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    <p>Here is the current state of functionality for Map/Reduce in MongoDB</p> <p>1) Most of the performance limitations for Map/Reduce still remain in MongoDB version 2.2. The Map/Reduce engine still requires that every record get converted from BSON to JSON, the actual calculations are performed using the embedded JavaScript engine (which is slow), and there still is a single global JavaScript lock, which only allows a single JavaScript thread to run at a single time.</p> <p>There have been some incremental improvements to Map/Reduce for sharded clusters. Most notably, the final Reduce operation is now distributed across multiple shards, and the output is also sharded in parallel.</p> <p>I would not recommend Map/Reduce for real-time aggregation in MongoDB version 2.2</p> <p>2) Starting with MongoDB 2.2, there is now a new Aggregation Framework. This is a new implementation of aggregation operations, written in C++, and tightly integrated into the MongoDB framework.</p> <p>Most Map/Reduce jobs can be rewritten to use the Aggregation Framework. They usually run faster (20x speed improvement vs. Map/Reduce is common in version 2.2), they make full use of the existing query engine, and you can run multiple Aggregation commands in parallel.</p> <p>If you have real-time aggregation requirements, the first place to start is with the Aggregation Framework. For more information about the aggregation framework, take a look at these links:</p> <ul> <li><a href="http://www.10gen.com/presentations/mongonyc-2012/new-aggregation-framework" rel="noreferrer">http://www.10gen.com/presentations/mongonyc-2012/new-aggregation-framework</a></li> <li><a href="http://docs.mongodb.org/manual/reference/aggregation/" rel="noreferrer">http://docs.mongodb.org/manual/reference/aggregation/</a></li> </ul> <p>3) There have been significant improvements in Map/Reduce in MongoDB version 2.4. The SpiderMonkey JavaScript engine has been replaced by the V8 JavaScript engine, and there is no longer a global JavaScript lock, which means that multiple Map/Reduce threads can run concurrently.</p> <p>The Map/Reduce engine is still considerably slower than the aggregation framework, for two main reasons:</p> <ul> <li><p>The JavaScript engine is interpreted, while the Aggregation Framework runs compiled C++ code</p></li> <li><p>The JavaScript engine still requires that every document being examined get converted from BSON to JSON; if you're saving the output in a collection, the result set must then be converted from JSON back to BSON</p></li> </ul> <p>There are no significant changes in Map/Reduce between 2.4 and 2.6.</p> <p>I still do not recommend using the Map/Reduce for real-time aggregation in MongoDB version 2.4 or 2.6.</p> <p>4) If you really need Map/Reduce, you can also look at the Hadoop Adaptor. There's more information here:</p> <ul> <li><a href="http://www.10gen.com/presentations/webinar/mongodb-hadoop-taming-elephant-room" rel="noreferrer">http://www.10gen.com/presentations/webinar/mongodb-hadoop-taming-elephant-room</a></li> <li><a href="http://api.mongodb.org/hadoop/MongoDB%2BHadoop+Connector.html" rel="noreferrer">http://api.mongodb.org/hadoop/MongoDB%2BHadoop+Connector.html</a></li> <li><a href="http://www.mongodb.org/display/DOCS/Hadoop+Quick+Start" rel="noreferrer">http://www.mongodb.org/display/DOCS/Hadoop+Quick+Start</a></li> </ul>
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    1. POMap-Reduce performance in MongoDb 2.2, 2.4, and 2.6
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    1. COThe upcoming 2.4 version has another javascript engine (V8) that should improve performance. For details see here: http://docs.mongodb.org/manual/release-notes/2.4/
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