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<p>Given a set of sorted datasets keyed with the same class and yielding equal
partitions, it is possible to effect a join of those datasets prior to the map.
This could save costs in re-partitioning, sorting, shuffling, and writing out
data required in the general case.</p>

<h3><a name="Interface"></a>Interface</h3>

<p>The attached code offers the following interface to users of these
classes.</p>

<table>
<tr><th>property</th><th>required</th><th>value</th></tr>
<tr><td>mapreduce.join.expr</td><td>yes</td>
    <td>Join expression to effect over input data</td></tr>
<tr><td>mapreduce.join.keycomparator</td><td>no</td>
    <td><tt>WritableComparator</tt> class to use for comparing keys</td></tr>
<tr><td>mapreduce.join.define.&lt;ident&gt;</td><td>no</td>
    <td>Class mapped to identifier in join expression</td></tr>
</table>

<p>The join expression understands the following grammar:</p>

<pre>func ::= &lt;ident&gt;([&lt;func&gt;,]*&lt;func&gt;)
func ::= tbl(&lt;class&gt;,"&lt;path&gt;");

</pre>

<p>Operations included in this patch are partitioned into one of two types:
join operations emitting tuples and "multi-filter" operations emitting a
single value from (but not necessarily included in) a set of input values.
For a given key, each operation will consider the cross product of all
values for all sources at that node.</p>

<p>Identifiers supported by default:</p>

<table>
<tr><th>identifier</th><th>type</th><th>description</th></tr>
<tr><td>inner</td><td>Join</td><td>Full inner join</td></tr>
<tr><td>outer</td><td>Join</td><td>Full outer join</td></tr>
<tr><td>override</td><td>MultiFilter</td>
    <td>For a given key, prefer values from the rightmost source</td></tr>
</table>

<p>A user of this class must set the <tt>InputFormat</tt> for the job to
<tt>CompositeInputFormat</tt> and define a join expression accepted by the
preceding grammar. For example, both of the following are acceptable:</p>

<pre>inner(tbl(org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat.class,
          "hdfs://host:8020/foo/bar"),
      tbl(org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat.class,
          "hdfs://host:8020/foo/baz"))

outer(override(tbl(org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat.class,
                   "hdfs://host:8020/foo/bar"),
               tbl(org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat.class,
                   "hdfs://host:8020/foo/baz")),
      tbl(org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat.class,
          "hdfs://host:8020/foo/rab"))
</pre>

<p><tt>CompositeInputFormat</tt> includes a handful of convenience methods to
aid construction of these verbose statements.</p>

<p>As in the second example, joins may be nested. Users may provide a
comparator class in the <tt>mapreduce.join.keycomparator</tt> property to specify
the ordering of their keys, or accept the default comparator as returned by
<tt>WritableComparator.get(keyclass)</tt>.</p>

<p>Users can specify their own join operations, typically by overriding
<tt>JoinRecordReader</tt> or <tt>MultiFilterRecordReader</tt> and mapping that
class to an identifier in the join expression using the
<tt>mapreduce.join.define.<em>ident</em></tt> property, where <em>ident</em> is
the identifier appearing in the join expression. Users may elect to emit- or
modify- values passing through their join operation. Consulting the existing
operations for guidance is recommended. Adding arguments is considerably more
complex (and only partially supported), as one must also add a <tt>Node</tt>
type to the parse tree. One is probably better off extending
<tt>RecordReader</tt> in most cases.</p>

<a href="http://issues.apache.org/jira/browse/HADOOP-2085">JIRA</a>

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