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https://issues.apache.org/jira/browse/FLINK-9712?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16629091#comment-16629091
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ASF GitHub Bot commented on FLINK-9712:
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fhueske commented on a change in pull request #6741: [FLINK-9712][table,docs]
Document processing time Temporal Table Joins
URL: https://github.com/apache/flink/pull/6741#discussion_r220635686
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File path: docs/dev/table/streaming/joins.md
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@@ -0,0 +1,93 @@
+---
+title: "Joins"
+nav-parent_id: streaming_tableapi
+nav-pos: 3
+---
+<!--
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+-->
+
+In batch processing joins are relatively easy, since we are working on a
bounded completed data sets.
+In stream processing things are a little bit more complicated, especially when
it comes to the issue how to handle that data can change over time.
+Because of that, there are couple of ways to actually perform the join using
either Table API or SQL.
+
+For more information regarding syntax please check Joins sections in [Table
API](../tableApi.html#joins) and [SQL](../sql.html#joins).
+
+* This will be replaced by the TOC
+{:toc}
+
+Regular Joins
+-------------
+
+This is the most basic case in which any new records or changes to either side
of the join input are visible and are affecting whole join result.
+If there is a new record on the left side, it will be joined with all of the
previous and future records on the other side.
+
+Such semantic has an important limitation:
+it requires to keep both sides of the join input on the state indefinitely and
resource usage will grow indefinitely as well.
+
+Example:
+{% highlight sql %}
+SELECT * FROM Orders
+INNER JOIN Product
+ON Orders.productId = Product.id
+{% endhighlight %}
+
+Time-windowed Joins
+-------------------
+
+In this case we are restricting scope of the join to some time window.
+This allows Flink to remove old values from the state (using
[watermarks](time_attributes.html) without affecting the correctness of the
result.
+
+Example:
+{% highlight sql %}
+SELECT *
+FROM
+ Orders o,
+ Shipments s
+WHERE o.id = s.orderId AND
+ o.ordertime BETWEEN s.shiptime - INTERVAL '4' HOUR AND s.shiptime
+{% endhighlight %}
+
+Temporal Table Joins
+--------------------
+
+Temporal Table Joins allow to join a stream (left/probe side) with a table
(right/build side) that changes over time.
+For each record from the probe side, it will be joined only with the latest
version of the build side.
+That means (in contrast to [Regular Joins](#regular-joins)) if there is a new
record on the build side,
+it will not affect the previous past results of the join.
+This again allow Flink to limit the number of elements that must be kept on
the state.
+In order to support updates (overwrites) of previous values on the build side
table, this table must define a primary key.
+
+Compared to [Time-windowed Joins](#time-windowed-joins),
+Temporal Table Joins are not defining a time window within which bounds the
records will be joined.
+Records from the probe side are joined with the most recent versions of the
build side and records on the build side might be arbitrary old.
Review comment:
We need to rephrase "most recent version" once we support event time. Maybe
it makes sense to explain this a bit more general. This would also help to
understand the syntax better (why do we need to pass a proc time attribute into
the temporal table function?)
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> Support enrichment joins in Flink SQL/Table API
> -----------------------------------------------
>
> Key: FLINK-9712
> URL: https://issues.apache.org/jira/browse/FLINK-9712
> Project: Flink
> Issue Type: New Feature
> Components: Table API & SQL
> Affects Versions: 1.5.0
> Reporter: Piotr Nowojski
> Assignee: Piotr Nowojski
> Priority: Major
> Labels: pull-request-available
>
> As described here:
> https://docs.google.com/document/d/1KaAkPZjWFeu-ffrC9FhYuxE6CIKsatHTTxyrxSBR8Sk/edit?usp=sharing
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