[SUPPORT] Exception on snapshot query on MOR table (hudi 0.6.0)

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Describe the problem you faced

A clear and concise description of the problem.

To Reproduce

Steps to reproduce the behavior:

1. have a table with 100GB data and under compaction
2. kill the spark job
3. try to read the data by snapshot query

val df = spark.read.format("org.apache.hudi")
.option("hoodie.datasource.query.type","snapshot")
.load("s3://path_to_data/*")

Expected behavior

A clear and concise description of what you expected to happen.

Environment Description

• Hudi version : 0.6.0

• Spark version : 2.4.4

• Hive version : not using

• Hadoop version : 3.2.1

• Storage (HDFS/S3/GCS…) : s3

• Running on Docker? (yes/no) : no

Additional context

Add any other context about the problem here.

Stacktrace

Exception: Task failed while writing rows.
	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:257)
	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$write$15(FileFormatWriter.scala:177)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
	at org.apache.spark.scheduler.Task.run(Task.scala:123)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:411)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
	at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.ArrayIndexOutOfBoundsException: 4191
	at org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainDoubleDictionary.decodeToDouble(PlainValuesDictionary.java:208)
	at org.apache.spark.sql.execution.datasources.parquet.ParquetDictionary.decodeToDouble(ParquetDictionary.java:46)
	at org.apache.spark.sql.execution.vectorized.OnHeapColumnVector.getDouble(OnHeapColumnVector.java:460)
	at org.apache.spark.sql.execution.vectorized.MutableColumnarRow.getDouble(MutableColumnarRow.java:126)
	at org.apache.spark.sql.execution.vectorized.MutableColumnarRow.get(MutableColumnarRow.java:178)
	at org.apache.hudi.HoodieMergeOnReadRDD$$anon$2.$anonfun$createRowWithRequiredSchema$1(HoodieMergeOnReadRDD.scala:239)
	at org.apache.hudi.HoodieMergeOnReadRDD$$anon$2.$anonfun$createRowWithRequiredSchema$1$adapted(HoodieMergeOnReadRDD.scala:237)
	at scala.collection.Iterator.foreach(Iterator.scala:941)
	at scala.collection.Iterator.foreach$(Iterator.scala:941)
	at scala.collection.AbstractIterator.foreach(Iterator.scala:1429)
	at scala.collection.IterableLike.foreach(IterableLike.scala:74)
	at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
	at org.apache.spark.sql.types.StructType.foreach(StructType.scala:99)
	at org.apache.hudi.HoodieMergeOnReadRDD$$anon$2.createRowWithRequiredSchema(HoodieMergeOnReadRDD.scala:237)
	at org.apache.hudi.HoodieMergeOnReadRDD$$anon$2.hasNext(HoodieMergeOnReadRDD.scala:197)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$2.hasNext(WholeStageCodegenExec.scala:636)
	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$executeTask$1(FileFormatWriter.scala:244)
	at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1394)
	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:242)
	... 9 more

[adaniline-paytm]

I have the same sporadic issue, using standard Spark 2.4.7 distribution and Hudi 0.6:

$ ls -l /opt/spark-2.4.7-bin-without-hadoop/jars/parquet-*
 /opt/spark-2.4.7-bin-without-hadoop/jars/parquet-column-1.10.1.jar
/opt/spark-2.4.7-bin-without-hadoop/jars/parquet-common-1.10.1.jar
/opt/spark-2.4.7-bin-without-hadoop/jars/parquet-encoding-1.10.1.jar
/opt/spark-2.4.7-bin-without-hadoop/jars/parquet-format-2.4.0.jar
/opt/spark-2.4.7-bin-without-hadoop/jars/parquet-hadoop-1.10.1.jar
/opt/spark-2.4.7-bin-without-hadoop/jars/parquet-jackson-1.10.1.jar

the only workaround we found is to disable VectorizedReader:

      rc.spark.conf.set("spark.sql.parquet.enableVectorizedReader", "false")

[vinothchandar]

Closing since the fix has since been landed