- Aggregation >
- Map-Reduce
Map-Reduce¶
Aggregation Pipeline as Alternative
Aggregation pipeline
provides better performance and a more coherent interface than
map-reduce, and various map-reduce operations can be rewritten
using aggregation pipeline operators, such as $group,
$merge, $accumulator, etc.
For examples of aggregation alternatives to map-reduce operations, see Map-Reduce Examples. See also Map-Reduce to Aggregation Pipeline.
Map-reduce is a data processing paradigm for condensing large volumes
of data into useful aggregated results. To perform map-reduce
operations, MongoDB provides the mapReduce database
command.
Consider the following map-reduce operation:
In this map-reduce operation, MongoDB applies the map phase to each input document (i.e. the documents in the collection that match the query condition). The map function emits key-value pairs. For those keys that have multiple values, MongoDB applies the reduce phase, which collects and condenses the aggregated data. MongoDB then stores the results in a collection. Optionally, the output of the reduce function may pass through a finalize function to further condense or process the results of the aggregation.
All map-reduce functions in MongoDB are JavaScript and run
within the mongod process. Map-reduce operations take the
documents of a single collection as the input and can perform
any arbitrary sorting and limiting before beginning the map stage.
mapReduce can return the results of a map-reduce operation
as a document, or may write the results to collections.
Map-Reduce JavaScript Functions¶
In MongoDB, map-reduce operations use custom JavaScript functions to map, or associate, values to a key. If a key has multiple values mapped to it, the operation reduces the values for the key to a single object.
The use of custom JavaScript functions provide flexibility to map-reduce operations. For instance, when processing a document, the map function can create more than one key and value mapping or no mapping. Map-reduce operations can also use a custom JavaScript function to make final modifications to the results at the end of the map and reduce operation, such as perform additional calculations.
Note
Starting in MongoDB 4.4, mapReduce no longer supports
the deprecated BSON type JavaScript code with scope
(BSON type 15) for its functions. The
map, reduce, and finalize functions must be either BSON
type String (BSON type 2) or
BSON type JavaScript (BSON type 13).
To pass constant values which will be accessible in the map,
reduce, and finalize functions, use the scope parameter.
The use of JavaScript code with scope for the mapReduce
functions has been deprecated since version 4.2.1.
Map-Reduce Results¶
In MongoDB, the map-reduce operation can write results to a collection
or return the results inline. If you write map-reduce output to a
collection, you can perform subsequent map-reduce operations on the
same input collection that merge replace, merge, or reduce new results
with previous results. See mapReduce and
Perform Incremental Map-Reduce for details and
examples.
When returning the results of a map-reduce operation inline, the
result documents must be within the BSON Document Size limit,
which is currently 16 megabytes. For additional information on limits
and restrictions on map-reduce operations, see the
mapReduce reference page.
Sharded Collections¶
MongoDB supports map-reduce operations on sharded collections.
However, starting in version 4.2, MongoDB deprecates the map-reduce
option to create a new sharded collection and the use of the
sharded option for map-reduce. To output to a sharded collection,
create the sharded collection first. MongoDB 4.2 also deprecates the
replacement of an existing sharded collection.