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mapReduce

mapReduce

The mapReduce command allows you to run map-reduce aggregation operations over a collection. The mapReduce command has the following prototype form:

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db.runCommand(
               {
                 mapReduce: <collection>,
                 map: <function>,
                 reduce: <function>,
                 finalize: <function>,
                 out: <output>,
                 query: <document>,
                 sort: <document>,
                 limit: <number>,
                 scope: <document>,
                 jsMode: <boolean>,
                 verbose: <boolean>,
                 bypassDocumentValidation: <boolean>,
                 collation: <document>
               }
             )

Pass the name of the collection to the mapReduce command (i.e. <collection>) to use as the source documents to perform the map-reduce operation.

Note

Views do not support map-reduce operations.

The command also accepts the following parameters:

Field	Type	Description
mapReduce	collection	The name of the collection on which you want to perform map-reduce. This collection will be filtered using query before being processed by the map function.
map	function	A JavaScript function that associates or “maps” a value with a key and emits the key and value pair. See Requirements for the map Function for more information.
reduce	function	A JavaScript function that “reduces” to a single object all the values associated with a particular key. See Requirements for the reduce Function for more information.
out	string or document	Specifies where to output the result of the map-reduce operation. You can either output to a collection or return the result inline. On a primary member of a replica set you can output either to a collection or inline, but on a secondary, only inline output is possible. See out Options for more information.
query	document	Optional. Specifies the selection criteria using query operators for determining the documents input to the map function.
sort	document	Optional. Sorts the input documents. This option is useful for optimization. For example, specify the sort key to be the same as the emit key so that there are fewer reduce operations. The sort key must be in an existing index for this collection.
limit	number	Optional. Specifies a maximum number of documents for the input into the map function.
finalize	function	Optional. Follows the reduce method and modifies the output. See Requirements for the finalize Function for more information.
scope	document	Optional. Specifies global variables that are accessible in the map, reduce and finalize functions.
jsMode	boolean	Optional. Specifies whether to convert intermediate data into BSON format between the execution of the map and reduce functions. Defaults to false. If false: Internally, MongoDB converts the JavaScript objects emitted by the map function to BSON objects. These BSON objects are then converted back to JavaScript objects when calling the reduce function. The map-reduce operation places the intermediate BSON objects in temporary, on-disk storage. This allows the map-reduce operation to execute over arbitrarily large data sets. If true: Internally, the JavaScript objects emitted during map function remain as JavaScript objects. There is no need to convert the objects for the reduce function, which can result in faster execution. You can only use jsMode for result sets with fewer than 500,000 distinct key arguments to the mapper’s emit() function.
verbose	Boolean	Optional. Specifies whether to include the timing information in the result information. Set verbose to true to include the timing information. Defaults to false.
bypassDocumentValidation	boolean	Optional. Enables mapReduce to bypass document validation during the operation. This lets you insert documents that do not meet the validation requirements. New in version 3.2.
collation	document	Optional. Specifies the collation to use for the operation. Collation allows users to specify language-specific rules for string comparison, such as rules for lettercase and accent marks. The collation option has the following syntax: copy collation: { locale: <string>, caseLevel: <boolean>, caseFirst: <string>, strength: <int>, numericOrdering: <boolean>, alternate: <string>, maxVariable: <string>, backwards: <boolean> } When specifying collation, the locale field is mandatory; all other collation fields are optional. For descriptions of the fields, see Collation Document. If the collation is unspecified but the collection has a default collation (see db.createCollection()), the operation uses the collation specified for the collection. If no collation is specified for the collection or for the operations, MongoDB uses the simple binary comparison used in prior versions for string comparisons. You cannot specify multiple collations for an operation. For example, you cannot specify different collations per field, or if performing a find with a sort, you cannot use one collation for the find and another for the sort. New in version 3.4.

The following is a prototype usage of the mapReduce command:

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var mapFunction = function() { ... };
var reduceFunction = function(key, values) { ... };

db.runCommand(
               {
                 mapReduce: <input-collection>,
                 map: mapFunction,
                 reduce: reduceFunction,
                 out: { merge: <output-collection> },
                 query: <query>
               }
             )

JavaScript in MongoDB

Although mapReduce uses JavaScript, most interactions with MongoDB do not use JavaScript but use an idiomatic driver in the language of the interacting application.

