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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 Backup and Restore

Backing up and restoring your MongoDB database is critical for data durability, disaster recovery, and ensuring minimal downtime in the event of failures. MongoDB provides several methods for backup and restore, ranging from simple manual backups to automated cloud-based solutions.

1. Backup Strategies

MongoDB supports both logical backups and physical backups. You should choose the backup strategy based on your requirements for backup frequency, storage space, and recovery speed.

a. Logical Backups (Mongodump/Mongorestore)

Logical backups create BSON (Binary JSON) dumps of your database or collections. These backups are portable across MongoDB versions and allow you to restore the data to another instance or cluster.

  • Use Cases: Regular database backups, migrating data, transferring data between environments (dev, staging, prod).
  • Limitations: Logical backups can be slower to restore and may require more space compared to physical backups.
Mongodump: Creating Logical Backups

The mongodump utility is used to create logical backups. You can dump the entire database or specific collections.

  1. Dump the Entire Database:bashCopy codemongodump --uri="mongodb://localhost:27017/mydb" --out=/path/to/backup
  2. Dump a Specific Collection:bashCopy codemongodump --uri="mongodb://localhost:27017/mydb" --collection=mycollection --out=/path/to/backup
  3. Backup with Authentication: If your MongoDB is configured with authentication, provide the username and password:bashCopy codemongodump --uri="mongodb://username:password@localhost:27017/mydb" --out=/path/to/backup
  4. Backup a Sharded Cluster: If you’re backing up a sharded cluster, you need to use the mongos router:bashCopy codemongodump --host=mongos-router --out=/path/to/backup
Mongorestore: Restoring Logical Backups

The mongorestore utility restores the database from the BSON dumps created by mongodump.

  1. Restore an Entire Database:bashCopy codemongorestore --uri="mongodb://localhost:27017" /path/to/backup/mydb
  2. Restore a Specific Collection:bashCopy codemongorestore --uri="mongodb://localhost:27017" --collection=mycollection /path/to/backup/mydb/mycollection.bson
  3. Restore with Authentication:bashCopy codemongorestore --uri="mongodb://username:password@localhost:27017" /path/to/backup/mydb
  4. Restore to a Different Database: You can restore a backup to a different database by using the --nsFrom and --nsTo options:bashCopy codemongorestore --uri="mongodb://localhost:27017" --nsFrom="mydb.*" --nsTo="newdb.*" /path/to/backup/mydb
  5. Restore Data from a Sharded Cluster: If restoring to a sharded cluster, ensure that the mongos router is correctly specified in the URI.

b. Physical Backups (Filesystem Snapshots)

Physical backups involve taking file system snapshots of the MongoDB data files. These backups are faster to create and restore, but they require some extra setup.

  • Use Cases: Large production environments with large databases where logical backups might take too long or require excessive disk space.
  • Limitations: Physical backups require downtime or the use of copy-on-write snapshots to ensure consistency.
Filesystem Snapshots

To create a physical backup, you take a snapshot of the MongoDB data directory while ensuring that MongoDB is either quiesced (paused) or in a consistent state. This involves using operating system tools or cloud storage snapshots (e.g., AWS EBS snapshots).

  1. Quiesce MongoDB (Optional): If you’re backing up from a running MongoDB instance, you can lock the database to ensure that it is in a consistent state during the snapshot.To lock the database:bashCopy codeuse admin db.fsyncLock() To release the lock after the snapshot:bashCopy codedb.fsyncUnlock()
  2. Snapshot the Data Directory: Use the appropriate system tools to create a snapshot of the data directory. For example:
    • On Linux (LVM snapshot):bashCopy codelvcreate --size 100G --snapshot --name mongodb_snapshot /dev/volume_group/mongodb_data
    • On AWS EC2 (EBS snapshot): Use the AWS Management Console or AWS CLI to take a snapshot of the EBS volume that holds the MongoDB data directory.
  3. Restore from a Snapshot: To restore the backup, simply revert the snapshot. Ensure MongoDB is stopped before performing the restore operation.bashCopy code# Example: restoring an EBS snapshot on AWS aws ec2 create-snapshot --volume-id vol-xxxxxxxx --description "Backup"

c. Cloud Backup (MongoDB Atlas)

If you are using MongoDB Atlas, a fully managed MongoDB service, backups are automated and handled for you, including backup retention, point-in-time recovery, and cross-region backup.

