sjwiesman commented on a change in pull request #12592:
URL: https://github.com/apache/flink/pull/12592#discussion_r444452641
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File path: docs/try-flink/table_api.md
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@@ -183,20 +183,22 @@ TableEnvironment tEnv = TableEnvironment.create(settings);
{% endhighlight %}
One of Flink's unique properties is that it provides consistent semantics
across batch and streaming.
-This means you can develop and test applications in batch mode on static
datasets, and deploy to production as streaming applications!
+This means you can develop and test applications in batch mode on static
datasets, and deploy to production as streaming applications.
## Attempt One
Now with the skeleton of a Job set-up, you are ready to add some business
logic.
The goal is to build a report that shows the total spend for each account
across each hour of the day.
This means the timestamp column needs be be rounded down from millisecond to
hour granularity.
-Just like a SQL query, Flink can select the required fields and group by your
keys.
+Flink supports developing relational applications in pure [SQL]({% link
dev/table/sql/index.md %}) or using the [Table API]({% link
dev/table/tableApi.md %}).
+The Table API is a fluent DSL inspired, that can be written in Python, Java,
or Scala and supports strong IDE integration.
Review comment:
Whoops, yes nice catch
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