97 lines
3.6 KiB
Markdown
97 lines
3.6 KiB
Markdown
Map/Reduce Example
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------------------
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This is an example of how to use the mapReduce function to perform
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map/reduce style aggregation on your data.
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This document has been shamelessly ported from the similar
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[pymongo Map/Reduce Example](http://api.mongodb.org/python/1.4%2B/examples/map_reduce.html).
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Setup
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-----
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To start, we’ll insert some example data which we can perform
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map/reduce queries on:
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> $ ghci -package mongoDB
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> GHCi, version 6.12.1: http://www.haskell.org/ghc/ :? for help
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> ...
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> Prelude> :set prompt "> "
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> > import Database.MongoDB
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> > import Database.MongoDB.BSON
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> > import Data.ByteString.Lazy.UTF8
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> > c <- connect "localhost" []
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> > let col = (fromString "test.mr1")
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> > :{
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> insertMany c col [
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> (toBsonDoc [("x", BsonInt32 1),
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> ("tags", BsonArray [toBson "dog",
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> toBson "cat"])]),
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> (toBsonDoc [("x", BsonInt32 2),
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> ("tags", BsonArray [toBson "cat"])]),
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> (toBsonDoc [("x", BsonInt32 3),
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> ("tags", BsonArray [toBson "mouse",
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> toBson "cat",
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> toBson "doc"])]),
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> (toBsonDoc [("x", BsonInt32 4),
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> ("tags", BsonArray [])])
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> ]
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> :}
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Basic Map/Reduce
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----------------
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Now we'll define our map and reduce functions. In this case we're
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performing the same operation as in the MongoDB Map/Reduce
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documentation - counting the number of occurrences for each tag in the
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tags array, across the entire collection.
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Our map function just emits a single (key, 1) pair for each tag in the
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array:
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> > :{
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> let mapFn = "
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> function() {\n
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> this.tags.forEach(function(z) {\n
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> emit(z, 1);\n
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> });\n
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> }"
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> :}
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The reduce function sums over all of the emitted values for a given
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key:
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> > :{
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> let reduceFn = "
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> function (key, values) {\n
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> var total = 0;\n
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> for (var i = 0; i < values.length; i++) {\n
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> total += values[i];\n
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> }\n
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> return total;\n
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> }"
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> :}
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Note: We can’t just return values.length as the reduce function might
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be called iteratively on the results of other reduce steps.
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Finally, we call map_reduce() and iterate over the result collection:
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> > mapReduce c col (fromString mapFn) (fromString reduceFn) [] >>= allDocs
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> [[(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)]]
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Advanced Map/Reduce
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-------------------
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MongoDB returns additional information in the map/reduce results. To
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obtain them, use *runMapReduce*:
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> > res <- runMapReduce c col (fromString mapFn) (fromString reduceFn) []
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> > res
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> [(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)]
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You can then obtain the results using *mapReduceResults*:
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> > mapReduceResults c (fromString "test") res >>= allDocs
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> [[(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)]]
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