[SPARK-13087] Grouping by a complex expression may lead to incorrect AttributeReferences in aggregations - ASF JIRA

Details

Type: Bug
Status: Resolved
Priority: Critical
Resolution: Fixed
Affects Version/s: 1.6.0, 2.0.0
Fix Version/s: 1.6.1, 2.0.0
Component/s: SQL
Labels:
None

Target Version/s:

1.6.1

Description

This is a regression from 1.5.

An example of the failure:

Working with this table...

0: jdbc:hive2://10.1.3.203:10000> DESCRIBE csd_0ae1abc1_a3af_4c63_95b0_9599faca6c3d;
+-----------------------+------------+----------+--+
|       col_name        | data_type  | comment  |
+-----------------------+------------+----------+--+
| c_date                | timestamp  | NULL     |
| c_count               | int        | NULL     |
| c_location_fips_code  | string     | NULL     |
| c_airtemp             | float      | NULL     |
| c_dewtemp             | float      | NULL     |
| c_pressure            | int        | NULL     |
| c_rain                | float      | NULL     |
| c_snow                | float      | NULL     |
+-----------------------+------------+----------+--+

...and this query (which isn't necessarily all that sensical or useful, but has been adapted from a similarly failing query that uses a custom UDF where the Spark SQL built-in `day` function has been substituted into this query)...

SELECT day ( c_date )  AS c_date, percentile_approx(c_rain, 0.5) AS c_expr_1256887735 FROM csd_0ae1abc1_a3af_4c63_95b0_9599faca6c3d GROUP BY day ( c_date )  ORDER BY c_date;

Spark 1.5 produces the expected results without error.

In Spark 1.6, this plan is produced...

Exchange rangepartitioning(c_date#63009 ASC,16), None
+- SortBasedAggregate(key=[dayofmonth(cast(c_date#63011 as date))#63020], functions=[(hiveudaffunction(HiveFunctionWrapper(org.apache.hadoop.hive.ql.udf.generic.GenericUDAFPercentileApprox,org.apache.hadoop.hive.ql.udf.generic.Gene
ricUDAFPercentileApprox@6f211801),c_rain#63017,0.5,false,0,0),mode=Complete,isDistinct=false)], output=[c_date#63009,c_expr_1256887735#63010])
   +- ConvertToSafe
      +- !Sort [dayofmonth(cast(c_date#63011 as date))#63020 ASC], false, 0
         +- !TungstenExchange hashpartitioning(dayofmonth(cast(c_date#63011 as date))#63020,16), None
            +- ConvertToUnsafe
               +- HiveTableScan [c_date#63011,c_rain#63017], MetastoreRelation default, csd_0ae1abc1_a3af_4c63_95b0_9599faca6c3d, None

...which fails with a TreeNodeException and stack traces that include this...

Caused by: ! org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2842.0 failed 4 times, most recent failure: Lost task 0.3 in stage 2842.0 (TID 15007, ip-10-1-1-59.dev.clearstory.com): org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: dayofmonth(cast(c_date#63011 as date))#63020
        at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:49)
        at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:86)
        at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:85)
        at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:259)
        at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:259)
        at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
        at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:258)
        at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:249)
        at org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:85)
        at org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection$$anonfun$$init$$2.apply(Projection.scala:62)
        at org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection$$anonfun$$init$$2.apply(Projection.scala:62)
        at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
        at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
        at scala.collection.immutable.List.foreach(List.scala:318)
        at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
        at scala.collection.AbstractTraversable.map(Traversable.scala:105)
        at org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection.<init>(Projection.scala:62)
        at org.apache.spark.sql.execution.SparkPlan$$anonfun$newMutableProjection$1.apply(SparkPlan.scala:254)
        at org.apache.spark.sql.execution.SparkPlan$$anonfun$newMutableProjection$1.apply(SparkPlan.scala:254)
        at org.apache.spark.sql.execution.Exchange.org$apache$spark$sql$execution$Exchange$$getPartitionKeyExtractor$1(Exchange.scala:196)
        at org.apache.spark.sql.execution.Exchange$$anonfun$3.apply(Exchange.scala:208)
        at org.apache.spark.sql.execution.Exchange$$anonfun$3.apply(Exchange.scala:207)
        at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$21.apply(RDD.scala:728)
        at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$21.apply(RDD.scala:728)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
        at org.apache.spark.scheduler.Task.run(Task.scala:89)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.RuntimeException: Couldn't find dayofmonth(cast(c_date#63011 as date))#63020 in [c_date#63011,c_rain#63017]
        at scala.sys.package$.error(package.scala:27)
        at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:92)
        at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:86)
        at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:48)
        ... 33 more

It is possible to work around the problem by adding a Project node in case an aggregation is relying on aliases missing in the child plan (https://github.com/mbautin/spark/commit/2e99064b42a6dddf6b94b989c744a1308aacaee2), but it seems there should be a deeper fix that prevents the problem instead of covering for it.

yhuai I think this problem crept in with the changes for ~~SPARK-9830~~

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is related to

SPARK-26041 catalyst cuts out some columns from dataframes: org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute

Resolved

links to

[Github] Pull Request #11011 (marmbrus)

[Github] Pull Request #11013 (marmbrus)

Grouping by a complex expression may lead to incorrect AttributeReferences in aggregations

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