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  • MongoDB – (No-SQL)

MongoDB – (No-SQL)

Curriculum

  • 10 Sections
  • 31 Lessons
  • 10 Weeks
Expand all sectionsCollapse all sections
  • Introduction to MongoDB
    MongoDB is a NoSQL database that is designed for handling large volumes of unstructured or semi-structured data. Unlike traditional relational databases (RDBMS) that use tables and rows to organize data, MongoDB stores data in a flexible document-oriented format using JSON-like documents (BSON - Binary JSON). This makes it highly scalable, flexible, and performant for applications that need to handle varying types of data with complex structures.
    5
    • 1.1
      What is MongoDB?
    • 1.2
      Why MongoDB?
    • 1.3
      When to use MongoDB?
    • 1.4
      Key Features of MongoDB
    • 1.5
      Installing MongoDB
  • MongoDB Basic Operations
    MongoDB provides a rich set of basic operations for interacting with the database, including creating, reading, updating, and deleting data (often abbreviated as CRUD operations). Below are the basic operations that you can perform with MongoDB.
    2
    • 2.0
      Database and Collection Basics
    • 2.1
      CRUD Operations
  • Advanced Querying Techniques
    MongoDB offers a rich set of querying capabilities, and as you work with larger datasets and more complex application requirements, you’ll often need to use advanced querying techniques. These techniques help you optimize performance, execute sophisticated queries, and leverage MongoDB’s powerful indexing and aggregation features.
    4
    • 3.1
      Query Filters and Operators
    • 3.2
      Advanced Querying
    • 3.3
      Sorting and Limiting Results
    • 3.4
      Aggregation Framework
  • Data Modeling and Schema Design
    Data modeling and schema design are critical when using MongoDB (or any NoSQL database) to ensure efficient data storage, fast queries, and scalability. Unlike relational databases, MongoDB is schema-less, which means you are not required to define a fixed schema upfront. However, making the right design decisions from the beginning is essential for maintaining performance and avoid complications as your data grows.
    4
    • 4.1
      Data Modeling
    • 4.2
      Document Structure
    • 4.3
      Schema Design Patterns
    • 4.4
      MongoDB and Relationships
  • Indexing and Performance Optimization
    In MongoDB, indexing is a critical part of performance optimization. Without proper indexes, MongoDB has to scan every document in a collection to satisfy queries, which can be very inefficient for large datasets. Indexes are used to quickly locate data without scanning every document, making reads faster and more efficient.
    3
    • 5.0
      Creating Indexes
    • 5.1
      Using Text Search
    • 5.2
      Performance Optimization
  • Integrating MongoDB with a Web Application (Node.js)
    Integrating MongoDB with a web application built using Node.js is a common and powerful combination for building scalable and efficient web apps. MongoDB’s flexibility with JSON-like data and Node.js's asynchronous event-driven architecture work well together. In this guide, I'll walk you through the steps for integrating MongoDB with a Node.js web application, covering the essentials of setting up the connection, performing CRUD operations, and using popular libraries.
    3
    • 6.0
      Setting Up MongoDB with Node.js
    • 6.1
      CRUD Operations with Mongoose
    • 6.2
      Error Handling and Validation
  • Security in MongoDB
    Security is an essential aspect when working with MongoDB, especially when handling sensitive data in production environments. MongoDB provides a variety of security features to help protect your data against unauthorized access, injection attacks, and other vulnerabilities. Here’s a guide on securing MongoDB and your Node.js application when interacting with MongoDB.
    2
    • 7.0
      Authentication and Authorization
    • 7.1
      Data Encryption
  • Working with MongoDB in Production
    3
    • 8.0
      MongoDB Backup and Restore
    • 8.1
      MongoDB Scaling and Sharding
    • 8.2
      MongoDB Replication
  • Deploying and Monitoring MongoDB
    Working with MongoDB in a production environment requires careful planning, attention to detail, and best practices to ensure optimal performance, security, reliability, and scalability.
    3
    • 9.0
      Deploying MongoDB to Production
    • 9.1
      Monitoring and Management
    • 9.2
      Summary for MongoDB deployment on Production
  • Building a Web App with MongoDB (Final Project)
    Demo Project (OneStopShop)
    2
    • 10.0
      Building the Application
    • 10.1
      Final Project Features

