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https://issues.apache.org/jira/browse/SPARK-26630?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16753146#comment-16753146
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Xiao Li commented on SPARK-26630:
---------------------------------
This is an improvement. Thanks!
> Support reading Hive-serde tables whose INPUTFORMAT is
> org.apache.hadoop.mapreduce
> ----------------------------------------------------------------------------------
>
> Key: SPARK-26630
> URL: https://issues.apache.org/jira/browse/SPARK-26630
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 2.4.0, 2.4.1, 3.0.0
> Reporter: Deegue
> Assignee: Deegue
> Priority: Major
> Fix For: 3.0.0
>
>
> This bug found in [link title|https://github.com/apache/spark/pull/23506] (PR
> #23506).
> It will throw ClassCastException when we use new input format (eg.
> `org.apache.hadoop.mapreduce.InputFormat`) to create HadoopRDD.So we need to
> use NewHadoopRDD to deal with this input format in TableReader.scala.
> Exception :
> {noformat}
> Caused by: java.lang.ClassCastException:
> org.apache.hadoop.mapreduce.lib.input.TextInputFormat cannot be cast to
> org.apache.hadoop.mapred.InputFormat
> at org.apache.spark.rdd.HadoopRDD.getInputFormat(HadoopRDD.scala:190)
> at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:204)
> at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:254)
> at scala.Option.getOrElse(Option.scala:138)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:252)
> at
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
> at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:254)
> at scala.Option.getOrElse(Option.scala:138)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:252)
> at
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
> at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:254)
> at scala.Option.getOrElse(Option.scala:138)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:252)
> at
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
> at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:254)
> at scala.Option.getOrElse(Option.scala:138)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:252)
> at
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
> at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:254)
> at scala.Option.getOrElse(Option.scala:138)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:252)
> at
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
> at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:254)
> at scala.Option.getOrElse(Option.scala:138)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:252)
> at org.apache.spark.ShuffleDependency.<init>(Dependency.scala:96)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$.prepareShuffleDependency(ShuffleExchangeExec.scala:343)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.prepareShuffleDependency(ShuffleExchangeExec.scala:101)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.$anonfun$doExecute$1(ShuffleExchangeExec.scala:137)
> at
> org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
> ... 87 more
> {noformat}
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