Requirements for the map Function

The map function is responsible for transforming each input document into zero or more documents. It can access the variables defined in the scope parameter, and has the following prototype:

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function() {
   ...
   emit(key, value);
}

The map function has the following requirements:

• In the map function, reference the current document as this within the function.
• The map function should not access the database for any reason.
• The map function should be pure, or have no impact outside of the function (i.e. side effects.)
• A single emit can only hold half of MongoDB’s maximum BSON document size.
• The map function may optionally call emit(key,value) any number of times to create an output document associating key with value.

The following map function will call emit(key,value) either 0 or 1 times depending on the value of the input document’s status field:

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function() {
    if (this.status == 'A')
        emit(this.cust_id, 1);
}

The following map function may call emit(key,value) multiple times depending on the number of elements in the input document’s items field:

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function() {
    this.items.forEach(function(item){ emit(item.sku, 1); });
}

Requirements for the reduce Function

The reduce function has the following prototype:

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function(key, values) {
   ...
   return result;
}

The reduce function exhibits the following behaviors:

• The reduce function should not access the database, even to perform read operations.
• The reduce function should not affect the outside system.
• MongoDB will not call the reduce function for a key that has only a single value. The values argument is an array whose elements are the value objects that are “mapped” to the key.
• MongoDB can invoke the reduce function more than once for the same key. In this case, the previous output from the reduce function for that key will become one of the input values to the next reduce function invocation for that key.
• The reduce function can access the variables defined in the scope parameter.
• The inputs to reduce must not be larger than half of MongoDB’s maximum BSON document size. This requirement may be violated when large documents are returned and then joined together in subsequent reduce steps.

Because it is possible to invoke the reduce function more than once for the same key, the following properties need to be true:

• the type of the return object must be identical to the type of the value emitted by the map function.

• the reduce function must be associative. The following statement must be true:

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  reduce(key, [ C, reduce(key, [ A, B ]) ] ) == reduce( key, [ C, A, B ] )
  

• the reduce function must be idempotent. Ensure that the following statement is true:

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  reduce( key, [ reduce(key, valuesArray) ] ) == reduce( key, valuesArray )
  

• the reduce function should be commutative: that is, the order of the elements in the valuesArray should not affect the output of the reduce function, so that the following statement is true:

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  reduce( key, [ A, B ] ) == reduce( key, [ B, A ] )
  

Requirements for the finalize Function

The finalize function has the following prototype:

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function(key, reducedValue) {
   ...
   return modifiedObject;
}

The finalize function receives as its arguments a key value and the reducedValue from the reduce function. Be aware that:

• The finalize function should not access the database for any reason.
• The finalize function should be pure, or have no impact outside of the function (i.e. side effects.)
• The finalize function can access the variables defined in the scope parameter.

out Options

You can specify the following options for the out parameter:

Output to a Collection

This option outputs to a new collection, and is not available on secondary members of replica sets.

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out: <collectionName>

Output to a Collection with an Action

This option is only available when passing a collection that already exists to out. It is not available on secondary members of replica sets.

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out: { <action>: <collectionName>
        [, db: <dbName>]
        [, sharded: <boolean> ]
        [, nonAtomic: <boolean> ] }

When you output to a collection with an action, the out has the following parameters:

• <action>: Specify one of the following actions:

  • replace

    Replace the contents of the <collectionName> if the collection with the <collectionName> exists.

  • merge

    Merge the new result with the existing result if the output collection already exists. If an existing document has the same key as the new result, overwrite that existing document.

  • reduce

    Merge the new result with the existing result if the output collection already exists. If an existing document has the same key as the new result, apply the reduce function to both the new and the existing documents and overwrite the existing document with the result.

• db:

  Optional. The name of the database that you want the map-reduce operation to write its output. By default this will be the same database as the input collection.

• sharded:

  Optional. If true and you have enabled sharding on output database, the map-reduce operation will shard the output collection using the _id field as the shard key.

• nonAtomic:

  Optional. Specify output operation as non-atomic. This applies only to the merge and reduce output modes, which may take minutes to execute.

  By default nonAtomic is false, and the map-reduce operation locks the database during post-processing.

  If nonAtomic is true, the post-processing step prevents MongoDB from locking the database: during this time, other clients will be able to read intermediate states of the output collection.

Output Inline

Perform the map-reduce operation in memory and return the result. This option is the only available option for out on secondary members of replica sets.

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out: { inline: 1 }

The result must fit within the maximum size of a BSON document.

