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- Map-Reduce Examples
Map-Reduce Examples¶
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In the mongo
shell, the db.collection.mapReduce()
method is a wrapper around the mapReduce
command. The
following examples use the db.collection.mapReduce()
method:
Consider the following map-reduce operations on a collection
orders
that contains documents of the following prototype:
{
_id: ObjectId("50a8240b927d5d8b5891743c"),
cust_id: "abc123",
ord_date: new Date("Oct 04, 2012"),
status: 'A',
price: 25,
items: [ { sku: "mmm", qty: 5, price: 2.5 },
{ sku: "nnn", qty: 5, price: 2.5 } ]
}
Return the Total Price Per Customer¶
Perform the map-reduce operation on the orders
collection to group
by the cust_id
, and calculate the sum of the price
for each
cust_id
:
Define the map function to process each input document:
- In the function,
this
refers to the document that the map-reduce operation is processing. - The function maps the
price
to thecust_id
for each document and emits thecust_id
andprice
pair.
var mapFunction1 = function() { emit(this.cust_id, this.price); };
- In the function,
Define the corresponding reduce function with two arguments
keyCustId
andvaluesPrices
:- The
valuesPrices
is an array whose elements are theprice
values emitted by the map function and grouped bykeyCustId
. - The function reduces the
valuesPrice
array to the sum of its elements.
var reduceFunction1 = function(keyCustId, valuesPrices) { return Array.sum(valuesPrices); };
- The
Perform the map-reduce on all documents in the
orders
collection using themapFunction1
map function and thereduceFunction1
reduce function.db.orders.mapReduce( mapFunction1, reduceFunction1, { out: "map_reduce_example" } )
This operation outputs the results to a collection named
map_reduce_example
. If themap_reduce_example
collection already exists, the operation will replace the contents with the results of this map-reduce operation:
Calculate Order and Total Quantity with Average Quantity Per Item¶
In this example, you will perform a map-reduce operation on the
orders
collection for all documents that have an ord_date
value greater than 01/01/2012
. The operation groups by the
item.sku
field, and calculates the number of
orders and the total quantity ordered for each sku
. The operation concludes by
calculating the average quantity per order for each sku
value:
Define the map function to process each input document:
- In the function,
this
refers to the document that the map-reduce operation is processing. - For each item, the function associates the
sku
with a new objectvalue
that contains thecount
of1
and the itemqty
for the order and emits thesku
andvalue
pair.
var mapFunction2 = function() { for (var idx = 0; idx < this.items.length; idx++) { var key = this.items[idx].sku; var value = { count: 1, qty: this.items[idx].qty }; emit(key, value); } };
- In the function,
Define the corresponding reduce function with two arguments
keySKU
andcountObjVals
:countObjVals
is an array whose elements are the objects mapped to the groupedkeySKU
values passed by map function to the reducer function.- The function reduces the
countObjVals
array to a single objectreducedValue
that contains thecount
and theqty
fields. - In
reducedVal
, thecount
field contains the sum of thecount
fields from the individual array elements, and theqty
field contains the sum of theqty
fields from the individual array elements.
var reduceFunction2 = function(keySKU, countObjVals) { reducedVal = { count: 0, qty: 0 }; for (var idx = 0; idx < countObjVals.length; idx++) { reducedVal.count += countObjVals[idx].count; reducedVal.qty += countObjVals[idx].qty; } return reducedVal; };
Define a finalize function with two arguments
key
andreducedVal
. The function modifies thereducedVal
object to add a computed field namedavg
and returns the modified object:var finalizeFunction2 = function (key, reducedVal) { reducedVal.avg = reducedVal.qty/reducedVal.count; return reducedVal; };
Perform the map-reduce operation on the
orders
collection using themapFunction2
,reduceFunction2
, andfinalizeFunction2
functions.db.orders.mapReduce( mapFunction2, reduceFunction2, { out: { merge: "map_reduce_example" }, query: { ord_date: { $gt: new Date('01/01/2012') } }, finalize: finalizeFunction2 } )
This operation uses the
query
field to select only those documents withord_date
greater thannew Date(01/01/2012)
. Then it output the results to a collectionmap_reduce_example
. If themap_reduce_example
collection already exists, the operation will merge the existing contents with the results of this map-reduce operation.