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https://issues.apache.org/jira/browse/FLINK-9877?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16561686#comment-16561686
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ASF GitHub Bot commented on FLINK-9877:
---------------------------------------
zentol commented on a change in pull request #6407: [FLINK-9877][docs] Add
documentation page for different datastream joins
URL: https://github.com/apache/flink/pull/6407#discussion_r206065563
##########
File path: docs/dev/stream/operators/joining.md
##########
@@ -0,0 +1,284 @@
+---
+title: "Joining"
+nav-id: streaming_joins
+nav-show_overview: true
+nav-parent_id: streaming_operators
+nav-pos: 11
+---
+<!--
+Licensed to the Apache Software Foundation (ASF) under one
+or more contributor license agreements. See the NOTICE file
+distributed with this work for additional information
+regarding copyright ownership. The ASF licenses this file
+to you under the Apache License, Version 2.0 (the
+"License"); you may not use this file except in compliance
+with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing,
+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied. See the License for the
+specific language governing permissions and limitations
+under the License.
+-->
+
+* toc
+{:toc}
+
+# Window Join
+A window join joins the elements of two streams that share a common key and
lie in the same window. These windows can be defined by using a [window
assigner]({{ site.baseurl}}/dev/stream/operators/windows.html#window-assigners)
and are evaluated on elements from both of the streams.
+
+The elements from both sides are then passed to a user-defined `JoinFunction`
or `FlatJoinFunction` where the user can emit results that meet the join
criteria.
+
+The general usage can be summarized as follows:
+
+{% highlight java %}
+stream.join(otherStream)
+ .where(<KeySelector>)
+ .equalTo(<KeySelector>)
+ .window(<WindowAssigner>)
+ .apply(<JoinFunction>)
+{% endhighlight %}
+
+Some notes on semantics:
+- The creation of pairwise combinations of elements of the two streams behaves
like an inner-join, meaning elements from one stream will not be emitted if
they don't have a corresponding element from the other stream to be joined with.
+- Those elements that do get joined will have as their timestamp the largest
timestamp that still lies in the respective window. For example a window with
`[5, 10)` as its boundaries would result in the joined elements having 9 as
their timestamp.
+
+In the following section we are going to give an overview over how different
kinds of window joins behave using some exemplary scenarios.
+
+## Tumbling Window Join
+When performing a tumbling window join, all elements with a common key and a
common tumbling window are joined as pairwise combinations and passed on to a
`JoinFunction` or `FlatJoinFunction`. Because this behaves like an inner join,
elements of one stream that do not have elements from another stream in their
tumbling window are not emitted!
+
+<img src="{{ site.baseurl }}/fig/tumbling-window-join.svg" class="center"
style="width: 80%;" />
+
+As illustrated in the figure, we define a tumbling window with the size of 2
milliseconds, which results in windows of the form `[0,1], [2,3], ...`. The
image shows the pairwise combinations of all elements in each window which will
be passed on to the `JoinFunction`. Note that in the tumbling window `[6,7]`
nothing is emitted because no elements exist in the green stream to be joined
with the orange elements ⑥ and ⑦.
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+import org.apache.flink.api.java.functions.KeySelector;
+import
org.apache.flink.streaming.api.windowing.assigners.TumblingEventTimeWindows;
+import org.apache.flink.streaming.api.windowing.time.Time;
+
+...
+
+DataStream<Integer> orangeStream = ...
+DataStream<Integer> greenStream = ...
+
+orangeStream.join(greenStream)
+ .where(<KeySelector>)
+ .equalTo(<KeySelector>)
+ .window(TumblingEventTimeWindows.of(Time.seconds(2)))
+ .apply (new JoinFunction<Integer, Integer, String> () {
+ @Override
+ public String join(Integer first, Integer second) {
+ return first + "," + second;
+ }
+ });
+ {% endhighlight %}
+</div>
+<div data-lang="scala" markdown="1">
+
+{% highlight scala %}
+import
org.apache.flink.streaming.api.windowing.assigners.SlidingEventTimeWindows;
+import org.apache.flink.streaming.api.windowing.time.Time;
+
+...
+
+val orangeStream: DataStream[Integer] = ...
+val greenStream: DataStream[Integer] = ...
+
+orangeStream.join(greenStream)
+ .where(elem => /* select key */)
+ .equalTo(elem => /* select key */)
+ .window(TumblingEventTimeWindows.of(Time.milliseconds(2)))
+ .apply { (e1, e2) => e1 + "," + e2 }
+ {% endhighlight %}
+
+</div>
+</div>
+
+## Sliding Window Join
+When performing a sliding window join, all elements with a common key and
common sliding window are joined are pairwise combinations and passed on to the
`JoinFunction` or `FlatJoinFunction`. Elements of one stream that do not have
elements from the other stream in the current sliding window are not emitted!
Note that some elements might be joined in one sliding window but not in
another!
