[SPARK-22291] Postgresql UUID[] to Cassandra: Conversion Error - ASF JIRA

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:
- patch
- postgresql
- sql
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))```