https://github.com/makarov-danil-school-projects-ctu/big-data-mongo-sharding-replication

MongoDB Cluster with sharding and replication
https://github.com/makarov-danil-school-projects-ctu/big-data-mongo-sharding-replication

clustering docker-compose mongodb nosql replication sharding

Last synced: 11 days ago
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MongoDB Cluster with sharding and replication

• Host: GitHub
• URL: https://github.com/makarov-danil-school-projects-ctu/big-data-mongo-sharding-replication
• Owner: Makarov-Danil-School-Projects-CTU
• Created: 2024-08-13T13:24:05.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-08-13T20:43:53.000Z (6 months ago)
• Last Synced: 2024-11-23T21:30:30.861Z (2 months ago)
• Topics: clustering, docker-compose, mongodb, nosql, replication, sharding
• Language: JavaScript
• Homepage:
• Size: 43.9 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
Keywords: Mongo, Docker Compose, Replication, Sharding, Clustering

## 📋 Task: Create 15 Non-Trivial Queries:

Design 15 different queries that are non-trivial and interconnected, demonstrating the capabilities and operations of the selected NoSQL database.

Each example should include:


- **The Query or Command:** The specific operation being performed on the database.


- **Solution:** The expected result or output of the query/command.


- **Detailed Explanation:** A thorough explanation of what each query/command does, why it works that way, and the context within the database.

## Utilize Database-Specific Features:

Make use of database-specific features such as:

- **Clustering:** Demonstrate how to manage and query data within a cluster.

- **Replication Factor:** Show how replication is handled, including how data is distributed across nodes and how it maintains consistency.

- **Sharding:** Provide examples of how data is partitioned across different shards, and how queries are executed in a sharded environment.

## Simulate a Node Failure:

Include an example where you simulate the failure of one or more nodes within the database cluster.


Describe Solutions: Offer possible solutions for handling such failures, explaining how the database can maintain availability, consistency, or recover from the failure, depending on the CAP theorem properties it adheres to.

## Example Format:


Each example should be clear and well-documented, with each step and its reasoning fully explained.


Include any necessary setup commands or context required to understand the examples.

## How to run?

docker-compose up -d && ./commands.sh

## Connect to Mongo Compass

## mongodb://127.0.0.1:27117,127.0.0.1:27118 (optional)

## Create student to test clustering:

docker-compose exec -it router01 mongosh

use dorm

db.students.insertOne({

    firstName: "John",

    lastName: "Doe",

    DOB: new Date("1995-05-15"),

    gender: "Male",

    nationality: "American",

    emailAddress: "[email protected]",

    phoneNumber: "123-456-7890",

    roomNumber: 101,

    block: "A",

    checkInDate: new Date("2023-01-01"),

    checkOutDate: new Date("2023-06-30"),

    university: "Example University",

    faculty: "Engineering"

});

After that, there will be no records about John Doe in two shard servers

## Try:

docker-compose exec -it shard01-a mongosh

use dorm

db.students.find({ lastName: "Doe" });

exit

docker-compose exec -it shard02-a mongosh

use dorm

db.students.find({ lastName: "Doe" });

exit

docker-compose exec -it shard03-a mongosh

use dorm

db.students.find({ lastName: "Doe" });

exit