Details

    • Sub-task
    • Status: Resolved
    • Blocker
    • Resolution: Fixed
    • None
    • 1.5.0
    • SQL
    • None
    • Spark 1.5 doc/QA sprint

    Description

      select
        i_item_desc,
        i_category,
        i_class,
        i_current_price,
        sum(ss_ext_sales_price) as itemrevenue
        -- sum(ss_ext_sales_price) * 100 / sum(sum(ss_ext_sales_price)) over (partition by i_class) as revenueratio
      from
        store_sales
        join item on (store_sales.ss_item_sk = item.i_item_sk)
        join date_dim on (store_sales.ss_sold_date_sk = date_dim.d_date_sk)
      where
        i_category in('Jewelry', 'Sports', 'Books')
        -- and d_date between cast('2001-01-12' as date) and (cast('2001-01-12' as date) + 30)
        -- and d_date between '2001-01-12' and '2001-02-11'
        -- and ss_date between '2001-01-12' and '2001-02-11'
        -- and ss_sold_date_sk between 2451922 and 2451952  -- partition key filter
        and ss_sold_date_sk between 2451911 and 2451941  -- partition key filter (1 calendar month)
        and d_date between '2001-01-01' and '2001-01-31'
      group by
        i_item_id,
        i_item_desc,
        i_category,
        i_class,
        i_current_price
      order by
        i_category,
        i_class,
        i_item_id,
        i_item_desc
        -- revenueratio
      limit 1000
      
      Job aborted due to stage failure: Task 11 in stage 62.0 failed 4 times, most recent failure: Lost task 11.3 in stage 62.0 (TID 5289, 10.0.227.73): java.lang.IllegalArgumentException: Unscaled value too large for precision
      	at org.apache.spark.sql.types.Decimal.set(Decimal.scala:76)
      	at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:338)
      	at org.apache.spark.sql.types.Decimal.apply(Decimal.scala)
      	at org.apache.spark.sql.catalyst.expressions.UnsafeRow.getDecimal(UnsafeRow.java:386)
      	at org.apache.spark.sql.catalyst.expressions.JoinedRow.getDecimal(JoinedRow.scala:97)
      	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
      	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
      	at org.apache.spark.sql.execution.joins.HashJoin$$anon$1.next(HashJoin.scala:101)
      	at org.apache.spark.sql.execution.joins.HashJoin$$anon$1.next(HashJoin.scala:74)
      	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.execution.joins.HashJoin$$anon$1.fetchNext(HashJoin.scala:115)
      	at org.apache.spark.sql.execution.joins.HashJoin$$anon$1.hasNext(HashJoin.scala:93)
      	at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
      	at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
      	at org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.processInputs(TungstenAggregationIterator.scala:353)
      	at org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.<init>(TungstenAggregationIterator.scala:587)
      	at org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$1.apply(TungstenAggregate.scala:72)
      	at org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$1.apply(TungstenAggregate.scala:64)
      	at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:706)
      	at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:706)
      	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
      	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
      	at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
      	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
      	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
      	at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
      	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
      	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
      	at org.apache.spark.scheduler.Task.run(Task.scala:88)
      	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
      	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:745)
      

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            davies Davies Liu
            marmbrus Michael Armbrust
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              Created:
              Updated:
              Resolved: