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This tutorial provides a comprehensive guide to understanding and working with MongoDB, from basic concepts to advanced operations.
Introduction to MongoDB
MongoDB is a NoSQL database that offers a flexible and scalable approach to data management. Unlike traditional relational databases, MongoDB utilizes a document-based structure, enabling a more intuitive way of organizing, accessing, and manipulating data.
Installation and Setup
Basic Concepts (Database, Collection, Document)
Document
A document is a basic unit of data in MongoDB, and it's analogous to a row in a relational database. Each document contains key-value pairs, where the keys are strings, and the values can be of various data types, including other documents or arrays of documents.
Documents within a collection can have different fields or structures.
Collection
A collection is a group of MongoDB documents, similar to a table in a relational database. Unlike a table, however, the documents within a collection can have different fields or structures.
Collections do not enforce a schema, meaning that the documents within a collection can vary in the fields they contain.
Database
In MongoDB, a database is a physical container for collections. Each database gets its file system on the host within which it stores files. A single MongoDB server can have multiple databases.
Field
A field is a name-value pair within a document. A field's name is a string, and its value can be a variety of data types, including other documents, arrays, or arrays of documents.
Embedded Documents
These are documents nested within other documents. MongoDB supports hierarchical or multi-dimensional data structures by allowing documents to embed documents within them.
Primary Key
MongoDB automatically creates a unique index on the _id field when a new collection is created.
The _id field serves as the primary key for the collection, ensuring that its value is unique across the collection.
Index
Indexes support the efficient execution of queries in MongoDB. Without indexes, MongoDB must perform a collection scan to search all the documents in a collection to select those that match the query statement. With an appropriate index, however, MongoDB can limit the number of documents it must inspect.
Replication
Replication provides redundancy and high availability and is critical for maintaining the robustness of the system. This is achieved by maintaining multiple copies of data across different servers.
Sharding
Sharding is a method used to distribute data across multiple machines. MongoDB uses sharding to support deployments with very large data sets and high throughput operations.
Aggregation
The aggregation framework in MongoDB provides a means to perform various data analysis and computational operations on the data. It enables users to obtain the kind of results for which the SQL GROUP BY clause is used.
Query Language
MongoDB provides a rich query language that allows you to perform read and write operations, as well as perform administrative functions and other miscellaneous tasks.
GridFS
If you need to store and retrieve files that exceed the BSON document size limit of 16MB, you can use MongoDB's GridFS API.
Create and Drop Database
Create and Drop Collection
CRUD Operations
MongoDB Projection
MongoDB Limit and Sort Documents
MongoDB Indexing
MongoDB with Java Programming Language
- Java MongoDB Connection Example
- Java MongoDB Create Collection Example
- Java MongoDB Drop Collection Example
- Java MongoDB Create or Insert Document Example Tutorial
- Java MongoDB Update Document Example
- Java MongoDB Read Document Example
- Java MongoDB Delete Document Example
- MongoDB Java CRUD Operations Example Tutorial
- MongoDB Commands with Examples
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