OPTIONS

group

Definition

group

Groups documents in a collection by the specified key and performs simple aggregation functions, such as computing counts and sums. The command is analogous to a SELECT <...> GROUP BY statement in SQL. The command returns a document with the grouped records as well as the command meta-data.

The group command takes the following prototype form:

{
  group:
   {
     ns: <namespace>,
     key: <key>,
     $reduce: <reduce function>,
     $keyf: <key function>,
     cond: <query>,
     finalize: <finalize function>
   }
}

The command accepts a document with the following fields:

Field Type Description
ns string The collection from which to perform the group by operation.
key document The field or fields to group. Returns a “key object” for use as the grouping key.
$reduce function An aggregation function that operates on the documents during the grouping operation. These functions may return a sum or a count. The function takes two arguments: the current document and an aggregation result document for that group.
initial document Initializes the aggregation result document.
$keyf function Optional. Alternative to the key field. Specifies a function that creates a “key object” for use as the grouping key. Use $keyf instead of key to group by calculated fields rather than existing document fields.
cond document Optional. The selection criteria to determine which documents in the collection to process. If you omit the cond field, group processes all the documents in the collection for the group operation.
finalize function Optional. A function that runs each item in the result set before group returns the final value. This function can either modify the result document or replace the result document as a whole. Unlike the $keyf and $reduce fields that also specify a function, this field name is finalize, not $finalize.

For the shell, MongoDB provides a wrapper method db.collection.group(). However, the db.collection.group() method takes the keyf field and the reduce field whereas the group command takes the $keyf field and the $reduce field.

Behavior

Limits and Restrictions

The group command does not work with sharded clusters. Use the aggregation framework or map-reduce in sharded environments.

The result set must fit within the maximum BSON document size.

Additionally, in version 2.2, the returned array can contain at most 20,000 elements; i.e. at most 20,000 unique groupings. For group by operations that results in more than 20,000 unique groupings, use mapReduce. Previous versions had a limit of 10,000 elements.

Prior to 2.4, the group command took the mongod instance’s JavaScript lock which blocked all other JavaScript execution.

mongo Shell JavaScript Functions/Properties

Changed in version 2.4.

In MongoDB 2.4, map-reduce operations, the group command, and $where operator expressions cannot access certain global functions or properties, such as db, that are available in the mongo shell.

When upgrading to MongoDB 2.4, you will need to refactor your code if your map-reduce operations, group commands, or $where operator expressions include any global shell functions or properties that are no longer available, such as db.

The following JavaScript functions and properties are available to map-reduce operations, the group command, and $where operator expressions in MongoDB 2.4:

Available Properties Available Functions  
args
MaxKey
MinKey
assert()
BinData()
DBPointer()
DBRef()
doassert()
emit()
gc()
HexData()
hex_md5()
isNumber()
isObject()
ISODate()
isString()
Map()
MD5()
NumberInt()
NumberLong()
ObjectId()
print()
printjson()
printjsononeline()
sleep()
Timestamp()
tojson()
tojsononeline()
tojsonObject()
UUID()
version()

JavaScript in MongoDB

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

Examples

The following are examples of the db.collection.group() method. The examples assume an orders collection with documents of the following prototype:

{
  _id: ObjectId("5085a95c8fada716c89d0021"),
  ord_dt: ISODate("2012-07-01T04:00:00Z"),
  ship_dt: ISODate("2012-07-02T04:00:00Z"),
  item:
    {
      sku: "abc123",
      price: 1.99,
      uom: "pcs",
      qty: 25
    }
}

Group by Two Fields

The following example groups by the ord_dt and item.sku fields those documents that have ord_dt greater than 01/01/2012:

db.runCommand(
   {
     group:
       {
         ns: 'orders',
         key: { ord_dt: 1, 'item.sku': 1 },
         cond: { ord_dt: { $gt: new Date( '01/01/2012' ) } },
         $reduce: function ( curr, result ) { },
         initial: { }
       }
   }
)

The result is a document that contain the retval field which contains the group by records, the count field which contains the total number of documents grouped, the keys field which contains the number of unique groupings (i.e. number of elements in the retval), and the ok field which contains the command status:

