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https://issues.apache.org/jira/browse/SPARK-48942?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
ASF GitHub Bot updated SPARK-48942:
-----------------------------------
Labels: pull-request-available (was: )
> Reading parquet with Array of Structs of UDTs throws Exception
> --------------------------------------------------------------
>
> Key: SPARK-48942
> URL: https://issues.apache.org/jira/browse/SPARK-48942
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.4.0, 3.5.1
> Reporter: James Willis
> Priority: Minor
> Labels: pull-request-available
>
> When reading parquet files that have a column that is an Array of Structs
> where the Struct contains a UDT, the read fails. We have repro'd this is
> 3.4.0 and 3.5.1.
> I see this might be some related work on Supporting UDTs in parquet:
> https://issues.apache.org/jira/browse/SPARK-39086
>
> I'm trying to create a UDT to repro this without sedona
>
> I discovered this when using Apache Sedona. Here is my minimal reproducible
> example:
> {code:java}
> sedona.sql("""
> SELECT ARRAY(STRUCT(ST_POINT(1.0, 1.1)))
> """).write.mode("overwrite").format("parquet").save(test_read_write_path)df =
> sedona.read.format("parquet").load(test_read_write_path)
> df.show() {code}
> This gives the following stack trace:
> {code:java}
> 24/07/19 03:31:23 WARN TaskSetManager: Lost task 0.0 in stage 22.0 (TID 24)
> (10.0.133.128 executor 1): java.lang.IllegalArgumentException: Spark type:
> StructType(StructField(col1,BinaryType,true)) doesn't match the type:
> StructType(StructField(col1,org.apache.spark.sql.sedona_sql.UDT.GeometryUDT@5b138d06,true))
> in column vector
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetColumnVector.<init>(ParquetColumnVector.java:69)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetColumnVector.<init>(ParquetColumnVector.java:116)
> at
> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.initBatch(VectorizedParquetRecordReader.java:272)
> at
> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.initBatch(VectorizedParquetRecordReader.java:292)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat.$anonfun$buildReaderWithPartitionValues$2(ParquetFileFormat.scala:286)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:228)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:290)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:125)
> at
> org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:594)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:388)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:888)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:888)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:92)
> at
> org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161)
> at org.apache.spark.scheduler.Task.run(Task.scala:139)
> at
> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:554)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1529)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:557)
> at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown
> Source)
> at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown
> Source)
> at java.base/java.lang.Thread.run(Unknown Source)
> 24/07/19 03:31:23 WARN TaskSetManager: Lost task 0.1 in stage 22.0 (TID 25)
> (10.0.183.100 executor 5): java.lang.IllegalArgumentException: Spark type:
> StructType(StructField(col1,BinaryType,true)) doesn't match the type:
> StructType(StructField(col1,org.apache.spark.sql.sedona_sql.UDT.GeometryUDT@239780ef,true))
> in column vector
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetColumnVector.<init>(ParquetColumnVector.java:69)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetColumnVector.<init>(ParquetColumnVector.java:116)
> at
> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.initBatch(VectorizedParquetRecordReader.java:272)
> at
> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.initBatch(VectorizedParquetRecordReader.java:292)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat.$anonfun$buildReaderWithPartitionValues$2(ParquetFileFormat.scala:286)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:228)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:290)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:125)
> at
> org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:594)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:388)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:888)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:888)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:92)
> at
> org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161)
> at org.apache.spark.scheduler.Task.run(Task.scala:139)
> at
> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:554)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1529)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:557)
> at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown
> Source)
> at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown
> Source)
> at java.base/java.lang.Thread.run(Unknown Source)
> 24/07/19 03:31:24 WARN TaskSetManager: Lost task 0.2 in stage 22.0 (TID 26)
> (10.0.137.49 executor 3): java.lang.IllegalArgumentException: Spark type:
> StructType(StructField(col1,BinaryType,true)) doesn't match the type:
> StructType(StructField(col1,org.apache.spark.sql.sedona_sql.UDT.GeometryUDT@54e7b6bf,true))
> in column vector
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetColumnVector.<init>(ParquetColumnVector.java:69)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetColumnVector.<init>(ParquetColumnVector.java:116)
> at
> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.initBatch(VectorizedParquetRecordReader.java:272)
> at
> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.initBatch(VectorizedParquetRecordReader.java:292)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat.$anonfun$buildReaderWithPartitionValues$2(ParquetFileFormat.scala:286)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:228)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:290)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:125)
> at
> org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:594)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:388)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:888)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:888)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:92)
> at
> org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161)
> at org.apache.spark.scheduler.Task.run(Task.scala:139)
> at
> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:554)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1529)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:557)
> at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown
> Source)
> at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown
> Source)
> at java.base/java.lang.Thread.run(Unknown Source) {code}
>
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