Nondeterministic Programming Methodology

    mongoose-fuzzy-search

    0.0.4 • Public • Published

    mongoose-fuzzy-search

    Mongoose plugin which adds fuzzy search capabilities on a Model based on trigrams sequence similarity

    Usage

    installation

    npm i --save mongoose-fuzzy-search

    Apply to a model

    import fuzzy from 'mongoose-fuzzy-search';
     
    const schema = new mongoose.Schema('User', {
        firstname: String,
        lastname: String
    });
     
    // add the plugin to the model and specify new fields on your schema to hold the trigrams projected 
    schema.plugin(fuzzy, {
       fields:{
           lastname_tg: 'lastname', // equivalent to (doc) => doc.get('lastname')
           fullname_tg: (doc) => [doc.get('firstname'), doc.get('lastname') ].join(' ') 
       }
    })
    const User = mongoose.model('User', schema);
     
    const user = new User({
        firstname: 'Laurent',    
        lastname: 'Renard',    
    })
     
     
    await user.save();

    The saved document will be:

    {
        "firstname": "Laurent",    
        "lastname": "Renard",
        "lastname_tg":["  r"," re","ren","ena","nar","ard","rd ","d  "],      
        "fullname_tg":["  l"," la","lau","aur","ure","ren","ent","nt ","t  ","  r"," re","ren","ena","nar","ard","rd ","d  "]      
    }

    Note: when using a string, it is equivalent to a function returning the value of the document at the matching path.

    Search

    The fuzzy static method returns a Aggregate matching the documents which have at least one matching trigram with the query and their similarity score. You can then decide to extend the pipeline: filter out, sort them, etc

    const result = await User.fuzzy('renart') // (.sort(), etc)
    // > [{ document: <the document>, similiarity: <the similarity score> }]

    similarity score

    The similarity score is calculated by dividing the size of the intersection set between the query and the document field trigrams, and the size of the trigrams set for the query.

    change the weight of the different fields

    When passing a string, the pipeline calculate the similarity for each trigram field and return the mean. However, you can combine various queries and give different weights to each of them:

    const results = await User.fuzzy({
                lastname_tg: {
                    searchQuery: 'Renard' 
                },
                fullname_tg: {
                    searchQuery: 'repnge',
                    weight: 20
                }
    });

    Notes

    This plugin does not:

    • add any index: it is up to you
    • remove stop words (which are usually language specific): you can still transform an argument before you pass it to the trigram function using the field options

    This plugin does:

    • add Document middleware on save and insertMany middleware in order to update the trigram fields on your documents on insert/update.
    • lowercase, deburr, split in words and concat each word trigram into a unique set

    This plugin is adapted for searches when relative strings length difference does not matter much (ideal for short string like emails, names, titles, etc), when the strings have no or very little semantic (like names etc).
    Otherwise, you might consider using another solution such as the native mongodb text index or a different database

    Install

    npm i mongoose-fuzzy-search

    DownloadsWeekly Downloads

    514

    Version

    0.0.4

    License

    ISC

    Unpacked Size

    85.8 kB

    Total Files

    5

    Last publish

    Collaborators

    • lorenzofox3