Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/3712#discussion_r132160738
--- Diff: docs/dev/table/sourceSinks.md ---
@@ -202,7 +202,38 @@ val csvTableSource = CsvTableSource
Provided TableSinks
-------------------
-**TODO**
+### JDBCAppendSink
+
+<code>JDBCAppendSink</code> allows you to bridge the data stream to the
JDBC driver. The sink only supports append-only data. It does not support
retractions and upserts from Flink's perspectives. However, you can customize
the query using <code>REPLACE</code> or <code>INSERT OVERWRITE</code> to
implement upsert inside the database.
+
+To use the JDBC sink, you have to add the JDBC connector dependency
(<code>flink-jdbc</code>) to your project. Then you can create the sink using
<code>JDBCAppendSinkBuilder</code>:
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+
+JDBCAppendTableSink sink = JDBCAppendTableSink.builder()
+ .setDrivername("org.apache.derby.jdbc.EmbeddedDriver")
+ .setDBUrl("jdbc:derby:memory:ebookshop")
+ .setQuery("INSERT INTO books (id) VALUES (?)")
+ .setFieldTypes(new TypeInformation<?>[] {INT_TYPE_INFO})
+ .build();
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+val sink = JDBCAppendTableSink.builder()
+ .setDrivername("org.apache.derby.jdbc.EmbeddedDriver")
+ .setDBUrl("jdbc:derby:memory:ebookshop")
+ .setQuery("INSERT INTO books (id) VALUES (?)")
+ .setFieldTypes(Array(INT_TYPE_INFO))
--- End diff --
use varargs?
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