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From dongjoon-hyun <...@git.apache.org>
Subject [GitHub] spark pull request #13798: [SPARKR][DOCS] R code doc cleanup
Date Tue, 21 Jun 2016 06:19:50 GMT
Github user dongjoon-hyun commented on a diff in the pull request:

    https://github.com/apache/spark/pull/13798#discussion_r67813477
  
    --- Diff: R/pkg/R/DataFrame.R ---
    @@ -606,10 +607,10 @@ setMethod("unpersist",
     #'
     #' The following options for repartition are possible:
     #' \itemize{
    -#'  \item{"Option 1"} {Return a new SparkDataFrame partitioned by
    +#'  \item{1.} {Return a new SparkDataFrame partitioned by
     #'                      the given columns into `numPartitions`.}
    -#'  \item{"Option 2"} {Return a new SparkDataFrame that has exactly `numPartitions`.}
    -#'  \item{"Option 3"} {Return a new SparkDataFrame partitioned by the given column(s),
    +#'  \item{2.} {Return a new SparkDataFrame that has exactly `numPartitions`.}
    +#'  \item{3.} {Return a new SparkDataFrame partitioned by the given column(s),
     #'                      using `spark.sql.shuffle.partitions` as number of partitions.}
    --- End diff --
    
    For the ordered itemize, what about the following?
    ```
    #' \enumerate{
    #'  \item Return a new SparkDataFrame partitioned by the given columns into `numPartitions`.
    #'  \item Return a new SparkDataFrame that has exactly `numPartitions`.
    #'  \item Return a new SparkDataFrame partitioned by the given column(s),
    #'                     using `spark.sql.shuffle.partitions` as number of partitions.
    #' }
    ```


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