[FLINK-15999][doc] Move broadcast state explanation from api doc to c…

…oncepts

This also reorders/massages the text a bit to make it fit in better.

docs/concepts/stateful-stream-processing.md

@@ -104,6 +104,8 @@ as many Key Groups as the defined maximum parallelism. During execution each
 parallel instance of a keyed operator works with the keys for one or more Key
 Groups.
 
+`TODO: potentially leave out Operator State and Broadcast State from concepts documentation`
+
 ## Operator State
 
 *Operator State* (or *non-keyed state*) is state that is is bound to one
@@ -116,9 +118,20 @@ The Operator State interfaces support redistributing state among parallel
 operator instances when the parallelism is changed. There can be different
 schemes for doing this redistribution.
 
-{% top %}
-
-## State Types (Keyed State, Broadcast State)
+## Broadcast State
+
+*Broadcast State* is a special type of *Operator State*. It was introduced to
+support use cases where some data coming from one stream is required to be
+broadcasted to all downstream tasks, where it is stored locally and is used to
+process all incoming elements on the other stream. As an example where
+broadcast state can emerge as a natural fit, one can imagine a low-throughput
+stream containing a set of rules which we want to evaluate against all elements
+coming from another stream. Having the above type of use cases in mind,
+broadcast state differs from the rest of operator states in that:
+ 1. it has a map format,
+ 2. it is only available to specific operators that have as inputs a
+ *broadcasted* stream and a *non-broadcasted* one, and
+ 3. such an operator can have *multiple broadcast states* with different names.
 
 {% top %}
 

docs/dev/stream/state/broadcast_state.md

@@ -25,18 +25,9 @@ under the License.
 * ToC
 {:toc}
 
-[Working with State](state.html) describes operator state which upon restore is either evenly distributed among the 
-parallel tasks of an operator, or unioned, with the whole state being used to initialize the restored parallel tasks.
-
-A third type of supported *operator state* is the *Broadcast State*. Broadcast state was introduced to support use cases
-where some data coming from one stream is required to be broadcasted to all downstream tasks, where it is stored locally
-and is used to process all incoming elements on the other stream. As an example where broadcast state can emerge as a 
-natural fit, one can imagine a low-throughput stream containing a set of rules which we want to evaluate against all 
-elements coming from another stream. Having the above type of use cases in mind, broadcast state differs from the rest 
-of operator states in that:
- 1. it has a map format,
- 2. it is only available to specific operators that have as inputs a *broadcasted* stream and a *non-broadcasted* one, and
- 3. such an operator can have *multiple broadcast states* with different names.
+In this section you will learn about how to use broadcast state in practise. Please refer to [Stateful Stream
+Processing]({{site.baseurl}}{% link concepts/stateful-stream-processing.md %})
+to learn about the concepts behind stateful stream processing. 
 
 ## Provided APIs