MongoDB Replication

Replication is a critical feature in MongoDB that allows you to create copies of your data across multiple servers, ensuring high availability, fault tolerance, and data redundancy. Replication in MongoDB is achieved through the use of Replica Sets, which are groups of MongoDB servers that maintain the same data set.

1. What is MongoDB Replication?

MongoDB replication is the process of synchronizing data across multiple MongoDB servers to ensure that the data is fault-tolerant, highly available, and can withstand server failures. The replication mechanism ensures that if one node (primary) goes down, another node (secondary) can take over, maintaining availability and consistency.

In MongoDB, replication is achieved using Replica Sets. A Replica Set is a group of MongoDB servers that share the same data set. Replica sets provide automatic failover and data redundancy, making them crucial for production environments.

Key Components of a Replica Set:

  1. Primary Node:
    • The primary node is the main node in a replica set where all write operations occur.
    • All data changes are made to the primary node, which then replicates those changes to the secondary nodes.
  2. Secondary Nodes:
    • Secondary nodes are copies of the primary node. They replicate data from the primary.
    • Secondary nodes can be used for read operations if read preference allows, but they cannot handle write operations unless they are promoted to the primary node.
  3. Arbiter:
    • An arbiter is a node that participates in elections for the primary node but does not store data. It exists solely for the purpose of breaking ties in case of a failure (when there is an even number of nodes in the replica set).
    • Arbiters are useful when you want to maintain an odd number of votes in the replica set to ensure a primary is always elected.
  4. Replication Oplog:
    • The oplog (operations log) is a special capped collection that logs all operations that modify the data in a replica set.
    • Secondary nodes replicate from the oplog of the primary node. The oplog is crucial for maintaining the order of operations in the replica set.

2. How MongoDB Replication Works

Replication in MongoDB works by having the primary node log all write operations to the oplog. This oplog is then replicated to the secondary nodes to keep them synchronized with the primary.

  1. Write Operation:
    • A write operation is issued to the primary node (e.g., insert, update, delete).
    • The primary logs the operation to its oplog.
  2. Oplog Synchronization:
    • The secondary nodes constantly monitor the primary’s oplog and apply any changes they see.
    • Secondary nodes fetch operations from the oplog and apply them in the same order they were issued on the primary, ensuring consistency.
  3. Read Operations:
    • By default, reads are performed from the primary node.
    • However, secondary nodes can be used for read scaling by configuring read preferences (e.g., secondary, nearest).
  4. Failover:
    • If the primary node becomes unavailable, the replica set will automatically trigger an election process to elect a new primary node from the secondary nodes.
    • This process ensures that there is always one primary node available to handle write operations.

3. Replica Set Election and Automatic Failover

One of the most important features of MongoDB replication is automatic failover and primary node election. This ensures that if the primary node fails, a secondary node can be promoted to primary without manual intervention.

How Elections Work:

  • Election Process: When a primary node becomes unavailable, the remaining nodes in the replica set hold an election to choose a new primary. This is based on a combination of factors:
    • The node with the most up-to-date data (largest oplog) is more likely to become the new primary.
    • The election process involves a voting mechanism where all nodes (excluding arbiters) vote to elect the new primary.
  • Automatic Failover:
    • After the election process, the new primary is responsible for handling write operations, and the old primary (if it comes back online) will become a secondary.
    • If there is no majority of nodes in the replica set (e.g., the number of nodes is even), and the primary node fails, MongoDB cannot elect a new primary, resulting in a partitioned or unavailable state.

