Query MongoDB using SQLlike syntax with MQL.

In MongoDB, querying data using the SQLlike syntax is possible thanks to the MongoDB Query Language MQL. This feature allows users familiar with SQL to execute queries in MongoDB with ease and familiarity. Lets explore how to query MongoDB using this powerful language.To start querying MongoDB with MQL, ensure that you have a MongoDB instance running and a database with data that you want to query. You can connect to your MongoDB instance using the MongoDB shell or any MongoDB client that supports MQL.1. SELECT StatementIn SQL, the SELECT statement is used to retrieve data from a database. Similarly, in MongoDB, the find method is used to query data from a collection. The basic syntax for querying data in MongoDB using the find method is as followsndb.collection.find query , projection nHere, query is a document that specifies the criteria for the selection, and projection is an optional document that specifies which fields to include or exclude in the result set.For example, to retrieve all documents from a collection named users in a MongoDB database, you can use the following queryndb.users.findn2. WHERE ClauseIn SQL, the WHERE clause is used to filter records based on a specified condition. In MongoDB, you can achieve the same using the query document within the find method. For example, to find all users with the age of 25 in the users collection, you can use the following queryndb.users.find age 25 n3. ORDER BY ClauseIn SQL, the ORDER BY clause is used to sort the result set in ascending or descending order based on one or more columns. In MongoDB, you can achieve sorting using the sort method in combination with the find method. For example, to sort the users by their age in descending order, you can use the following queryndb.users.find.sort age 1 n4. LIMIT and OFFSET ClausesIn SQL, the LIMIT and OFFSET clauses are used to limit the number of records returned and skip a specified number of records, respectively. In MongoDB, you can achieve the same using the limit and skip methods in combination with the find method. For example, to retrieve the first 5 users from the users collection skipping the first 2 records, you can use the following queryndb.users.find.skip2.limit5n5. JOIN OperationsIn SQL, JOIN operations are used to retrieve data from two or more related tables based on a related column between them. In MongoDB, the concept of JOIN is different due to the NoSQL nature of the database. Instead of JOINs, you can denormalize your data by embedding related data within a single document or using multiple collections and referencing documents between them.6. Aggregation FunctionsIn SQL, aggregation functions such as COUNT, SUM, AVG, etc., are used to perform calculations on groups of records. In MongoDB, you can achieve similar functionality using the aggregation pipeline. The aggregation pipeline consists of stages that process and transform the data sequentially.For example, to calculate the average age of users in the users collection, you can use the following aggregation queryndb.users.aggregaten group _id null, avgAge avg age nnThese are just a few examples of how you can query MongoDB using the MQL syntax, which is very similar to SQL. By leveraging the power of MQL, you can easily retrieve and manipulate data in MongoDB, whether you are a SQL expert or new to NoSQL databases. So, next time you need to query MongoDB, feel free to use the SQLlike syntax to get the job done efficiently. Happy querying!