how to convert string to numerical values in mongo

Question

I am trying to convert a string that contains a numerical value to its value in an aggregate query in MongoDB.

Example of document

{
"_id": ObjectId("5522XXXXXXXXXXXX"),
   "Date": "2015-04-05",
   "PartnerID": "123456",
   "moop": "1234" 
}

Example of the aggregate query I use

{
    aggregate: 'my_collection',
    pipeline: [
         {$match: {
             Date : 
                  {$gt:'2015-04-01', 
                  $lt: '2015-04-05'
                  }}
             },
         {$group:
             {_id: "$PartnerID",
              total:{$sum:'$moop'}
             }}]}

where the results are

{
   "result": [
     {
       "_id": "123456",
       "total": NumberInt(0) 
    }
}

How can you convert the string to its numerical value?

Answer 1

String can be converted to numbers in MongoDB v4.0 using $toInt operator. In this case

db.col.aggregate([
    {
        $project: {
            _id: 0,
            moopNumber: { $toInt: "$moop" }
        }
    }
])

outputs:

{ "moopNumber" : 1234 }

Answer 2

Using MongoDB 4.0 and newer

You have two options i.e. $toInt or $convert. Using $toInt, follow the example below:

filterDateStage = {
    '$match': {
        'Date': {
            '$gt': '2015-04-01', 
            '$lt': '2015-04-05'
        }
    }
};

groupStage = {
    '$group': {
        '_id': '$PartnerID',
        'total': { '$sum': { '$toInt': '$moop' } }
    }
};

db.getCollection('my_collection').aggregate([
   filterDateStage,
   groupStage
])

If the conversion operation encounters an error, the aggregation operation stops and throws an error. To override this behavior, use $convert instead.

Using $convert

groupStage = {
    '$group': {
        '_id': '$PartnerID',
        'total': { 
            '$sum': { 
                '$convert': { 'input': '$moop', 'to': 'int' }
            } 
        }
    }
};

---

Using Map/Reduce

With map/reduce you can use javascript functions like parseInt() to do the conversion. As an example, you could 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 converted moop string value to the PartnerID for each document and emits the PartnerID and converted moop pair. This is where the javascript native function parseInt() can be applied:

var mapper = function () {
    var x = parseInt(this.moop);
    emit(this.PartnerID, x);
};

Next, define the corresponding reduce function with two arguments keyCustId and valuesMoop. valuesMoop is an array whose elements are the integer moop values emitted by the map function and grouped by keyPartnerID. The function reduces the valuesMoop array to the sum of its elements.

var reducer = function(keyPartnerID, valuesMoop) {
                  return Array.sum(valuesMoop);
              };

db.collection.mapReduce(
    mapper,
    reducer,
    {
        out : "example_results",
        query: { 
            Date: {
                $gt: "2015-04-01", 
                $lt: "2015-04-05"
            }
        }       
    }
 );

 db.example_results.find(function (err, docs) {
    if(err) console.log(err);
    console.log(JSON.stringify(docs));
 });

For example, with the following sample collection of documents:

/* 0 */
{
    "_id" : ObjectId("550c00f81bcc15211016699b"),
    "Date" : "2015-04-04",
    "PartnerID" : "123456",
    "moop" : "1234"
}

/* 1 */
{
    "_id" : ObjectId("550c00f81bcc15211016699c"),
    "Date" : "2015-04-03",
    "PartnerID" : "123456",
    "moop" : "24"
}

/* 2 */
{
    "_id" : ObjectId("550c00f81bcc15211016699d"),
    "Date" : "2015-04-02",
    "PartnerID" : "123457",
    "moop" : "21"
}

/* 3 */
{
    "_id" : ObjectId("550c00f81bcc15211016699e"),
    "Date" : "2015-04-02",
    "PartnerID" : "123457",
    "moop" : "8"
}

The above Map/Reduce operation will save the results to the example_results collection and the shell command db.example_results.find() will give:

/* 0 */
{
    "_id" : "123456",
    "value" : 1258
}

/* 1 */
{
    "_id" : "123457",
    "value" : 29
}

Answer 3

You can easily convert the string data type to numerical data type.

Don't forget to change collectionName & FieldName. for ex : CollectionNmae : Users & FieldName : Contactno.

