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[DOCS] Added important updateStateByKey details

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

Author: Michael Vogiatzis <michaelvogiatzis@gmail.com>

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
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Michael Vogiatzis 2015-07-09 19:53:23 -07:00 committed by Tathagata Das
parent 1903641e68
commit d538919cc4
1 changed files with 2 additions and 0 deletions
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docs/streaming-programming-guide.md
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@ -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: