26th Sep - MongoDB $cmp Operator ~ Linchakin

What is the $cmp operator in MongoDB?

MongoDB provides a variety of aggregation pipeline operators. The $cmp operator is one of those operators. The $cmp operator is used to compare two values or types and returns the result.

It returns the following result according to these conditions:

If both values are equal, it returns 0.
If the first value is greater than the second value, it returns 1.
If the first value is less than the second value, it returns -1.

Syntax of the $log10 operator:

{ $cmp : [ < expression 1 >, < expression 2 > ] }

Examples:

Suppose we have a collection of the products with the following documents.

{ { "_id" : 1, "name" : "rectangle", "length" : 11, "breath" : 10 } { "_id" : 2, "name" : "square", "length" : 10, "breath" : 10 } { "_id" : 3, "name" : "rectangle", "length" : 14, "breath" : 16 } { "_id" : 4, "name" : "square", "length" : 6, "breath" : 6 } { "_id" : 5, "name" : "rectangle", "length" : 11, "breath" : 16 } }

Example 1: Using $cmp Operator

In this example, we're going to compare the length and width fields using the $cmp operator.

db.products.aggregate ( [ { $project : { _id : 1, name : 1, length : 1, breadth : 1, result: { $cmp : [ "$length", "$breadth" ] } } } ] )

Output:

{
         "_id" : 1, 
         "name" : "rectangle",
         "length" : 11,
         "breath" : 10,
         "result" : 1
}
{
         "_id" : 2, 
         "name" : "square",
         "length" : 10,
         "breath" : 10,
         "result" : 0
}
{
         "_id" : 3, 
         "name" : "rectangle",
         "length" : 14,
         "breath" : 16,
         "result" : -1
}
{
         "_id" : 4, 
         "name" : "square",
         "length" : 6,
         "breath" : 6,
         "result" : 0
}
{
         "_id" : 5, 
         "name" : "rectangle",
         "length" : 11,
         "breath" : 16,
         "result" : -1
}

Suppose we add the following documents to our collection:

{ { "_id" : 6, "name" : "rectangle", "length" : null, "breath" : 10 } { "_id" : 7, "name" : "square", "length" : 10, "breath" : null } { "_id" : 8, "name" : "rectangle", "length" : null, "breath" : null } }

Example 2: Comparing null values

db.products.aggregate ( [ { $match : {_id : { $nin : [ 1, 2, 3, 4, 5 ] } } }, { $project : { _id : 1, name : 1, length : 1, breadth : 1, result: { $cmp : [ "$length", "$breadth" ] } } } ] )

Output:

{
         "_id" : 6, 
         "name" : "rectangle",
         "length" : null,
         "breath" : 10,
         "result" : -1
}
{
         "_id" : 7, 
         "name" : "square",
         "length" : 10,
         "breath" : null,
         "result" : 1
}
{
         "_id" : 8, 
         "name" : "rectangle",
         "length" : null,
         "breath" : null,
         "result" : 0
}

Suppose we add the following documents to our collection:

{ "_id" : 9, "name" : "item_1", "a" : ISODate("2020-05-09T23:30:15.100Z"), "b" : 10 } { "_id" : 10, "name" : "item_2", "a" : 10, "b" : ISODate("2012-11-18T04:00:20.112Z") } { "_id" : 11, "name" : "item_3", "a" : ISODate("2018-11-14T04:00:20.112Z"), "b" : ISODate("2015-10-07T04:00:20.112Z") }

Example 3: Comparing different types

db.products.aggregate ( [ { $match : {_id : { $nin : [ 1, 2, 3, 4, 5, 6, 7, 8 ] } } }, { $project : { _id : 1, name : 1, a : 1, b : 1, result: { $cmp : [ "$a", "$b" ] } } } ] )

Output:

{
         "_id" : 9, 
         "name" : "item_1",
         "a" : ISODate("2020-05-09T23:30:15.100Z"),
         "b" : 10,
         "result" : 1
}
{
         "_id" : 10, 
         "name" : "item_2",
         "a" : 10,
         "b" : ISODate("2012-11-18T04:00:20.112Z"),     
         "result" : -1
}
{
         "_id" : 11, 
         "name" : "item_3",
         "a" : ISODate("2018-11-14T04:00:20.112Z"),
         "b" : ISODate("2015-10-07T04:00:20.112Z"),
         "result" : 1
}