mongodb/mapreduce

542179528

　　


MapReduce

　　

Map/reduce in MongoDB is useful for batch processing of data and aggregation operations. It is similar in spirit to using something like Hadoop with all input coming from a collection and output going to a collection.  Often, in a situation where you would have used GROUP BY in SQL, map/reduce is the right tool in MongoDB. [table]
	Indexing and standard queries in MongoDB are separate from map/reduce.  If you have used CouchDB in the past, note this is a big difference: MongoDB is more like MySQL for basic querying and indexing.  See the queries and indexing documentation for those operations.

• Overview
  
  
  
  • 
    
    
    
    • Output options
      
    • Result object
      
    
    
    
  • Map Function
    
  • Reduce Function
    
  • Finalize Function
    
  
  
  
• Sharded Environments
  
• Examples
  
  
  
  • Shell Example 1
    
  • Shell Example 2
    
  • More Examples
    
  • Note on Permanent Collections
    
  
  
  
• Parallelism
  
• Presentations
  
• See Also
  

　　


Overview
　　map/reduce is invoked via a database command.
The database creates a temporary collection to hold output of the
operation.  The collection is cleaned up when the client connection
closes, or when explicitly dropped. Alternatively, one can specify a
permanent output collection name.  map and reduce functions are written in JavaScript and execute on the server.
　　Command syntax:





db.runCommand(
{ mapreduce : ,
map : ,
reduce :
[, query : ]
[, sort : ]
[, limit : ]
[, out : ]
[, keeptemp: ]
[, finalize : ]
[, scope : ]
[, verbose : true]
}
);

　　* keeptemp - if true, the generated collection is not treated as temporary. Defaults to false.  When out is specified, the collection is automatically made permanent. (MongoDB