{ "retval" :
      [ { "ord_dt" : ISODate("2012-07-01T04:00:00Z"), "item.sku" : "abc123"},
        { "ord_dt" : ISODate("2012-07-01T04:00:00Z"), "item.sku" : "abc456"},
        { "ord_dt" : ISODate("2012-07-01T04:00:00Z"), "item.sku" : "bcd123"},
        { "ord_dt" : ISODate("2012-07-01T04:00:00Z"), "item.sku" : "efg456"},
        { "ord_dt" : ISODate("2012-06-01T04:00:00Z"), "item.sku" : "abc123"},
        { "ord_dt" : ISODate("2012-06-01T04:00:00Z"), "item.sku" : "efg456"},
        { "ord_dt" : ISODate("2012-06-01T04:00:00Z"), "item.sku" : "ijk123"},
        { "ord_dt" : ISODate("2012-05-01T04:00:00Z"), "item.sku" : "abc123"},
        { "ord_dt" : ISODate("2012-05-01T04:00:00Z"), "item.sku" : "abc456"},
        { "ord_dt" : ISODate("2012-06-08T04:00:00Z"), "item.sku" : "abc123"},
        { "ord_dt" : ISODate("2012-06-08T04:00:00Z"), "item.sku" : "abc456"}
      ],
  "count" : 13,
  "keys" : 11,
  "ok" : 1 }

The method call is analogous to the SQL statement:

SELECT ord_dt, item_sku
FROM orders
WHERE ord_dt > '01/01/2012'
GROUP BY ord_dt, item_sku

Calculate the Sum

The following example groups by the ord_dt and item.sku fields those documents that have ord_dt greater than 01/01/2012 and calculates the sum of the qty field for each grouping:

db.runCommand(
   { group:
       {
         ns: 'orders',
         key: { ord_dt: 1, 'item.sku': 1 },
         cond: { ord_dt: { $gt: new Date( '01/01/2012' ) } },
         $reduce: function ( curr, result ) {
                     result.total += curr.item.qty;
                  },
         initial: { total : 0 }
       }
    }
)

The retval field of the returned document is an array of documents that contain the group by fields and the calculated aggregation field:

{ "retval" :
      [ { "ord_dt" : ISODate("2012-07-01T04:00:00Z"), "item.sku" : "abc123", "total" : 25 },
        { "ord_dt" : ISODate("2012-07-01T04:00:00Z"), "item.sku" : "abc456", "total" : 25 },
        { "ord_dt" : ISODate("2012-07-01T04:00:00Z"), "item.sku" : "bcd123", "total" : 10 },
        { "ord_dt" : ISODate("2012-07-01T04:00:00Z"), "item.sku" : "efg456", "total" : 10 },
        { "ord_dt" : ISODate("2012-06-01T04:00:00Z"), "item.sku" : "abc123", "total" : 25 },
        { "ord_dt" : ISODate("2012-06-01T04:00:00Z"), "item.sku" : "efg456", "total" : 15 },
        { "ord_dt" : ISODate("2012-06-01T04:00:00Z"), "item.sku" : "ijk123", "total" : 20 },
        { "ord_dt" : ISODate("2012-05-01T04:00:00Z"), "item.sku" : "abc123", "total" : 45 },
        { "ord_dt" : ISODate("2012-05-01T04:00:00Z"), "item.sku" : "abc456", "total" : 25 },
        { "ord_dt" : ISODate("2012-06-08T04:00:00Z"), "item.sku" : "abc123", "total" : 25 },
        { "ord_dt" : ISODate("2012-06-08T04:00:00Z"), "item.sku" : "abc456", "total" : 25 }
      ],
  "count" : 13,
  "keys" : 11,
  "ok" : 1 }

The method call is analogous to the SQL statement:

SELECT ord_dt, item_sku, SUM(item_qty) as total
FROM orders
WHERE ord_dt > '01/01/2012'
GROUP BY ord_dt, item_sku

Calculate Sum, Count, and Average

The following example groups by the calculated day_of_week field, those documents that have ord_dt greater than 01/01/2012 and calculates the sum, count, and average of the qty field for each grouping:

db.runCommand(
   {
     group:
       {
         ns: 'orders',
         $keyf: function(doc) {
                    return { day_of_week: doc.ord_dt.getDay() };
                },
         cond: { ord_dt: { $gt: new Date( '01/01/2012' ) } },
         $reduce: function( curr, result ) {
                      result.total += curr.item.qty;
                      result.count++;
                  },
         initial: { total : 0, count: 0 },
         finalize: function(result) {
                      var weekdays = [
                           "Sunday", "Monday", "Tuesday",
                           "Wednesday", "Thursday",
                           "Friday", "Saturday"
                          ];
                      result.day_of_week = weekdays[result.day_of_week];
                      result.avg = Math.round(result.total / result.count);
                   }
       }
   }
)

The retval field of the returned document is an array of documents that contain the group by fields and the calculated aggregation field:

{
  "retval" :
      [
        { "day_of_week" : "Sunday", "total" : 70, "count" : 4, "avg" : 18 },
        { "day_of_week" : "Friday", "total" : 110, "count" : 6, "avg" : 18 },
        { "day_of_week" : "Tuesday", "total" : 70, "count" : 3, "avg" : 23 }
      ],
  "count" : 13,
  "keys" : 3,
  "ok" : 1
}
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