MongoDB Filtering: A Complete Guide 101 - Learn | Hello (2023)

With the exponential growth of semi-structured and unstructured data on the web, it becomes imperative for organizations to look for a robust database management system. MongoDB has become the popular choice as a NoSQL and document-oriented database for processing this type of data. When trying to query, aggregate, and analyze MongoDB data, it becomes critical to optimize your queries to get faster results with minimal computational effort.

One solution is performance.MongoDB Filteringwhich returns only those documents that match its specified condition. You can also run MongoDB filtering in MongoDB Compass to take advantage of the powerful GUI tool. You can also perform MongoDB filtering and optimize query performance with other MongoDB products, such as MongoDB Atlas App Services.

In this article, you'll learn more about MongoDB filtering and how to apply filters to your queries.

Index

• What is MongoDB?
  • Main features of MongoDB
• Why do you need MongoDB filtering?
• MongoDB Filtering: 3 Critical Issues
  • MongoDB Filtering: MongoDB Filter Aggregation Operator
  • Filtrado MongoDB: MongoDB Compass
  • Filtered MongoDB: MongoDB domain
• Diploma

MongoDB es popularFree, open source, cross-platform document-oriented databasedesigned to efficiently store and process large amounts of data. Unlike traditional relational databases, MongoDB is classified as a NoSQL database management system that uses JSON-like collections and documents instead of tables made up of rows and columns. Each collection consists of several documents that contain the basic units of data in the form of key-value pairs.

Officially released in 2009 as an open source development model, the MongoDB database is developed, maintained, and managed by MongoDB.Inc under a combination ofServer Side Public LicenseIt's inapache license. MongoDB is widely used by organizations like MetLife, Barclays, Viacom, New York Times, Facebook, Nokia, eBay, Adobe, Google, etc. MongoDB is very flexible as it supports multiple programming languages ​​likeC, C++, C#, Go, Java, Node.js, Perl, PHP, Python, Motor, Ruby, Scala, Swift y Mongoid.

Main features of MongoDB

MongoDB offers a wide range of attractive features:

• High data availability:MongoDB replication The role provides multiple servers for backup and disaster recovery. Since multiple servers store the same data or chunks of data, MongoDB offers higher data availability and stability. You don't have to worry about server crashes, service interruptions, or even old hardware failures because real-time data replication ensures uninterrupted data access and security.
• supercharged analysis: You may need to consider thousands to millions of variables when running ad hoc queries. MongoDB indexes BSON documents and uses MongoDB Query Language (MQL) that allows ad hoc query updates in real time. MongoDB has full support for field queries, range queries, and regular expression searches along with custom functions.
• indexing: ComVarious indexes and language-specific sort order functionsMongoDB provides optimal query performance to support complex record access patterns. For real-time query patterns and ever-evolving application needs, MongoDB also offers on-demand index creation.
• horizontal scalability: Through the use of sharding, MongoDB provides horizontal scalability by using sharded keys to distribute data across various combinations of servers. Each shard in each MongoDB cluster stores pieces of data, thus acting as a separate database. This comprehensive database collection enables efficient handling of ever-increasing amounts of data without downtime. The entire sharding ecosystem is monitored and managed by mongos, which forward queries to the correct shard based on the shard key.
• load balancing: Real-time replication and sharding have a huge impact on large-scale load balancing. first class guarantee Concurrency controls and locking protocols allow MongoDB to effectively handle multiple simultaneous read and write requests for the same data.
• accumulation: Equal toSQL grouping byclause, MongoDB can easily batch data and return a single result even after performing multiple other operations on the data in the group. The MongoDB aggregation framework consists of 3 types of aggregations, namely H.Pipeline aggregation, map reduce function, and single purpose aggregation methods.

Why do you need MongoDB filtering?

By applying a filter to your query, you essentially change the MongoDB query so that it only returns a subset of results that match the query. These filters contain additional query parameters that allow you to omit fields from your query. You can apply filters on:

• Optimize queries and minimize computational effort.
• Protect sensitive data by skipping critical or unused fields.
• Restrict queries to a subset of all documents.

MongoDB Filtering: 3 Critical Issues

To understand MongoDB filtering effectively, you can go through the following aspects:

• MongoDB Filtering: MongoDB Filter Aggregation Operator
• Filtrado MongoDB: MongoDB Compass
• Filtered MongoDB: MongoDB domain

MongoDB Filtering: MongoDB Filter Aggregation Operator

With version 3.2, you can start filtering MongoDB with the new$filteraggregation operator. This operator selects and returns a subset of an array based on the specified condition. Note that this array of elements is in the original order. You can use the following syntax for the $filter operator:

{ $filter: { entry: <matrix>, as: <chain>, cond: <expression> } }

The above syntax consists of the following parameters:

• Forbidden: This points to the array from which you want to filter the data.
• con: This is an optional parameter that represents the variable name of an element in its input array. If you don't provide a name, "this" will be assigned as the default name.
• condition: With this parameter you can specify whether an element of an array should be included in the query result or not. The filter operator individually references each element of your input array with the variable name that you specified in the As parameter.

