mongodb/map-reduce-example.md

Map/Reduce Example

This is an example of how to use the mapReduce function to perform map/reduce style aggregation on your data.

This document has been shamelessly ported from the similar pymongo Map/Reduce Example.

Setup

To start, we’ll insert some example data which we can perform map/reduce queries on:

$ ghci -package mongoDB GHCi, version 6.12.1: http://www.haskell.org/ghc/ :? for help ... Prelude> :set prompt "> "

import Database.MongoDB import Database.MongoDB.BSON import Data.ByteString.Lazy.UTF8 c <- connect "localhost" [] let col = (fromString "test.mr1") :{ insertMany c col [ (toBsonDoc [("x", BsonInt32 1), ("tags", BsonArray [toBson "dog", toBson "cat"])]), (toBsonDoc [("x", BsonInt32 2), ("tags", BsonArray [toBson "cat"])]), (toBsonDoc [("x", BsonInt32 3), ("tags", BsonArray [toBson "mouse", toBson "cat", toBson "doc"])]), (toBsonDoc [("x", BsonInt32 4), ("tags", BsonArray [])]) ] :}

Basic Map/Reduce

Now we'll define our map and reduce functions. In this case we're performing the same operation as in the MongoDB Map/Reduce documentation - counting the number of occurrences for each tag in the tags array, across the entire collection.

Our map function just emits a single (key, 1) pair for each tag in the array:

:{ let mapFn = " function() {\n this.tags.forEach(function(z) {\n emit(z, 1);\n });\n }" :}

The reduce function sums over all of the emitted values for a given key:

:{ let reduceFn = " function (key, values) {\n var total = 0;\n for (var i = 0; i < values.length; i++) {\n total += values[i];\n }\n return total;\n }" :}

Note: We can’t just return values.length as the reduce function might be called iteratively on the results of other reduce steps.

Finally, we call map_reduce() and iterate over the result collection:

mapReduce c col (fromString mapFn) (fromString reduceFn) [] >>= allDocs (Chunk "_id" Empty,BsonString (Chunk "cat" Empty)),(Chunk "value" Empty,BsonDouble 6.0)],[(Chunk "_id" Empty,BsonString (Chunk "doc" Empty)),(Chunk "value" Empty,BsonDouble 1.0)],[(Chunk "_id" Empty,BsonString (Chunk "dog" Empty)),(Chunk "value" Empty,BsonDouble 3.0)],[(Chunk "_id" Empty,BsonString (Chunk "mouse" Empty)),(Chunk "value" Empty,BsonDouble 2.0)

Advanced Map/Reduce

MongoDB returns additional information in the map/reduce results. To obtain them, use runMapReduce:

res <- runMapReduce c col (fromString mapFn) (fromString reduceFn) [] res [(Chunk "result" Empty,BsonString (Chunk "tmp.mr.mapreduce_1268105512_18" Empty)),(Chunk "timeMillis" Empty,BsonInt32 90),(Chunk "counts" Empty,BsonDoc [(Chunk "input" Empty,BsonInt64 8),(Chunk "emit" Empty,BsonInt64 12),(Chunk "output" Empty,BsonInt64 4)]),(Chunk "ok" Empty,BsonDouble 1.0)]

You can then obtain the results using mapReduceResults:

mapReduceResults c (fromString "test") res >>= allDocs (Chunk "_id" Empty,BsonString (Chunk "cat" Empty)),(Chunk "value" Empty,BsonDouble 6.0)],[(Chunk "_id" Empty,BsonString (Chunk "doc" Empty)),(Chunk "value" Empty,BsonDouble 1.0)],[(Chunk "_id" Empty,BsonString (Chunk "dog" Empty)),(Chunk "value" Empty,BsonDouble 3.0)],[(Chunk "_id" Empty,BsonString (Chunk "mouse" Empty)),(Chunk "value" Empty,BsonDouble 2.0)