Required Access

If your MongoDB deployment enforces authentication, the user executing the mapReduce command must possess the following privilege actions:

Map-reduce with {out : inline} output option: - find

Map-reduce with the replace action when outputting to a collection: - find, - insert, - replace

Map-reduce with the merge or reduce actions when outputting to a collection: - find, - insert, - update

The readWrite built-in role provides the necessary permissions to perform map-reduce aggregation.

Map-Reduce Examples

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:

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{
     _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:

1. 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 the cust_id for each document and emits the cust_id and price pair.
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   var mapFunction1 = function() {
                          emit(this.cust_id, this.price);
                      };
   

2. Define the corresponding reduce function with two arguments keyCustId and valuesPrices:

   • The valuesPrices is an array whose elements are the price values emitted by the map function and grouped by keyCustId.
   • The function reduces the valuesPrice array to the sum of its elements.
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   var reduceFunction1 = function(keyCustId, valuesPrices) {
                             return Array.sum(valuesPrices);
                         };
   

3. Perform the map-reduce on all documents in the orders collection using the mapFunction1 map function and the reduceFunction1 reduce function.

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   db.orders.mapReduce(
                        mapFunction1,
                        reduceFunction1,
                        { out: "map_reduce_example" }
                      )
   

   This operation outputs the results to a collection named map_reduce_example. If the map_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:

1. 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 object value that contains the count of 1 and the item qty for the order and emits the sku and value pair.
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   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);
                          }
                       };
   

2. Define the corresponding reduce function with two arguments keySKU and countObjVals:

   • countObjVals is an array whose elements are the objects mapped to the grouped keySKU values passed by map function to the reducer function.
   • The function reduces the countObjVals array to a single object reducedValue that contains the count and the qty fields.
   • In reducedVal, the count field contains the sum of the count fields from the individual array elements, and the qty field contains the sum of the qty fields from the individual array elements.
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   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;
                     };
   

3. Define a finalize function with two arguments key and reducedVal. The function modifies the reducedVal object to add a computed field named avg and returns the modified object:

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   var finalizeFunction2 = function (key, reducedVal) {
   
                          reducedVal.avg = reducedVal.qty/reducedVal.count;
   
                          return reducedVal;
   
                       };
   

4. Perform the map-reduce operation on the orders collection using the mapFunction2, reduceFunction2, and finalizeFunction2 functions.

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   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 with ord_date greater than new Date(01/01/2012). Then it output the results to a collection map_reduce_example. If the map_reduce_example collection already exists, the operation will merge the existing contents with the results of this map-reduce operation.

For more information and examples, see the Map-Reduce page and Perform Incremental Map-Reduce.

Output

The mapReduce command adds support for the bypassDocumentValidation option, which lets you bypass document validation when inserting or updating documents in a collection with validation rules.

If you set the out parameter to write the results to a collection, the mapReduce command returns a document in the following form:

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{
    "result" : <string or document>,
    "timeMillis" : <int>,
    "counts" : {
        "input" : <int>,
        "emit" : <int>,
        "reduce" : <int>,
        "output" : <int>
    },
    "ok" : <int>,
}

If you set the out parameter to output the results inline, the mapReduce command returns a document in the following form:

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{
    "results" : [
       {
          "_id" : <key>,
          "value" :<reduced or finalizedValue for key>
       },
       ...
    ],
    "timeMillis" : <int>,
    "counts" : {
       "input" : <int>,
       "emit" : <int>,
       "reduce" : <int>,
       "output" : <int>
    },
    "ok" : <int>
}

mapReduce.result

For output sent to a collection, this value is either:

• a string for the collection name if out did not specify the database name, or
• a document with both db and collection fields if out specified both a database and collection name.

mapReduce.results

For output written inline, an array of resulting documents. Each resulting document contains two fields:

• _id field contains the key value,
• value field contains the reduced or finalized value for the associated key.

mapReduce.timeMillis

The command execution time in milliseconds.

mapReduce.counts

Various count statistics from the mapReduce command.

mapReduce.counts.input

The number of input documents, which is the number of times the mapReduce command called the map function.

mapReduce.counts.emit

The number of times the mapReduce command called the emit function.

mapReduce.counts.reduce

The number of times the mapReduce command called the reduce function.

mapReduce.counts.output

The number of output values produced.

mapReduce.ok

A value of 1 indicates the mapReduce command ran successfully. A value of 0 indicates an error.

Additional Information

• Troubleshoot the Map Function
• Troubleshoot the Reduce Function
• db.collection.mapReduce()
• Aggregation

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