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)]]