[FLINK-15999][doc] Fix formatting and links in timely-stream-processing.md

docs/concepts/timely-stream-processing.md

@@ -29,38 +29,47 @@ under the License.
 
 ## Time
 
-When referring to time in a streaming program (for example to define windows), one can refer to different notions
-of time:
+When referring to time in a streaming program (for example to define windows),
+one can refer to different notions of time:
 
-  - **Event Time** is the time when an event was created. It is usually described by a timestamp in the events,
-    for example attached by the producing sensor, or the producing service. Flink accesses event timestamps
-    via [timestamp assigners]({{ site.baseurl }}/dev/event_timestamps_watermarks.html).
+  - **Event Time** is the time when an event was created. It is usually
+    described by a timestamp in the events, for example attached by the
+    producing sensor, or the producing service. Flink accesses event timestamps
+    via [timestamp assigners]({{ site.baseurl
+    }}/dev/event_timestamps_watermarks.html).
 
-  - **Ingestion time** is the time when an event enters the Flink dataflow at the source operator.
+  - **Ingestion time** is the time when an event enters the Flink dataflow at
+    the source operator.
 
-  - **Processing Time** is the local time at each operator that performs a time-based operation.
+  - **Processing Time** is the local time at each operator that performs a
+    time-based operation.
 
 <img src="{{ site.baseurl }}/fig/event_ingestion_processing_time.svg" alt="Event Time, Ingestion Time, and Processing Time" class="offset" width="80%" />
 
-More details on how to handle time are in the [event time docs]({{ site.baseurl }}/dev/event_time.html).
+More details on how to handle time are in the [event time docs]({{ site.baseurl
+}}{% link dev/event_time.md %}).
 
 {% top %}
 
 ## Windows
 
-Aggregating events (e.g., counts, sums) works differently on streams than in batch processing.
-For example, it is impossible to count all elements in a stream,
-because streams are in general infinite (unbounded). Instead, aggregates on streams (counts, sums, etc),
-are scoped by **windows**, such as *"count over the last 5 minutes"*, or *"sum of the last 100 elements"*.
+Aggregating events (e.g., counts, sums) works differently on streams than in
+batch processing.  For example, it is impossible to count all elements in a
+stream, because streams are in general infinite (unbounded). Instead,
+aggregates on streams (counts, sums, etc), are scoped by **windows**, such as
+*"count over the last 5 minutes"*, or *"sum of the last 100 elements"*.
 
-Windows can be *time driven* (example: every 30 seconds) or *data driven* (example: every 100 elements).
-One typically distinguishes different types of windows, such as *tumbling windows* (no overlap),
-*sliding windows* (with overlap), and *session windows* (punctuated by a gap of inactivity).
+Windows can be *time driven* (example: every 30 seconds) or *data driven*
+(example: every 100 elements).  One typically distinguishes different types of
+windows, such as *tumbling windows* (no overlap), *sliding windows* (with
+overlap), and *session windows* (punctuated by a gap of inactivity).
 
 <img src="{{ site.baseurl }}/fig/windows.svg" alt="Time- and Count Windows" class="offset" width="80%" />
 
-More window examples can be found in this [blog post](https://flink.apache.org/news/2015/12/04/Introducing-windows.html).
-More details are in the [window docs](../dev/stream/operators/windows.html).
+More window examples can be found in this [blog
+post](https://flink.apache.org/news/2015/12/04/Introducing-windows.html).  More
+details are in the [window docs]({{ site.baseurl }}{% link
+dev/stream/operators/windows.md %}).
 
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