java.lang.UnsupportedOperationException: org.apache.parquet.column.values.dictionary.PlainValuesDict

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本文介绍了一种常见的Spark处理Parquet文件时遇到的UnsupportedOperationException错误，并提供了详细的堆栈跟踪。该错误通常由向Parquet列中写入不一致的数据类型引起，解决方法是在写入前确保所有列值类型统一。

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Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 3 in stage 9.0 failed 4 times, most recent failure: Lost task 3.3 in stage 9.0 (TID 56, www.byxf.master.com, executor 8): java.lang.UnsupportedOperationException: org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainIntegerDictionary
at org.apache.parquet.column.Dictionary.decodeToBinary(Dictionary.java:44)
at org.apache.spark.sql.execution.vectorized.ColumnVector.getUTF8String(ColumnVector.java:625)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$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:377)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:126)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
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)

产生这个报错，多是由于向parquet 列值中插入不同类型的列值产生，只需将在插入时将列值转换为统一格式即可。