Sameer Agarwal created SPARK-19430: -------------------------------------- Summary: Cannot read external tables with VARCHAR columns if they're backed by ORC files written by Hive 1.2.1 Key: SPARK-19430 URL: https://issues.apache.org/jira/browse/SPARK-19430 Project: Spark Issue Type: Bug Components: SQL Affects Versions: 2.1.0, 2.0.2, 1.6.3 Reporter: Sameer Agarwal
Spark throws an exception when trying to read external tables with VARCHAR columns if they're backed by ORC files that were written by Hive 1.2.1. Steps to reproduce (credits to [~lian cheng]): # Write an ORC table using Hive 1.2.1 with {noformat} CREATE TABLE orc_varchar_test STORED AS ORC AS SELECT CASTE('a' AS VARCHAR(10)) AS c0{noformat} # Get the raw path of the written ORC file # Create an external table pointing to this file and read the table using Spark {noformat} val path = "/tmp/orc_varchar_test" sql(s"create external table if not exists test (c0 varchar(10)) stored as orc location '$path'") spark.table("test").show(){noformat} The problem here is that the metadata in the ORC file written by Hive is different from those written by Spark. We can inspect the ORC file written above: {noformat} $ hive --orcfiledump file:///Users/lian/local/var/lib/hive/warehouse_1.2.1/orc_varchar_test/000000_0 Structure for file:///Users/lian/local/var/lib/hive/warehouse_1.2.1/orc_varchar_test/000000_0 File Version: 0.12 with HIVE_8732 Rows: 1 Compression: ZLIB Compression size: 262144 Type: struct<_col0:varchar(10)> <---- ... {noformat} On the other hand, if you create an ORC table using the same DDL and inspect the written ORC file, you'll see: {noformat} ... Type: struct<c0:string> ... {noformat} Note that all tests are done with {{spark.sql.hive.convertMetastoreOrc}} set to {{false}}, which is the default case. I've verified that Spark 1.6.x, 2.0.x and 2.1.x all fail with instances of the following error: {code} java.lang.ClassCastException: org.apache.hadoop.hive.serde2.io.HiveVarcharWritable cannot be cast to org.apache.hadoop.io.Text at org.apache.hadoop.hive.serde2.objectinspector.primitive.WritableStringObjectInspector.getPrimitiveWritableObject(WritableStringObjectInspector.java:41) at org.apache.spark.sql.hive.HiveInspectors$$anonfun$unwrapperFor$23.apply(HiveInspectors.scala:529) at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$14$$anonfun$apply$15.apply(TableReader.scala:419) at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$14$$anonfun$apply$15.apply(TableReader.scala:419) at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$fillObject$2.apply(TableReader.scala:435) at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$fillObject$2.apply(TableReader.scala:426) at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:126) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) at org.apache.spark.scheduler.Task.run(Task.scala:99) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322) 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:745) {code} -- This message was sent by Atlassian JIRA (v6.3.15#6346) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org