable.scala:104)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.org$apache$spark$sql$execution$datasources$parquet$ParquetSchemaConverter$$convert(ParquetSchemaConverter.scala:84)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$convertGroupField$1.apply(ParquetSchemaConverter.scala:201)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$$anonfun$convertGroupField$1.apply(ParquetSchemaConverter.scala:201)
> at scala.Option.fold(Option.scala:158)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convertGroupField(ParquetSchemaConverter.scala:201)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter.convertField(ParquetSchemaConverter.scala:109)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetRowConverter$ParquetArrayConverter.<init>(ParquetRowConverter.scala:483)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetRowConverter.org$apache$spark$sql$execution$datasources$parquet$ParquetRowConverter$$newConverter(ParquetRowConverter.scala:298)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetRowConverter$$anonfun$6.apply(ParquetRowConverter.scala:183)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetRowConverter$$anonfun$6.apply(ParquetRowConverter.scala:180)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> at scala.collection.AbstractTraversable.map(Traversable.scala:104)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetRowConverter.<init>(ParquetRowConverter.scala:180)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetRecordMaterializer.<init>(ParquetRecordMaterializer.scala:38)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetReadSupport.prepareForRead(ParquetReadSupport.scala:95)
> at org.apache.parquet.hadoop.InternalParquetRecordReader.initialize(InternalParquetRecordReader.java:175)
> at org.apache.parquet.hadoop.ParquetRecordReader.initializeInternalReader(ParquetRecordReader.java:190)
> at org.apache.parquet.hadoop.ParquetRecordReader.initialize(ParquetRecordReader.java:147)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anonfun$buildReaderWithPartitionValues$1.apply(ParquetFileFormat.scala:381)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anonfun$buildReaderWithPartitionValues$1.apply(ParquetFileFormat.scala:337)
> at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:124)
> at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:174)
> at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:105)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
> at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:395)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:234)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:228)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> at org.apache.spark.scheduler.Task.run(Task.scala:108)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748)
> {code}
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