  • Automated Backups: Atlas provides daily backups with retention policies.
  • Point-in-Time Recovery (PITR): With PITR, you can restore your data to any point in time within the backup retention window.

You can configure the backup settings and restore from backups directly in the Atlas UI or API.

2. Backup Best Practices

To ensure reliable backups and smooth restores, follow these best practices:

a. Schedule Regular Backups

Set up automated backups on a schedule to ensure data consistency. Use cron jobs (Linux) or Task Scheduler (Windows) to automate mongodump or snapshot backups.

For example, a cron job for daily backups:

bash

Copy code

0 2 * * * /usr/bin/mongodump --uri="mongodb://localhost:27017" --out=/path/to/backup/$(date +\%F)

b. Retention Policy

Ensure that old backups are archived or deleted after a certain period to avoid using excessive storage. Implement a backup retention policy that defines how long backups should be kept based on your needs and compliance requirements.

c. Test Restores Regularly

Test your backups by periodically restoring them to a separate instance. This helps ensure the integrity of the backup process and prepares you for real disaster recovery scenarios.

d. Use Offsite or Cloud Storage

Store backups in offsite locations or cloud storage for added protection against physical disasters (e.g., data center outages or hardware failures). Cloud services like AWS S3, Google Cloud Storage, or Azure Blob Storage can be used to store and manage backups.

e. Backup MongoDB with Sharded Clusters

Sharded clusters require special consideration. While you can take a backup of each shard using mongodump, you must ensure that the config servers are also backed up, as they contain metadata about the cluster.

To back up a sharded cluster:

  • Use mongodump with a mongos router to capture data across all shards.
  • Alternatively, use filesystem snapshots for each shard and config server.

3. Restore Best Practices

When restoring data, especially in production environments, follow these best practices:

a. Plan for Downtime

Restoring large datasets can take time. Plan for appropriate downtime and inform stakeholders in advance. During the restoration process, MongoDB might be in a read-only state or unavailable entirely.

b. Monitor the Restore Process

Monitor the restore process for any issues, such as slow performance or missing data. If restoring from a logical backup, use mongorestore‘s logging features to check for errors.

c. Verify Data Integrity

Once the restore process is complete, verify the integrity of the data. Run sample queries, check for missing collections or documents, and verify application functionality to ensure the restore was successful.

d. Use --drop to Overwrite Existing Data

If you need to overwrite the existing data in a database during the restore process, use the --drop option with mongorestore:

bash

Copy code

mongorestore --uri="mongodb://localhost:27017" --drop /path/to/backup/mydb

This will drop the existing collections before restoring the data.

4. Monitoring and Alerts

Set up monitoring to detect backup failures or issues. MongoDB provides built-in tools like mongostat and mongotop for monitoring the health of the database. You can also integrate with cloud-based monitoring systems like MongoDB Atlas, Prometheus, or Datadog to set up alerts for backup failures, replication issues, or disk space shortages.

5. Disaster Recovery Planning

In addition to backup and restore procedures, create a disaster recovery plan that includes:

  • Clear steps for restoring the database: Document the exact steps to restore from backups in different scenarios (e.g., full restore, partial restore, or point-in-time restore).
  • RTO (Recovery Time Objective) and RPO (Recovery Point Objective): Define your acceptable downtime (RTO) and data loss (RPO) limits. Use this information to tailor your backup strategy to meet your recovery goals.

Conclusion

MongoDB provides multiple backup strategies to ensure data durability, protection, and fast recovery. Whether using mongodump for logical backups, filesystem snapshots for physical backups, or leveraging the cloud with MongoDB Atlas, it’s essential to implement a robust backup strategy tailored to your application’s needs. Regularly test your backups and ensure your disaster recovery plan is ready to minimize downtime in the event of a failure.

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