Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/12887#discussion_r62148066
--- Diff: R/pkg/R/DataFrame.R ---
@@ -570,10 +570,17 @@ setMethod("unpersist",
#' Repartition
#'
-#' Return a new SparkDataFrame that has exactly numPartitions partitions.
-#'
+#' The following options for repartition are possible:
+#' \itemize{
+#' \item{"Option 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 columns,
+#' preserving the existing number of partitions.}
--- End diff --
We support:
repartition(N)
repartition(N, col1, col2)
repartition(col1, col2)
For the third case, the number of partition is
spark.sql.shuffle.partitions, not preserving the existing number of partitions.
Have I misunderstood something?
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