You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Wenchen Fan (Jira)" <ji...@apache.org> on 2020/02/27 06:52:00 UTC
[jira] [Assigned] (SPARK-30590) can't use more than five type-safe
user-defined aggregation in select statement
[ https://issues.apache.org/jira/browse/SPARK-30590?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Wenchen Fan reassigned SPARK-30590:
-----------------------------------
Assignee: L. C. Hsieh
> can't use more than five type-safe user-defined aggregation in select statement
> -------------------------------------------------------------------------------
>
> Key: SPARK-30590
> URL: https://issues.apache.org/jira/browse/SPARK-30590
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.2.3, 2.3.4, 2.4.4, 3.0.0
> Reporter: Daniel Mantovani
> Assignee: L. C. Hsieh
> Priority: Major
> Fix For: 3.0.0
>
>
> How to reproduce:
> {code:scala}
> val df = Seq((1,2,3,4,5,6)).toDF("a","b","c","d","e","f")
> import org.apache.spark.sql.expressions.Aggregator
> import org.apache.spark.sql.Encoder
> import org.apache.spark.sql.Encoders
> import org.apache.spark.sql.Row
> case class FooAgg(s:Int) extends Aggregator[Row, Int, Int] {
> def zero:Int = s
> def reduce(b: Int, r: Row): Int = b + r.getAs[Int](0)
> def merge(b1: Int, b2: Int): Int = b1 + b2
> def finish(b: Int): Int = b
> def bufferEncoder: Encoder[Int] = Encoders.scalaInt
> def outputEncoder: Encoder[Int] = Encoders.scalaInt
> }
> val fooAgg = (i:Int) => FooAgg(i).toColumn.name(s"foo_agg_$i")
> scala> df.select(fooAgg(1),fooAgg(2),fooAgg(3),fooAgg(4),fooAgg(5)).show
> +---------+---------+---------+---------+---------+
> |foo_agg_1|foo_agg_2|foo_agg_3|foo_agg_4|foo_agg_5|
> +---------+---------+---------+---------+---------+
> | 3| 5| 7| 9| 11|
> +---------+---------+---------+---------+---------+
> {code}
> With 6 arguments we have error:
> {code:scala}
> scala> df.select(fooAgg(1),fooAgg(2),fooAgg(3),fooAgg(4),fooAgg(5),fooAgg(6)).show
> org.apache.spark.sql.AnalysisException: unresolved operator 'Aggregate [fooagg(FooAgg(1), None, None, None, input[0, int, false] AS value#114, assertnotnull(cast(value#114 as int)), input[0, int, false] AS value#113, IntegerType, IntegerType, false) AS foo_agg_1#116, fooagg(FooAgg(2), None, None, None, input[0, int, false] AS value#119, assertnotnull(cast(value#119 as int)), input[0, int, false] AS value#118, IntegerType, IntegerType, false) AS foo_agg_2#121, fooagg(FooAgg(3), None, None, None, input[0, int, false] AS value#124, assertnotnull(cast(value#124 as int)), input[0, int, false] AS value#123, IntegerType, IntegerType, false) AS foo_agg_3#126, fooagg(FooAgg(4), None, None, None, input[0, int, false] AS value#129, assertnotnull(cast(value#129 as int)), input[0, int, false] AS value#128, IntegerType, IntegerType, false) AS foo_agg_4#131, fooagg(FooAgg(5), None, None, None, input[0, int, false] AS value#134, assertnotnull(cast(value#134 as int)), input[0, int, false] AS value#133, IntegerType, IntegerType, false) AS foo_agg_5#136, fooagg(FooAgg(6), None, None, None, input[0, int, false] AS value#139, assertnotnull(cast(value#139 as int)), input[0, int, false] AS value#138, IntegerType, IntegerType, false) AS foo_agg_6#141];;
> 'Aggregate [fooagg(FooAgg(1), None, None, None, input[0, int, false] AS value#114, assertnotnull(cast(value#114 as int)), input[0, int, false] AS value#113, IntegerType, IntegerType, false) AS foo_agg_1#116, fooagg(FooAgg(2), None, None, None, input[0, int, false] AS value#119, assertnotnull(cast(value#119 as int)), input[0, int, false] AS value#118, IntegerType, IntegerType, false) AS foo_agg_2#121, fooagg(FooAgg(3), None, None, None, input[0, int, false] AS value#124, assertnotnull(cast(value#124 as int)), input[0, int, false] AS value#123, IntegerType, IntegerType, false) AS foo_agg_3#126, fooagg(FooAgg(4), None, None, None, input[0, int, false] AS value#129, assertnotnull(cast(value#129 as int)), input[0, int, false] AS value#128, IntegerType, IntegerType, false) AS foo_agg_4#131, fooagg(FooAgg(5), None, None, None, input[0, int, false] AS value#134, assertnotnull(cast(value#134 as int)), input[0, int, false] AS value#133, IntegerType, IntegerType, false) AS foo_agg_5#136, fooagg(FooAgg(6), None, None, None, input[0, int, false] AS value#139, assertnotnull(cast(value#139 as int)), input[0, int, false] AS value#138, IntegerType, IntegerType, false) AS foo_agg_6#141]
> +- Project [_1#6 AS a#13, _2#7 AS b#14, _3#8 AS c#15, _4#9 AS d#16, _5#10 AS e#17, _6#11 AS F#18]
> +- LocalRelation [_1#6, _2#7, _3#8, _4#9, _5#10, _6#11]
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:43)
> at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:95)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$3.apply(CheckAnalysis.scala:431)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$3.apply(CheckAnalysis.scala:430)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:430)
> at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:95)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$executeAndCheck$1.apply(Analyzer.scala:108)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$executeAndCheck$1.apply(Analyzer.scala:105)
> at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.markInAnalyzer(AnalysisHelper.scala:201)
> at org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:105)
> at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:57)
> at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:55)
> at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:47)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:78)
> at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:3412)
> at org.apache.spark.sql.Dataset.select(Dataset.scala:1340)
> ... 50 elided
> {code}
>
>
>
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org