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https://issues.apache.org/jira/browse/FLINK-7798?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16204526#comment-16204526
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ASF GitHub Bot commented on FLINK-7798:
---------------------------------------
Github user xccui commented on a diff in the pull request:
https://github.com/apache/flink/pull/4825#discussion_r144688874
--- Diff: docs/dev/table/tableApi.md ---
@@ -498,6 +499,23 @@ Table left = tableEnv.fromDataSet(ds1, "a, b, c");
Table right = tableEnv.fromDataSet(ds2, "d, e, f");
Table result = left.join(right).where("a = d").select("a, b, e");
{% endhighlight %}
+ <p><b>Note:</b> Currently, only time-windowed inner joins can be
processed in a streaming fashion.</p>
+
+ <p>A time-windowed join requires a special join condition that
bounds the time on both sides. This can be done by two appropriate range
predicates (<code> <, <=, >=, ></code>) that compares the <a
href="streaming.html#time-attributes">time attributes</a> of both input tables.
The following rules apply for time predicates:
+ <ul>
+ <li>Time predicates must compare time attributes of both input
tables.</li>
+ <li>Time predicates must compare only time attributes of the
same type, i.e., processing time with processing time or event time with event
time.</li>
+ <li>Only range predicates are valid time predicates.</li>
+ <li>Non-time predicates must not access a time attribute.</li>
--- End diff --
@fhueske, I think the last rule about time attribute access could be
removed now, right?
> Add support for windowed joins to Table API
> -------------------------------------------
>
> Key: FLINK-7798
> URL: https://issues.apache.org/jira/browse/FLINK-7798
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Affects Versions: 1.4.0
> Reporter: Fabian Hueske
> Assignee: Xingcan Cui
> Priority: Blocker
> Fix For: 1.4.0
>
>
> Currently, windowed joins on streaming tables are only supported through SQL.
> The Table API should support these joins as well. For that, we have to adjust
> the Table API validation and translate the API into the respective logical
> plan. Since most of the code should already be there for the batch Table API
> joins, this should be fairly straightforward.
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