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Map-Reduce and Sharded Collections

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  • Sharded Collection as Input
  • Sharded Collection as Output

Note

Aggregation Pipeline as an Alternative to Map-Reduce

Starting in MongoDB 5.0, map-reduce is deprecated:

For examples of aggregation pipeline alternatives to map-reduce, see:

Map-reduce supports operations on sharded collections, both as an input and as an output. This section describes the behaviors of mapReduce specific to sharded collections.

However, starting in version 4.2, MongoDB deprecates the map-reduce option to create a new sharded collection as well as 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.

When using sharded collection as the input for a map-reduce operation, mongos will automatically dispatch the map-reduce job to each shard in parallel. There is no special option required. mongos will wait for jobs on all shards to finish.

If the out field for mapReduce has the sharded value, MongoDB shards the output collection using the _id field as the shard key.

Note

Starting in version 4.2, MongoDB deprecates the use of the sharded option for mapReduce/db.collection.mapReduce().

To output to a sharded collection:

  • If the output collection does not exist, create the sharded collection first.

    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. As such, to output to a sharded collection, create the sharded collection first.

    If you did not create the sharded collection first, MongoDB creates and shards the collection on the _id field. However, it is recommended that you create the sharded collection first.

  • Starting in version 4.2, MongoDB deprecates the replacement of an existing sharded collection.

  • Starting in version 4.0, if the output collection already exists but is not sharded, map-reduce fails.

  • For a new or an empty sharded collection, MongoDB uses the results of the first stage of the map-reduce operation to create the initial chunks distributed among the shards.

  • mongos dispatches, in parallel, a map-reduce post-processing job to every shard that owns a chunk. During the post-processing, each shard will pull the results for its own chunks from the other shards, run the final reduce/finalize, and write locally to the output collection.

Note

  • During later map-reduce jobs, MongoDB splits chunks as needed.

  • Balancing of chunks for the output collection is automatically prevented during post-processing to avoid concurrency issues.

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