4. Advantages of Replication in MongoDB

  • High Availability: If the primary node goes down, one of the secondary nodes is automatically elected as the new primary, ensuring that the application can continue writing data without downtime.
  • Data Redundancy: MongoDB keeps multiple copies of the data on different servers (in different locations if desired), providing redundancy in case of hardware failures.
  • Read Scaling: By configuring read preferences, MongoDB allows read operations to be distributed across primary and secondary nodes. This reduces the load on the primary node and improves read throughput.
  • Disaster Recovery: With replication, MongoDB provides a mechanism for backing up data, as the data can be replicated across multiple geographically distributed data centers.

5. Setting Up MongoDB Replica Sets

To set up a MongoDB replica set, you will need at least three nodes: one primary and two secondaries (for fault tolerance). Here’s a basic overview of the setup:

Step 1: Start the MongoDB Instances

Start each MongoDB instance with the --replSet option, specifying the replica set name.

  1. Start the Primary Node:bashCopy codemongod --port 27017 --dbpath /data/db --replSet rs0
  2. Start the Secondary Nodes:bashCopy codemongod --port 27018 --dbpath /data/db --replSet rs0 mongod --port 27019 --dbpath /data/db --replSet rs0

Step 2: Initialize the Replica Set

After starting the MongoDB instances, connect to the primary node and initialize the replica set.

  1. Connect to the Primary Node:bashCopy codemongo --port 27017
  2. Initiate the Replica Set:javascriptCopy coders.initiate() This command will initialize the replica set and configure the first node as the primary.

Step 3: Add Secondary Nodes

After initializing the replica set, add the secondary nodes to the replica set:

  1. Add the Secondaries:javascriptCopy coders.add("localhost:27018") rs.add("localhost:27019")
  2. Check the Replica Set Status: To verify that the nodes are part of the replica set, you can run:javascriptCopy coders.status() This will show the status of all nodes, including which node is currently the primary.

6. Replica Set Configuration and Management

Replica Set Configuration Options:

  • Read Preferences: MongoDB allows you to configure how reads are distributed across replica set members. The most common read preferences are:
    • primary: Read from the primary node (default).
    • secondary: Read from a secondary node.
    • nearest: Read from the nearest available node, either primary or secondary.
    Example in a MongoDB query:javascriptCopy codedb.collection.find().readPref('secondary')
  • Write Concern: You can configure the level of acknowledgement MongoDB should wait for when performing write operations. Write concern can be set to ensure that writes are acknowledged by one or more replica set members before they are considered successful.Example:javascriptCopy codedb.collection.insert({ name: "John" }, { writeConcern: { w: 2 } })
  • Replication Lag: If a secondary node is too far behind the primary, it can cause performance issues. MongoDB provides monitoring tools (such as mongostat or rs.printSlaveReplicationInfo()) to check for replication lag.

Arbiters in a Replica Set:

Arbiters are nodes that do not store data but participate in elections. They are used to ensure there is always an odd number of voting nodes in a replica set, which prevents tied elections.

To add an arbiter:

javascript

Copy code

rs.addArb("localhost:27020")

7. Replication Best Practices

  • Odd Number of Nodes: Always use an odd number of voting nodes (including arbiters). This ensures that elections can always produce a definitive result (avoiding a split-brain situation).
  • Use Replica Sets with a Minimum of Three Nodes: A three-node replica set provides better fault tolerance and prevents the split-brain scenario.
  • Geographically Distributed Replication: Consider deploying replica sets across multiple data centers or regions to increase fault tolerance and reduce latency for users in different geographical locations.
  • Monitoring and Alerting: Use monitoring tools like MongoDB Atlas, Cloud Manager, or third-party services to monitor the health of your replica sets. Alerts should be set up for primary node failures, replication lag, and node unavailability.

Conclusion

MongoDB replication is a powerful feature that enhances the availability, fault tolerance, and scalability of MongoDB deployments. By using replica sets, MongoDB ensures that your data is replicated across

MongoDB Scaling and Sharding
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Deploying MongoDB to Production
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