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Posted to issues@spark.apache.org by "Marco Gaido (JIRA)" <ji...@apache.org> on 2017/12/16 09:00:02 UTC
[jira] [Commented] (SPARK-22806) Window Aggregate functions:
unexpected result at ordered partition
[ https://issues.apache.org/jira/browse/SPARK-22806?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16293716#comment-16293716 ]
Marco Gaido commented on SPARK-22806:
-------------------------------------
This is the right behavior. Also Postgres works like this. if you specify the order by clause, by default the range is UNBOUNDED PRECEDING - CURRENT ROW.
> Window Aggregate functions: unexpected result at ordered partition
> ------------------------------------------------------------------
>
> Key: SPARK-22806
> URL: https://issues.apache.org/jira/browse/SPARK-22806
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.3.0
> Reporter: Attila Zsolt Piros
> Attachments: WindowFunctionsWithGroupByError.scala
>
>
> I got different results for aggregate functions (even for sum and count) when the partition is ordered "Window.partitionBy(column).orderBy(column))" and when it is not ordered 'Window.partitionBy(column)".
> Example:
> {code:java}
> test("count, sum, stddev_pop functions over window") {
> val df = Seq(
> ("a", 1, 100.0),
> ("b", 1, 200.0)).toDF("key", "partition", "value")
> df.createOrReplaceTempView("window_table")
> checkAnswer(
> df.select(
> $"key",
> count("value").over(Window.partitionBy("partition")),
> sum("value").over(Window.partitionBy("partition")),
> stddev_pop("value").over(Window.partitionBy("partition"))
> ),
> Seq(
> Row("a", 2, 300.0, 50.0),
> Row("b", 2, 300.0, 50.0)))
> }
> test("count, sum, stddev_pop functions over ordered by window") {
> val df = Seq(
> ("a", 1, 100.0),
> ("b", 1, 200.0)).toDF("key", "partition", "value")
> df.createOrReplaceTempView("window_table")
> checkAnswer(
> df.select(
> $"key",
> count("value").over(Window.partitionBy("partition").orderBy("key")),
> sum("value").over(Window.partitionBy("partition").orderBy("key")),
> stddev_pop("value").over(Window.partitionBy("partition").orderBy("key"))
> ),
> Seq(
> Row("a", 2, 300.0, 50.0),
> Row("b", 2, 300.0, 50.0)))
> }
> {code}
> The "count, sum, stddev_pop functions over ordered by window" fails with the error:
> {noformat}
> == Results ==
> !== Correct Answer - 2 == == Spark Answer - 2 ==
> !struct<> struct<key:string,count(value) OVER (PARTITION BY partition ORDER BY key ASC NULLS FIRST unspecifiedframe$()):bigint,sum(value) OVER (PARTITION BY partition ORDER BY key ASC NULLS FIRST unspecifiedframe$()):double,stddev_pop(value) OVER (PARTITION BY partition ORDER BY key ASC NULLS FIRST unspecifiedframe$()):double>
> ![a,2,300.0,50.0] [a,1,100.0,0.0]
> [b,2,300.0,50.0] [b,2,300.0,50.0]
> {noformat}
>
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