[SPARK-4481][Streaming][Doc] Fix the wrong description of updateFunc (backport for branch-1.2)

backport for branch-1.2 as per #3356

Author: zsxwing <zsxwing@gmail.com>

Closes #3376 from zsxwing/SPARK-4481-branch-1.2 and squashes the following commits:

53b94e8 [zsxwing] Fix the wrong description of updateFunc

1 files changed, 3 insertions, 4 deletions

diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/PairDStreamFunctions.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/PairDStreamFunctions.scala
index 9467595d30..f405dda6c7 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/PairDStreamFunctions.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/PairDStreamFunctions.scala
@@ -398,10 +398,9 @@ class PairDStreamFunctions[K, V](self: DStream[(K,V)])
    * Return a new "state" DStream where the state for each key is updated by applying
    * the given function on the previous state of the key and the new values of each key.
    * org.apache.spark.Partitioner is used to control the partitioning of each RDD.
-   * @param updateFunc State update function. If `this` function returns None, then
-   *                   corresponding state key-value pair will be eliminated. Note, that
-   *                   this function may generate a different a tuple with a different key
-   *                   than the input key. It is up to the developer to decide whether to
+   * @param updateFunc State update function. Note, that this function may generate a different
+   *                   tuple with a different key than the input key. Therefore keys may be removed
+   *                   or added in this way. It is up to the developer to decide whether to
    *                   remember the partitioner despite the key being changed.
    * @param partitioner Partitioner for controlling the partitioning of each RDD in the new
    *                    DStream