[SPARK-7937] Cannot compare Hive named_struct. (when using argmax, argmin)

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Fixed
• Affects Version/s: 1.4.0
• Fix Version/s: 1.5.0
• Component/s: SQL
• Labels: releasenotes
• Assignee: L. C. Hsieh
• Reporter: Jianshi Huang
• Shepherd: Reynold Xin
• Created: 29/May/15 06:13
• Updated: 03/Aug/15 00:53
• Resolved: 03/Aug/15 00:53

Description

Imagine the following SQL:

Intention: get last used bank account country.

select bank_account_id, 
  max(named_struct(
    'src_row_update_ts', unix_timestamp(src_row_update_ts,'yyyy/M/D HH:mm:ss'), 
    'bank_country', bank_country)).bank_country 
from bank_account_monthly
where year_month='201502' 
group by bank_account_id

=>

Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 94 in stage 96.0 failed 4 times, most recent failure: Lost task 94.3 in stage 96.0 (TID 22281, xxxx): java.lang.RuntimeException: Type StructType(StructField(src_row_update_ts,LongType,true), StructField(bank_country,StringType,true)) does not support ordered operations
        at scala.sys.package$.error(package.scala:27)
        at org.apache.spark.sql.catalyst.expressions.LessThan.ordering$lzycompute(predicates.scala:222)
        at org.apache.spark.sql.catalyst.expressions.LessThan.ordering(predicates.scala:215)
        at org.apache.spark.sql.catalyst.expressions.LessThan.eval(predicates.scala:235)
        at org.apache.spark.sql.catalyst.expressions.MaxFunction.update(aggregates.scala:147)
        at org.apache.spark.sql.execution.Aggregate$$anonfun$doExecute$1$$anonfun$7.apply(Aggregate.scala:165)
        at org.apache.spark.sql.execution.Aggregate$$anonfun$doExecute$1$$anonfun$7.apply(Aggregate.scala:149)
        at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:686)
        at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:686)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:70)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
        at org.apache.spark.scheduler.Task.run(Task.scala:70)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:724)

Issue Links

• links to: [Github] Pull Request #6519 (viirya)
• links to: [Github] Pull Request #7877 (rxin)