[
https://issues.apache.org/jira/browse/SPARK-9832?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Davies Liu reassigned SPARK-9832:
---------------------------------
Assignee: 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: Davies Liu
> 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}
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
