MongoDB Aggregation Stages Operator - $match
Description
The MongoDB $match operator filters the documents to pass only those documents that match the specified condition(s) to the next pipeline stage.
Syntax:
{ $match: { <query> } }
Points to remember:
- It is very much effective if you place the $match as early as possible in the aggregation pipeline that limits the total number of documents in the aggregation pipeline.
- When $match placed at the very beginning of a pipeline, the query can take advantage of indexes.
- The $where can not be used in $match queries as part of the aggregation pipeline.
Sample collection empdetails
{
"_id" : ObjectId("5541ffb465713ddc838b2dc7"),
"emp_code" : "E005",
"emp_name" : "Alan Hogg",
"date_of_join" : "15/09/2013",
"salary" : 9000,
"deduction" : {
"pf" : 2000,
"pt" : 300,
"it" : 200
}
}
{
"_id" : ObjectId("5542003c65713ddc838b2dc8"),
"emp_code" : "E006",
"emp_name" : "Karlos Mint",
"date_of_join" : "23/05/2010",
"salary" : 12000,
"deduction" : {
"pf" : 3000,
"pt" : 300,
"it" : 400
}
}
{
"_id" : ObjectId("554200a065713ddc838b2dc9"),
"emp_code" : "E007",
"emp_name" : "Burg Hence",
"date_of_join" : "27/08/2011",
"salary" : 10000,
"deduction" : 4000
}
Example : $match - to Equality Match
The following command selects the documents where the salary field equals to 9000.
> db.empdetails.aggregate(
... [ { $match : { salary : 9000 } } ]
... ).pretty();
Output :
{
"_id" : ObjectId("5541ffb465713ddc838b2dc7"),
"emp_code" : "E005",
"emp_name" : "Alan Hogg",
"date_of_join" : "15/09/2013",
"salary" : 9000,
"deduction" : {
"pf" : 2000,
"pt" : 300,
"it" : 200
}
}
Example : $match with $count
The following aggregation pipeline, $match selects the documents where the salary is greater than 9000 and less than or equal to 12000. Then sends the result for grouping with $group pipeline operator to perform a count.
db.empdetails.aggregate( [
{ $match : { salary : { $gt : 9000, $lte : 12000 } } },
{ $group: { _id: null, count: { $sum: 1 } } }
] );
Outputp:
{ "_id" : null, "count" : 2 }