Github user rmetzger commented on a diff in the pull request:
https://github.com/apache/incubator-flink/pull/87#discussion_r15664277
--- Diff: docs/java_api_guide.md ---
@@ -427,6 +403,88 @@ DataSet<Tuple2<String, Integer>> out =
in.project(2,0).types(String.class, Integ
Defining Keys
-------------
+One transformation (join, coGroup) require that a key is defined on
+its argument DataSets, and other transformations (Reduce, GroupReduce,
+Aggregate) allow that the DataSet is grouped on a key before they are
+applied.
+
+A DataSet is grouped as
+{% highlight java %}
+DataSet<...> input = // [...]
+DataSet<...> reduced = input
+ .groupBy(/*define key here*/)
+ .reduceGroup(/*do something*/);
+{% endhighlight %}
+
+The data model of Flink is not based on key-value pairs. Therefore,
+you do not need to physically pack the data set types into keys and
+values. Keys are "virtual": they are defined as functions over the
+actual data to guide the grouping operator.
+
+The simplest case is grouping a data set of Tuples on one or more
+fields of the Tuple:
+{% highlight java %}
+DataSet<Tuple3<Integer,String,Long>> input = // [...]
+DataSet<Tuple3<Integer,String,Long> grouped = input
+ .groupBy(1)
--- End diff --
Aren't the fields 0-indexed? So `groupBy(1)` is the second field (String) ?
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