asfgit closed pull request #7275: [hotfix] [docs] Fix typo in dynamic tables
documentation
URL: https://github.com/apache/flink/pull/7275
This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:
As this is a foreign pull request (from a fork), the diff is supplied
below (as it won't show otherwise due to GitHub magic):
diff --git a/docs/dev/table/streaming/dynamic_tables.md
b/docs/dev/table/streaming/dynamic_tables.md
index 698cd673185..fba1b6d7eca 100644
--- a/docs/dev/table/streaming/dynamic_tables.md
+++ b/docs/dev/table/streaming/dynamic_tables.md
@@ -66,7 +66,7 @@ With these points in mind, we introduce following concept of
*Dynamic tables* in
Dynamic Tables & Continuous Queries
---------------------------------------
-*Dynamic tables* are the core concept of Flink's Table API and SQL support for
streaming data. In contrast to the static tables that represent batch data,
dynamic table are changing over time. They can be queried like static batch
tables. Querying a dynamic table yields a *Continuous Query*. A continuous
query never terminates and produces a dynamic table as result. The query
continuously updates its (dynamic) result table to reflect the changes on its
input (dynamic) table. Essentially, a continuous query on a dynamic table is
very similar to the definition query of a materialized view.
+*Dynamic tables* are the core concept of Flink's Table API and SQL support for
streaming data. In contrast to the static tables that represent batch data,
dynamic tables are changing over time. They can be queried like static batch
tables. Querying a dynamic table yields a *Continuous Query*. A continuous
query never terminates and produces a dynamic table as result. The query
continuously updates its (dynamic) result table to reflect the changes on its
input (dynamic) table. Essentially, a continuous query on a dynamic table is
very similar to the definition query of a materialized view.
It is important to note that the result of a continuous query is always
semantically equivalent to the result of the same query being executed in batch
mode on a snapshot of the input tables.
@@ -177,7 +177,7 @@ When converting a dynamic table into a stream or writing it
to an external syste
</center>
<br><br>
-* **Upsert stream:** An upsert stream is a stream with two types of messages,
*upsert messages* and *delete message*. A dynamic table that is converted into
an upsert stream requires a (possibly composite) unique key. A dynamic table
with unique key is converted into a dynamic table by encoding `INSERT` and
`UPDATE` changes as upsert message and `DELETE` changes as delete message. The
stream consuming operator needs to be aware of the unique key attribute in
order to apply messages correctly. The main difference to a retract stream is
that `UPDATE` changes are encoded with a single message and hence more
efficient. The following figure visualizes the conversion of a dynamic table
into an upsert stream.
+* **Upsert stream:** An upsert stream is a stream with two types of messages,
*upsert messages* and *delete messages*. A dynamic table that is converted into
an upsert stream requires a (possibly composite) unique key. A dynamic table
with unique key is converted into a dynamic table by encoding `INSERT` and
`UPDATE` changes as upsert message and `DELETE` changes as delete message. The
stream consuming operator needs to be aware of the unique key attribute in
order to apply messages correctly. The main difference to a retract stream is
that `UPDATE` changes are encoded with a single message and hence more
efficient. The following figure visualizes the conversion of a dynamic table
into an upsert stream.
<center>
<img alt="Dynamic tables" src="{{ site.baseurl
}}/fig/table-streaming/redo-mode.png" width="85%">
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
[email protected]
With regards,
Apache Git Services
