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  1. Spark
  2. SPARK-22291

Postgresql UUID[] to Cassandra: Conversion Error

    Details

    • Type: Bug
    • Status: Resolved
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: 2.2.0
    • Fix Version/s: 2.2.1, 2.3.0
    • Component/s: SQL
    • Labels:
    • Environment:

      Debian Linux, Scala 2.11, Spark 2.2.0, PostgreSQL 9.6, Cassandra 3

    • Flags:
      Patch

      Description

      My job reads data from a PostgreSQL table that contains columns of user_ids uuid[] type, so that I'm getting the error above when I'm trying to save data on Cassandra.

      However, the creation of this same table on Cassandra works fine! user_ids list<text>.

      I can't change the type on the source table, because I'm reading data from a legacy system.

      I've been looking at point printed on log, on class org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils.scala

      Stacktrace on Spark:

      Caused by: java.lang.ClassCastException: [Ljava.util.UUID; cannot be cast to [Ljava.lang.String;
      at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$14.apply(JdbcUtils.scala:443)
      at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$14.apply(JdbcUtils.scala:442)
      at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$makeGetter$13$$anonfun$18.apply(JdbcUtils.scala:472)
      at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$makeGetter$13$$anonfun$18.apply(JdbcUtils.scala:472)
      at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$nullSafeConvert(JdbcUtils.scala:482)
      at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$makeGetter$13.apply(JdbcUtils.scala:470)
      at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$makeGetter$13.apply(JdbcUtils.scala:469)
      at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:330)
      at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:312)
      at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
      at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
      at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:32)
      at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
      at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
      at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:395)
      at org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$1$$anon$1.hasNext(InMemoryRelation.scala:133)
      at org.apache.spark.storage.memory.MemoryStore.putIteratorAsValues(MemoryStore.scala:215)
      at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1038)
      at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1029)
      at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:969)
      at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1029)
      at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:760)
      at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:334)
      at org.apache.spark.rdd.RDD.iterator(RDD.scala:285)
      at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
      at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
      at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
      at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
      at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
      at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
      at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
      at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
      at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
      at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
      at org.apache.spark.scheduler.Task.run(Task.scala:108)
      at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
      at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
      at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
      at java.lang.Thread.run(Thread.java:748)
      

      Proposed solution:

      At this specific point spark-sql_2.11-2.2.0-sources.jar!/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala:443

      //My suggestion is change the line 443 from
      
      ```array.asInstanceOf[Array[java.lang.String]]
                    .map(UTF8String.fromString)```
      
      //to 
      ```array.map(UTF8String.fromString(_.toString))```
      

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            • Assignee:
              jmchung Jen-Ming Chung
              Reporter:
              fabiojwalter Fabio J. Walter
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              Dates

              • Created:
                Updated:
                Resolved: