Github user roshannaik commented on a diff in the pull request:
https://github.com/apache/storm/pull/1914#discussion_r100959018
--- Diff: docs/Joins.md ---
@@ -0,0 +1,126 @@
+---
+title: Joining Streams in Storm Core
+layout: documentation
+documentation: true
+---
+
+Storm core supports joining multiple data streams into one with the help
of `JoinBolt`.
+`JoinBolt` is a Windowed bolt, i.e. it waits for the configured window
duration to match up the
+tuples among the streams being joined. This helps align the streams within
a Window boundary.
+
+Each of `JoinBolt`'s incoming data streams must be Fields Grouped on a
single field. A stream
+should only be joined with the other streams using the field on which it
has been FieldsGrouped.
+Knowing this will help understand the join syntax described below.
+
+## Performing Joins
+Consider the following SQL join involving 4 tables:
+
+```sql
+select userId, key4, key2, key3
+from table1
+inner join table2 on table2.userId = table1.key1
+inner join table3 on table3.key3 = table2.userId
+left join table4 on table4.key4 = table3.key3
+```
+
+Similar joins could be expressed on tuples generated by 4 spouts using
`JoinBolt`:
+
+```java
+JoinBolt jbolt = new JoinBolt("spout1", "key1") // from
spout1
+ .join ("spout2", "userId", "spout1") //
inner join spout2 on spout2.userId = spout1.key1
+ .join ("spout3", "key3", "spout2") //
inner join spout3 on spout3.key3 = spout2.userId
+ .leftJoin ("spout4", "key4", "spout3") // left
join spout4 on spout4.key4 = spout3.key3
+ .select ("userId, key4, key2, spout3:key3") //
chose output fields
+ .withTumblingWindow( new Duration(10,
TimeUnit.MINUTES) ) ;
+
+topoBuilder.setBolt("joiner", jbolt, 1)
+ .fieldsGrouping("spout1", new Fields("key1") )
+ .fieldsGrouping("spout2", new Fields("userId") )
+ .fieldsGrouping("spout3", new Fields("key3") )
+ .fieldsGrouping("spout4", new Fields("key4") );
+```
+
+The bolt constructor takes two arguments. The 1st argument introduces the
data from `spout1`'
+to be the first stream and specifies that it will always use field `key1`
when joining this with the others streams.
+The name of the component specified must refer to the spout or bolt that
is directly connected to the Join bolt.
+Here data received from `spout1` must be fields grouped on `key1`.
Similarly, each of the `leftJoin()` and `join()` method
+calls introduce a new stream along with the field to use for the join. As
seen in above example, the same FieldsGrouping
+requirement applies to these streams as well. The 3rd argument to the join
methods refers to another stream with which
+to join.
+
+The `select()` method is used to specify the output fields. The argument
to `select` is a comma separated list of fields.
+Individual field names can be prefixed with a stream name to disambiguate
between the same field name occurring in
+multiple streams as follows: `.select("spout3:key3, spout4:key3")`.
Nested tuple types are supported if the
--- End diff --
ya... i started with the dot syntax... then realized that it still leaves
ambiguity .. if there is a field and stream with same name. I wanted to avoid
putting code to guess whether the first part is a stream name or a key name. So
its just to avoid that corner case.
Standard SQL does not have this issue as it doesn't allow a mix of table
names and nested field names in a simple x.y.z format.
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