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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-9832) TPCDS Q98 Fails
Date Wed, 12 Aug 2015 23:36:46 GMT

     [ https://issues.apache.org/jira/browse/SPARK-9832?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-9832:
-----------------------------------

    Assignee: Apache Spark  (was: Davies Liu)

> TPCDS Q98 Fails
> ---------------
>
>                 Key: SPARK-9832
>                 URL: https://issues.apache.org/jira/browse/SPARK-9832
>             Project: Spark
>          Issue Type: Sub-task
>          Components: SQL
>            Reporter: Michael Armbrust
>            Assignee: Apache Spark
>            Priority: Blocker
>
> {code}
> 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
> {code}
> {code}
> 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)
> {code}



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