+
+<img src="{{ site.baseurl }}/fig/sliding-window-join.svg" class="center"
style="width: 80%;" />
+
+In this example we are using sliding windows with a size of two milliseconds
and slide them by one millisecond, resulting in the sliding windows `[-1,
0],[0,1],[1,2],[2,3], …`.<!-- TODO: Can -1 actually exist?--> The joined
elements below the x-axis are the ones that are passed to the `JoinFunction`
for each sliding window. Here you can also see how for example the orange ② is
joined with the green ③ in the window `[2,3]`, but is not joined with anything
in the window `[1,2]`.
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+
+{% highlight java %}
+import org.apache.flink.api.java.functions.KeySelector;
+import
org.apache.flink.streaming.api.windowing.assigners.SlidingEventTimeWindows;
+import org.apache.flink.streaming.api.windowing.time.Time;
+
+...
+
+DataStream<Integer> orangeStream = ...
+DataStream<Integer> greenStream = ...
+
+orangeStream.join(greenStream)
+ .where(<KeySelector>)
+ .equalTo(<KeySelector>)
+ .window(SlidingEventTimeWindows.of(Time.milliseconds(2) /* size */,
Time.milliseconds(1) /* slide */))
+ .apply (new JoinFunction<Integer, Integer, String> () {
+ @Override
+ public String join(Integer first, Integer second) {
+ return first + "," + second;
+ }
+ });
+ {% endhighlight %}
+</div>
+<div data-lang="scala" markdown="1">
+
+{% highlight scala %}
+import
org.apache.flink.streaming.api.windowing.assigners.SlidingEventTimeWindows;
+import org.apache.flink.streaming.api.windowing.time.Time;
+
+...
+
+val orangeStream: DataStream[Integer] = ...
+val greenStream: DataStream[Integer] = ...
+
+orangeStream.join(greenStream)
+ .where(elem => /* select key */)
+ .equalTo(elem => /* select key */)
+ .window(SlidingEventTimeWindows.of(Time.milliseconds(2) /* size */,
Time.milliseconds(1) /* slide */))
+ .apply { (e1, e2) => e1 + "," + e2 }
+ {% endhighlight %}
+</div>
+</div>
+
+## Session Window Join
+When performing a session window join, all elements with the same key that
when _"combined"_ fulfill the session criteria are joined in pairwise
combinations and passed on to the `JoinFunction` or `FlatJoinFunction`. Again
this performs an inner join, so if there is a session window that only contains
elements from one stream, no output will be emitted!
+
+<img src="{{ site.baseurl }}/fig/session-window-join.svg" class="center"
style="width: 80%;" />
+
+Here we define a session window join where each session is divided by a gap of
at least 1ms. There are three sessions, and in the first two sessions the
joined elements from both streams are passed to the `JoinFunction`. In the
third session there are no elements in the green stream, so ⑧ and ⑨ are not
joined!
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+
+{% highlight java %}
+import org.apache.flink.api.java.functions.KeySelector;
+import
org.apache.flink.streaming.api.windowing.assigners.EventTimeSessionWindows;
+import org.apache.flink.streaming.api.windowing.time.Time;
+
+...
+
+DataStream<Integer> orangeStream = ...
+DataStream<Integer> greenStream = ...
+
+orangeStream.join(greenStream)
+ .where(<KeySelector>)
+ .equalTo(<KeySelector>)
+ .window(EventTimeSessionWindows.withGap(Time.milliseconds(1)))
+ .apply (new JoinFunction<Integer, Integer, String> () {
+ @Override
+ public String join(Integer first, Integer second) {
+ return first + "," + second;
+ }
+ });
+ {% endhighlight %}
+</div>
+<div data-lang="scala" markdown="1">
+
+{% highlight scala %}
+import
org.apache.flink.streaming.api.windowing.assigners.EventTimeSessionWindows;
+import org.apache.flink.streaming.api.windowing.time.Time;
+
+...
+
+val orangeStream: DataStream[Integer] = ...
+val greenStream: DataStream[Integer] = ...
+
+orangeStream.join(greenStream)
+ .where(elem => /* select key */)
+ .equalTo(elem => /* select key */)
+ .window(EventTimeSessionWindows.withGap(Time.milliseconds(1)))
+ .apply { (e1, e2) => e1 + "," + e2 }
+ {% endhighlight %}
+
+</div>
+</div>
+
+# Interval Join
+The interval join joins elements of two streams (we'll call them A & B for
now) with a common key and where elements of stream B have timestamps that lie
in a relative time interval to timestamps of elements in stream A.
+
+This can also expressed a little more formally as
Review comment:
I would also remove `a little`.
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> Add separate docs page for different join types in DataStream API
> -----------------------------------------------------------------
>
> Key: FLINK-9877
> URL: https://issues.apache.org/jira/browse/FLINK-9877
> Project: Flink
> Issue Type: Sub-task
> Components: Documentation
> Reporter: Florian Schmidt
> Assignee: Florian Schmidt
> Priority: Major
> Labels: pull-request-available
> Fix For: 1.6.0
>
>
> https://github.com/apache/flink/pull/6407
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