Try this query..

db.collectionName.find().forEach( function (x) {
x.FieldName = parseInt(x.FieldName);
db.collectionName.save(x);
});

Answer 4

Here is a pure MongoDB based solution for this problem which I just wrote for fun. It's effectively a server-side string-to-number parser which supports positive and negative numbers as well as decimals:

db.collection.aggregate({
    $addFields: {
        "moop": {
            $reduce: {
                "input": {
                    $map: { // split string into char array so we can loop over individual characters
                        "input": {
                            $range: [ 0, { $strLenCP: "$moop" } ] // using an array of all numbers from 0 to the length of the string
                        },
                        "in":{
                            $substrCP: [ "$moop", "$$this", 1 ] // return the nth character as the mapped value for the current index
                        }
                    }
                },
                "initialValue": { // initialize the parser with a 0 value
                    "n": 0, // the current number
                    "sign": 1, // used for positive/negative numbers
                    "div": null, // used for shifting on the right side of the decimal separator "."
                    "mult": 10 // used for shifting on the left side of the decimal separator "."
                }, // start with a zero
                "in": {
                    $let: {
                        "vars": {
                            "n": {
                                $switch: { // char-to-number mapping
                                    branches: [
                                        { "case": { $eq: [ "$$this", "1" ] }, "then": 1 },
                                        { "case": { $eq: [ "$$this", "2" ] }, "then": 2 },
                                        { "case": { $eq: [ "$$this", "3" ] }, "then": 3 },
                                        { "case": { $eq: [ "$$this", "4" ] }, "then": 4 },
                                        { "case": { $eq: [ "$$this", "5" ] }, "then": 5 },
                                        { "case": { $eq: [ "$$this", "6" ] }, "then": 6 },
                                        { "case": { $eq: [ "$$this", "7" ] }, "then": 7 },
                                        { "case": { $eq: [ "$$this", "8" ] }, "then": 8 },
                                        { "case": { $eq: [ "$$this", "9" ] }, "then": 9 },
                                        { "case": { $eq: [ "$$this", "0" ] }, "then": 0 },
                                        { "case": { $and: [ { $eq: [ "$$this", "-" ] }, { $eq: [ "$$value.n", 0 ] } ] }, "then": "-" }, // we allow a minus sign at the start
                                        { "case": { $eq: [ "$$this", "." ] }, "then": "." }
                                    ],
                                    default: null // marker to skip the current character
                                } 
                            }
                        },
                        "in": {
                            $switch: {
                                "branches": [
                                    {
                                        "case": { $eq: [ "$$n", "-" ] },
                                        "then": { // handle negative numbers
                                            "sign": -1, // set sign to -1, the rest stays untouched
                                            "n": "$$value.n",
                                            "div": "$$value.div",
                                            "mult": "$$value.mult",
                                        },
                                    },
                                    {
                                        "case": { $eq: [ "$$n", null ] }, // null is the "ignore this character" marker
                                        "then": "$$value" // no change to current value
                                    }, 
                                    {
                                        "case": { $eq: [ "$$n", "." ] },
                                        "then": { // handle decimals
                                            "n": "$$value.n",
                                            "sign": "$$value.sign",
                                            "div": 10, // from the decimal separator "." onwards, we start dividing new numbers by some divisor which starts at 10 initially
                                            "mult": 1, // and we stop multiplying the current value by ten
                                        },
                                    }, 
                                ],
                                "default": {
                                    "n": {
                                        $add: [
                                            { $multiply: [ "$$value.n", "$$value.mult" ] }, // multiply the already parsed number by 10 because we're moving one step to the right or by one once we're hitting the decimals section
                                            { $divide: [ "$$n", { $ifNull: [ "$$value.div", 1 ] } ] } // add the respective numerical value of what we look at currently, potentially divided by a divisor
                                        ]
                                    },
                                    "sign": "$$value.sign",
                                    "div": { $multiply: [ "$$value.div" , 10 ] },
                                    "mult": "$$value.mult"
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}, {
    $addFields: { // fix sign
        "moop": { $multiply: [ "$moop.n", "$moop.sign" ] }
    }
})

I am certainly not advertising this as the bee's knees or anything and it might have severe performance implications for larger datasets over a client based solutions but there might be cases where it comes in handy...

The above pipeline will transform the following documents:

{ "moop": "12345" } --> { "moop": 12345 }

and

{ "moop": "123.45" } --> { "moop": 123.45 }

and

{ "moop": "-123.45" } --> { "moop": -123.45 }

and

{ "moop": "2018-01-03" } --> { "moop": 20180103.0 }