zherenyu831 opened a new issue #2285: URL: https://github.com/apache/hudi/issues/2285
**_Tips before filing an issue_** - Have you gone through our [FAQs](https://cwiki.apache.org/confluence/display/HUDI/FAQ)? - Join the mailing list to engage in conversations and get faster support at [email protected]. - If you have triaged this as a bug, then file an [issue](https://issues.apache.org/jira/projects/HUDI/issues) directly. **Describe the problem you faced** A clear and concise description of the problem. **To Reproduce** Steps to reproduce the behavior: 1. have some table under compaction 2. kill the spark job 3. try to read the data by snapshot query **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 ``` ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected]
