Fabio J. Walter created SPARK-22291: ---------------------------------------
Summary: Postgresql UUID[] to Cassandra: Conversion Error Key: SPARK-22291 URL: https://issues.apache.org/jira/browse/SPARK-22291 Project: Spark Issue Type: Bug Components: Spark Core, SQL Affects Versions: 2.2.0 Environment: Debian Linux, Scala 2.11, Spark 2.2.0, PostgreSQL 9.6, Cassandra 3 Reporter: Fabio J. Walter 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: {noformat} 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) {noformat} 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 {code:scala} //My suggestion is change the line 443 from ```array.asInstanceOf[Array[java.lang.String]] .map(UTF8String.fromString)``` //to ```array.map(UTF8String.fromString(_.toString))``` {code} -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org