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 2020/03/30 05:39:00 UTC
[jira] [Resolved] (SPARK-30532)
DataFrameStatFunctions.approxQuantile doesn't work with TABLE.COLUMN syntax
[ https://issues.apache.org/jira/browse/SPARK-30532?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Wenchen Fan resolved SPARK-30532.
---------------------------------
Fix Version/s: 3.0.0
Resolution: Fixed
Issue resolved by pull request 27916
[https://github.com/apache/spark/pull/27916]
> DataFrameStatFunctions.approxQuantile doesn't work with TABLE.COLUMN syntax
> ---------------------------------------------------------------------------
>
> Key: SPARK-30532
> URL: https://issues.apache.org/jira/browse/SPARK-30532
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.4.4
> Reporter: Chris Suchanek
> Priority: Minor
> Fix For: 3.0.0
>
>
> The DataFrameStatFunctions.approxQuantile doesn't work with fully qualified column name (i.e TABLE_NAME.COLUMN_NAME) which is often the way you refer to the column when working with joined dataframes having ambiguous column names.
> See code below for example.
> {code:java}
> import scala.util.Random
> val l = (0 to 1000).map(_ => Random.nextGaussian() * 1000)
> val df1 = sc.parallelize(l).toDF("num").as("tt1")
> val df2 = sc.parallelize(l).toDF("num").as("tt2")
> val dfx = df2.crossJoin(df1)
> dfx.stat.approxQuantile("tt1.num", Array(0.1), 0.0)
> // throws: java.lang.IllegalArgumentException: Field "tt1.num" does not exist.
> Available fields: num
> dfx.stat.approxQuantile("num", Array(0.1), 0.0)
> // throws: org.apache.spark.sql.AnalysisException: Reference 'num' is ambiguous, could be: tt2.num, tt1.num.;{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