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MongoDb query condition on comparing 2 fields

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How does MongoDB compare two databases?

First of all, download our MongoDB GUI in case you haven't already. It's available for Windows, Mac, and Linux. Next, open Data Compare and Sync either by right-clicking on a collection or clicking on the Compare button.

How do I test multiple conditions in MongoDB?

Find Multiple Conditions Using the $or Operator The or operator in MongoDB is used to select or retrieve only documents that match at least one of the provided phrases. You can also use this operator in a method like a find() , update() , etc., as per the requirements.

Which evaluation operator should you use if you want to query documents from a collection by comparing the values of two fields?

we can use the $where query operator to find the documents after comparing the two fields.


You can use a $where. Just be aware it will be fairly slow (has to execute Javascript code on every record) so combine with indexed queries if you can.

db.T.find( { $where: function() { return this.Grade1 > this.Grade2 } } );

or more compact:

db.T.find( { $where : "this.Grade1 > this.Grade2" } );

UPD for mongodb v.3.6+

you can use $expr as described in recent answer


You can use $expr ( 3.6 mongo version operator ) to use aggregation functions in regular query.

Compare query operators vs aggregation comparison operators.

Regular Query:

db.T.find({$expr:{$gt:["$Grade1", "$Grade2"]}})

Aggregation Query:

db.T.aggregate({$match:{$expr:{$gt:["$Grade1", "$Grade2"]}}})

If your query consists only of the $where operator, you can pass in just the JavaScript expression:

db.T.find("this.Grade1 > this.Grade2");

For greater performance, run an aggregate operation that has a $redact pipeline to filter the documents which satisfy the given condition.

The $redact pipeline incorporates the functionality of $project and $match to implement field level redaction where it will return all documents matching the condition using $$KEEP and removes from the pipeline results those that don't match using the $$PRUNE variable.


Running the following aggregate operation filter the documents more efficiently than using $where for large collections as this uses a single pipeline and native MongoDB operators, rather than JavaScript evaluations with $where, which can slow down the query:

db.T.aggregate([
    {
        "$redact": {
            "$cond": [
                { "$gt": [ "$Grade1", "$Grade2" ] },
                "$$KEEP",
                "$$PRUNE"
            ]
        }
    }
])

which is a more simplified version of incorporating the two pipelines $project and $match:

db.T.aggregate([
    {
        "$project": {
            "isGrade1Greater": { "$cmp": [ "$Grade1", "$Grade2" ] },
            "Grade1": 1,
            "Grade2": 1,
            "OtherFields": 1,
            ...
        }
    },
    { "$match": { "isGrade1Greater": 1 } }
])

With MongoDB 3.4 and newer:

db.T.aggregate([
    {
        "$addFields": {
            "isGrade1Greater": { "$cmp": [ "$Grade1", "$Grade2" ] }
        }
    },
    { "$match": { "isGrade1Greater": 1 } }
])

In case performance is more important than readability and as long as your condition consists of simple arithmetic operations, you can use aggregation pipeline. First, use $project to calculate the left hand side of the condition (take all fields to left hand side). Then use $match to compare with a constant and filter. This way you avoid javascript execution. Below is my test in python:

import pymongo
from random import randrange

docs = [{'Grade1': randrange(10), 'Grade2': randrange(10)} for __ in range(100000)]

coll = pymongo.MongoClient().test_db.grades
coll.insert_many(docs)

Using aggregate:

%timeit -n1 -r1 list(coll.aggregate([
    {
        '$project': {
            'diff': {'$subtract': ['$Grade1', '$Grade2']},
            'Grade1': 1,
            'Grade2': 1
        }
    },
    {
        '$match': {'diff': {'$gt': 0}}
    }
]))

1 loop, best of 1: 192 ms per loop

Using find and $where:

%timeit -n1 -r1 list(coll.find({'$where': 'this.Grade1 > this.Grade2'}))

1 loop, best of 1: 4.54 s per loop