[DOCS] Added important updateStateByKey details

Runs for *all* existing keys and returning "None" will remove the key-value pair.

Author: Michael Vogiatzis <[email protected]>

Closes #7229 from mvogiatzis/patch-1 and squashes the following commits:

e7a2946 [Michael Vogiatzis] Updated updateStateByKey text
00283ed [Michael Vogiatzis] Removed space
c2656f9 [Michael Vogiatzis] Moved description farther up
0a42551 [Michael Vogiatzis] Added important updateStateByKey details

(cherry picked from commit d538919)
Signed-off-by: Tathagata Das <[email protected]>

Author: mvogiatzis

docs/streaming-programming-guide.md

@@ -854,6 +854,8 @@ it with new information. To use this, you will have to do two steps.
 1. Define the state update function - Specify with a function how to update the state using the
 previous state and the new values from an input stream.
 
+In every batch, Spark will apply the state  update function for all existing keys, regardless of whether they have new data in a batch or not. If the update function returns `None` then the key-value pair will be eliminated.
+
 Let's illustrate this with an example. Say you want to maintain a running count of each word
 seen in a text data stream. Here, the running count is the state and it is an integer. We
 define the update function as: