[jira] [Updated] (SPARK-31517) SparkR::orderBy with multiple columns descending produces error

["Ross Bowen (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-31517?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Ross Bowen updated SPARK-31517:
-------------------------------
    Summary: SparkR::orderBy with multiple columns descending produces error  (was: orderBy with multiple columns descending does not work properly)

> SparkR::orderBy with multiple columns descending produces error
> ---------------------------------------------------------------
>
>                 Key: SPARK-31517
>                 URL: https://issues.apache.org/jira/browse/SPARK-31517
>             Project: Spark
>          Issue Type: Bug
>          Components: SparkR
>    Affects Versions: 2.4.5
>         Environment: Databricks Runtime 6.5
>            Reporter: Ross Bowen
>            Priority: Major
>
> When specifying two columns within an `orderBy()` function, to attempt to get an ordering by two columns in descending order, an error is returned.
> {code:java}
>  library(magrittr) library(SparkR) cars <- cbind(model = rownames(mtcars), mtcars) carsDF <- createDataFrame(cars) carsDF %>% mutate(rank = over(rank(), orderBy(windowPartitionBy(column("cyl")), desc(column("mpg")), desc(column("disp"))))) %>% head() {code}
> This returns an error:
> {code:java}
>  Error in ns[[i]] : subscript out of bounds{code}
> This seems to be related to the more general issue that the following code, excluding the use of the `desc()` function also fails:
> {code:java}
>  carsDF %>% mutate(rank = over(rank(), orderBy(windowPartitionBy(column("cyl")), column("mpg"), column("disp")))) %>% head(){code}
>  



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