fhueske commented on a change in pull request #6521: [FLINK-5315][table] Adding
support for distinct operation for table API on DataStream
URL: https://github.com/apache/flink/pull/6521#discussion_r211208758
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File path: docs/dev/table/tableApi.md
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@@ -381,6 +381,36 @@ Table result = orders
{% highlight java %}
Table orders = tableEnv.scan("Orders");
Table result = orders.distinct();
+{% endhighlight %}
+ <p><b>Note:</b> For streaming queries the required state to compute
the query result might grow infinitely depending on the number of distinct
fields. Please provide a query configuration with valid retention interval to
prevent excessive state size. See <a href="streaming.html">Streaming
Concepts</a> for details.</p>
+ </td>
+ </tr>
+ <tr>
+ <td>
+ <strong>Distinct Aggregation</strong><br>
+ <span class="label label-primary">Streaming</span>
+ </td>
+ <td>
+ <p>Similar to a SQL DISTINCT AGGREGATION clause such as COUNT(DISTINCT
a). Returns aggregation results with a following running aggregation operator
to aggregate over rows with only distinct value. Distinct aggregations can
operator with <b>GroupBy Aggregation</b>, <b>GroupBy Window Aggregation</b> and
<b>Over Window Aggregation</b>.</p>
+{% highlight java %}
+Table orders = tableEnv.scan("Orders");
+// Distinct aggregation on group by
+Table groupByDistinctResult = orders
+ .groupBy("a")
+ .select("a, b.sum.distinct as d");
+// Distinct aggregation on time window group by
+Table groupByWindowDistinctResult = orders
+ .window(Tumble.over("5.minutes").on("rowtime").as("w")).groupBy("a, w")
+ .select("a, b.sum.distinct as d");
+// Distinct aggregation on over window
+Table result = orders
+ .window(Over
+ .partitionBy("a")
+ .orderBy("rowtime")
+ .preceding("UNBOUNDED_RANGE")
+ .following("CURRENT_RANGE")
Review comment:
`following` can be omitted (defaults to `CURRENT_RANGE`)
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