sjwiesman commented on a change in pull request #14257:
URL: https://github.com/apache/flink/pull/14257#discussion_r533833261
##########
File path: docs/dev/table/streaming/temporal_tables.md
##########
@@ -36,6 +36,14 @@ For the changing dimension table, Flink allows for accessing
the content of the
Motivation
----------
Review comment:
temporal tables got a lot of new features in 1.12. Please rebase,
unfortunately, a lot of what you did is no longer relevant.
##########
File path: docs/dev/table/streaming/unbounded-data-processing/joins.md
##########
@@ -22,17 +22,18 @@ specific language governing permissions and limitations
under the License.
-->
-Joins are a common and well-understood operation in batch data processing to
connect the rows of two relations. However, the semantics of joins on [dynamic
tables](dynamic_tables.html) are much less obvious or even confusing.
+Joins are a common and well-understood operation in batch data processing to
connect the rows of two relations. However, the semantics of joins on [dynamic
tables](dynamic_tables.html) representing unbounded data are fairly
non-trivial.
-Because of that, there are a couple of ways to actually perform a join using
either Table API or SQL.
+However there are a couple of ways to actually perform a join using either
Table API or SQL.
For more information regarding the syntax, please check the join sections in
[Table API](../tableApi.html#joins) and [SQL]({{ site.baseurl
}}/dev/table/sql/queries.html#joins).
+//TODO: Explain the complications of unbounded joins
Review comment:
remove todo
##########
File path: docs/dev/table/streaming/unbounded-data-processing/joins.md
##########
@@ -22,17 +22,18 @@ specific language governing permissions and limitations
under the License.
-->
-Joins are a common and well-understood operation in batch data processing to
connect the rows of two relations. However, the semantics of joins on [dynamic
tables](dynamic_tables.html) are much less obvious or even confusing.
+Joins are a common and well-understood operation in batch data processing to
connect the rows of two relations. However, the semantics of joins on [dynamic
tables](dynamic_tables.html) representing unbounded data are fairly
non-trivial.
-Because of that, there are a couple of ways to actually perform a join using
either Table API or SQL.
+However there are a couple of ways to actually perform a join using either
Table API or SQL.
For more information regarding the syntax, please check the join sections in
[Table API](../tableApi.html#joins) and [SQL]({{ site.baseurl
}}/dev/table/sql/queries.html#joins).
+//TODO: Explain the complications of unbounded joins
* This will be replaced by the TOC
{:toc}
-Regular Joins
--------------
+Regular Joins and its challenges
+---------------------------------------
Review comment:
Lets get rid of "and its challenges". We want to make flink more
approachable :)
##########
File path: docs/dev/table/streaming/unbounded-data-processing/joins.md
##########
@@ -351,4 +339,20 @@ FROM
<span class="label label-danger">Attention</span> Flink does not support event
time temporal table joins currently.
+### Temporal Table joins vs Other joins
+
+In contrast to [regular joins](#regular-joins), the previous results of the
temporal table join will not be affected despite the changes on the build side.
Also, the temporal table join operator is very lightweight and does not keep
any state.
+
+Compared to [interval joins](#interval-joins), temporal table joins do not
define a time window within which the records will be joined.
Review comment:
again, 1.12 added support for temporal event time table joins so this
needs to be updated.
##########
File path: docs/dev/table/streaming/unbounded-data-processing/joins.md
##########
@@ -351,4 +339,20 @@ FROM
<span class="label label-danger">Attention</span> Flink does not support event
time temporal table joins currently.
+### Temporal Table joins vs Other joins
+
+In contrast to [regular joins](#regular-joins), the previous results of the
temporal table join will not be affected despite the changes on the build side.
Also, the temporal table join operator is very lightweight and does not keep
any state.
Review comment:
Also doesn't sound right here.
```suggestion
In contrast to [regular joins](#regular-joins), the previous results of the
temporal table join will not be affected despite the changes on the build side.
The temporal table join operator is very lightweight and does not keep any
state.
```
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