Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/16137#discussion_r91855194
--- Diff: core/src/main/scala/org/apache/spark/SparkContext.scala ---
@@ -721,16 +732,15 @@ class SparkContext(config: SparkConf) extends Logging
{
}
/**
- * Creates a new RDD[Long] containing elements from `start` to
`end`(exclusive), increased by
+ * Creates a new `RDD[Long]` containing elements from `start` to
`end`(exclusive), increased by
* `step` every element.
*
* @note if we need to cache this RDD, we should make sure each
partition does not exceed limit.
- *
* @param start the start value.
* @param end the end value.
* @param step the incremental step
* @param numSlices the partition number of the new RDD.
- * @return
+ * @return RDD containing distributed range
--- End diff --
Nit: RDDs are really pointers and bookeeping. The "represent" rather than
"contain"
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