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How to use mongodb

Apr 02, 2024 pm 01:09 PM

How to use MongoDB: Download and install MongoDB. Create a database and connect to it. Create a collection (similar to a table). Insert a document (the unit in which data is stored). Query documents (using a query language). Update documents (modify existing data). Delete the document (permanently removes the data). Aggregation pipeline (processing data in series). Other features: data validation, indexing, replication, sharding.

How to use mongodb

How to use MongoDB

Install MongoDB

  • Download the official MongoDB installer: https://www.mongodb.com/try/download/community
  • Follow the instructions in the installer to install

Create database

<code>mongod --dbpath /path/to/data</code>
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Connect to the database

<code>mongo</code>
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Create a collection

  • A collection is similar to a relational database Table in

    <code>db.createCollection("myCollection")</code>
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Insert document

  • ##Document is the basic unit of data storage in MongoDB

    <code>db.myCollection.insertOne({ name: "John Doe", age: 30 })</code>
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Query documents

  • Query uses the query language to filter documents in the collection

    <code>db.myCollection.find({ age: { $gt: 25 } })</code>
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Update document

  • Update document can modify the data in the existing document

    <code>db.myCollection.updateOne({ name: "John Doe" }, { $set: { age: 31 } })</code>
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Delete document

  • Deleting a document permanently removes it from the collection

    <code>db.myCollection.deleteOne({ name: "John Doe" })</code>
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Aggregation Pipeline

  • Aggregation pipelines chain multiple operations together to process data

    <code>db.myCollection.aggregate([
    { $match: { age: { $gt: 25 } } },
    { $group: { _id: "$name", averageAge: { $avg: "$age" } } }
    ])</code>
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More features

MongoDB also provides the following Features:

  • Data validation: Ensure data conforms to specific rules
  • Index: Improve query performance
  • Replication: Provide redundancy and fault tolerance for data
  • Sharding: Distribute large data sets to multiple servers

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