hseagle commented on issue #2538:
URL: https://github.com/apache/hudi/issues/2538#issuecomment-774397457
After set **spark.sql.hive.convertMetastoreParquet=false**, the duplicated
key can be removed.
But another issue is encounted, the column with timestamp data type cann't
be fetched. The error message is showed as below
```log
Caused by: java.lang.ClassCastException: org.apache.hadoop.io.LongWritable
cannot be cast to org.apache.hadoop.hive.serde2.io.TimestampWritable
at
org.apache.hadoop.hive.serde2.objectinspector.primitive.WritableTimestampObjectInspector.getPrimitiveJavaObject(WritableTimestampObjectInspector.java:39)
at
org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$14(TableReader.scala:468)
at
org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$14$adapted(TableReader.scala:467)
at
org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$18(TableReader.scala:493)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
Source)
at
org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at
org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:340)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:872)
at
org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:872)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at
org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
```
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