1. MongoDB

#mongodb #database #backend

MongoDB

MongoDB is a popular NoSQL, document-oriented database that stores data in flexible, JSON-like documents rather than traditional rows and columns. This flexibility makes it ideal for handling large amounts of unstructured or semi-structured data.

To install mongodb
mongodb install
install the the mongo db shell that is mongosh as well
mongosh
attachments/Pasted image 20241105134010.png| 400

now after installing the the mongosh zip extract the zip
keep the extract in the documents folder for easy excess
now open the extract file youll find a app right click the app open properties and copy the path

mine is
C:\Users\omkar\Documents\mongosh-2.3.3-win32-x64\mongosh-2.3.3-win32-x64\bin
now open environment variables and in the system varibales click on new and add path

attachments/Pasted image 20241105135935.png| 300 attachments/Pasted image 20241105140310.png| 300

we can also use the mongo db in vs code just install the extension in vs code

Description Example
Show all databases. show dbs
Switch to or create a database named myDatabase. use myDatabase
Drop the current database. db.dropDatabase()
Show all collections in the current database. show collections
Create a collection named myCollection. db.createCollection('myCollection')
Drop the collection named myCollection. db.myCollection.drop()
Insert a single document into myCollection. db.myCollection.insertOne({ name: 'John', age: 30 })
Insert multiple documents into myCollection. db.myCollection.insertMany([{ name: 'Jane', age: 25 }, { name: 'Doe', age: 40 }])
Retrieve all documents from myCollection. db.myCollection.find()
Find documents where age is greater than 20. db.myCollection.find({ age: { $gt: 20 } })
Update the document where name is John. db.myCollection.updateOne({ name: 'John' }, { $set: { age: 31 } })
Delete the document where name is John. db.myCollection.deleteOne({ name: 'John' })
Aggregate data based on age. db.myCollection.aggregate([{ $match: { age: { $gt: 20 } } }, { $group: { _id: "$age", total: { $sum: 1 } } }])
Get statistics about the current database. db.stats()
Get statistics about myCollection. db.myCollection.stats()
Export myCollection to a JSON file. mongoexport --db myDatabase --collection myCollection --out output.json
Import data from a JSON file into myCollection. mongoimport --db myDatabase --collection myCollection --file input.json

MongoDB Key Concepts

  1. Sorting and Limiting:

    • Explanation: Sorting allows you to order the results based on specified fields. Limiting restricts the number of documents returned.
    • Example:
      db.collectionName.find().sort({ age: 1 }).limit(5); // Sort by age ascending and limit to 5 results

  2. Find:

    • Explanation: Used to retrieve documents that match specific criteria from a collection.
    • Example:
      db.collectionName.find({ age: { $gt: 25 } }); // Find all documents with age > 25

  3. Update:

    • Explanation: Modifies existing documents in a collection. You can update specific fields or replace the entire document.
    • Example:
      db.collectionName.updateOne({ name: "John" }, { $set: { age: 32 } });

  4. Delete:

    • Explanation: Removes documents from a collection. You can delete one document, many documents, or all documents based on the criteria.
    • Example:
      db.collectionName.deleteOne({ name: "Jane" });

  5. Comparison Operators:

    • Explanation: Operators like $gt (greater than), $lt (less than), $eq (equal to) help filter data in queries.
    • Examples:
      • $gt: Greater than
      • $lt: Less than
      • $gte: Greater than or equal to
      • $lte: Less than or equal to
      db.collectionName.find({ age: { $gte: 25 } });

  6. Logical Operators:

    • Explanation: Logical operators such as $or, $and, $not are used to combine multiple conditions.
    • Example:
      db.collectionName.find({ $or: [{ age: { $lt: 20 } }, { age: { $gt: 50 } }] });

  7. Indexes:

    • Explanation: Indexes improve query performance by allowing the database to locate and retrieve data faster. They are often created on fields that are frequently searched.
    • Example:
      db.collectionName.createIndex({ age: 1 }); // Creates an ascending index on the age field

  8. Collections:

    • Explanation: Collections are like tables in MongoDB, storing groups of documents with similar purposes. Each document in a collection can have different fields and structures.
    • Example:
      • Create a collection: db.createCollection("users")