You can use the following conditions in the cond parameter for MongoDB filtering:

• Greater than ((>) or $gt)
• Less than ((<) or $lt)
• Greater than equal to ((>=) or $gte)
• Less than equal to ((<=) or $old)

To understand MongoDB filtering, you can refer to the sample collection inventory, which includes the following documents:

{ _id: 101, products: [ { prod_id: 56, quantity: 10, cost: 200 }, { prod_id: 3, quantity: 5, cost: 340 } ]}{ _id: 102, products: [ { prod_id: 40, Quantity: 4, Cost: 120 }, { Product ID: 20, Quantity: 5, Cost: 3 }, { Product ID: 30, Quantity: 2, Cost: 200 } ]}{ _ID: 103, Products: [ { Product ID: 4 , Quantity: 3, Cost: 25 } ]}

You can use the $filter operator for MongoDB filtering to get the products whose cost is greater than 100.

Investigation:

db.inventory.aggregate([ { $project: { products: { $filter: { input: "$products", as: "prod", cond: { $gte: [ "$$prod.cost", 100 ] } } } } }])

Salida:

{ "_id" : 0, "productos" : [ { prod_id: 56, Menge: 10, Costo: 200 }, { prod_id: 3, Menge: 5, Costo: 340} ]}{ "_id" : 1, "productos " : [ { prod_id: 40, Menge: 4, Custo: 120 }, {prod_id: 30, Menge: 2, Custo: 200 } ]}{ "_id" : 2, "products" : [ ] }

Filtrado MongoDB: MongoDB Compass

An effective way to query, aggregate, and analyze your MongoDB data is to use a powerful GUI like MongoDB Compass. It is completely free and compatible with macOS, Windows and Linux. You can simply specify the filter document in the filter box on the query bar and clickRunto run the query. For example, you can consider a sample query for MongoDB filtering that returns documents with the country value Brazil:

It should be noted that the Compass filter used for MongoDB filtering uses themongoShell mode representation of MongoDB extended JSONBSON data types. For example, you might consider the following filter, which returns documents where start_date is greater than the BSON date 2020-07-04:

{ "fecha_de_inicio": {$gt: new data('2020-07-04')} }

By specifying the date type in start_date and the comparison operator $gt, Compass performs the greater-than-chronological comparison and returns documents with a start_date after 7/4/2020.

However, if you try to run the query without the date type, MongoDB Compass compares the start dates as stringslexicographical, instead of comparing values ​​chronologically.

Filtrado MongoDB: MongoDB Atlas Application Services

MongoDB Atlas App Services allows you to easily write and host an application in a fully managed cloud ecosystem. This cloud environment includes Atlas Device Sync, serverless cloud capabilities, declarative data access rules, and more. A filter in App Services consists of the following components:

• apply when: You can use this expression to check if the filter is applied to an incoming request. You can use variables like%%of usermi%%Investigation, although you can't use MongoDB variables like%%Fuentesince the application services apply their filters before reading any data.
• Optional query document: You can provide the standard MongoDB query syntax for this query. This query document is merged with the existing query for each query that matches the filter.
• Optional screening document: This document uses the standard MongoDB projection syntax and is merged with the existing projection of each request to which the filter is applied.

To understand MongoDB filtering for application services, consider the following collection of examples:

{ "_id": ObjectId(...), "name": "suraj", Alter: 34, "vote": "no", "shareVoteAnonymous": true }{ "_id": ObjectId(...), "name": "anand", Alter: 56, "vote": "sí", "shareVoteAnonymous": true }{ "_id": ObjectId(...), "name": "jenny", Alter: 44, "vote": "no", "shareVoteAnonymous": false }{ "_id": ObjectId(...), "name": "rob", Alter: 52, "vote": "no", "shareVoteAnonymous": true }{ "_id": ObjectId(...), "name": "tim", Alter: 28, "vote": "no", "shareVoteAnonymous": false }{ "_id": ObjectId(... ), "name": "bain", Alter: 54, "vote": "yes", "shareVoteAnonymous": true }

Filter:

{ "name": "AnonymizeVotes", "apply_when": true, "query": { "shareVoteAnonymous": true }, "project": { "_id": { "_id": 0, "age": 1, " votar": 1 } }

Salida:

{ age: 34, "vote": "No" }{ age: 56, "vote": "Yes" }{ age: 44, "vote": "No" }{ age: 52, "vote": "No " }{ Age: 28, "Vote": "No" }{ Age: 54, "Vote": "Yes" }

Diploma

You learned it in this article.MongoDB Filteringand how to effectively filter documents in MongoDB. MongoDB provides the $filter aggregation operator, which you can use to filter your documents and extract the desired fields based on the specified condition. You can also use MongoDB Compose to easily query your MongoDB data in a visual environment by simply providing the filter in the query bar. MongoDB Atlas App Services also allows you to filter the incoming MongoDB query. The filter can add additional query parameters and omit fields from the query results before App Services executes the query.

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Share your experience with MongoDB filtering! Let us know in the comments section!