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# ElixirRaft

A learning implementation of the Raft consensus algorithm in Elixir, designed for understanding distributed consensus mechanisms.

## Overview

ElixirRaft is an educational implementation of the Raft consensus protocol, focusing on clarity and understanding rather than production use. It implements core Raft features including:

- Leader election
- Log replication
- Term management
- Cluster membership
- Persistent state management
- Network communication

## Project Structure

```
lib/
├── consensus/                   # Core consensus mechanisms
│   ├── commit_manager.ex         # Manages log commitment
│   ├── message_dispatcher.ex     # Handles message routing
│   └── state_machine.ex          # Applies committed entries
│
├── core/                       # Core Raft components
│   ├── cluster_config.ex        # Cluster membership
│   ├── log_entry.ex            # Log entry structure
│   ├── node_id.ex              # Node identification
│   ├── server_state.ex         # Server state management
│   └── term.ex                 # Term management
│
├── network/                    # Network layer
│   ├── peer.ex                 # Peer connection management
│   ├── tcp_transport.ex        # TCP communication
│   └── transport_behaviour.ex  # Transport interface
│
├── rpc/                       # RPC message definitions
│   └── messages.ex             # Protocol messages
│
├── server/                    # Role implementations
│   ├── candidate.ex            # Candidate role
│   ├── follower.ex            # Follower role
│   ├── leader.ex              # Leader role
│   └── role_behaviour.ex      # Role interface
│
└── storage/                   # Persistence layer
    ├── log_store.ex            # Log storage
    └── state_store.ex          # State persistence
```

## Implementation Details

### Core Components

#### Server Roles
- **Leader**: Handles log replication and heartbeats
- **Follower**: Responds to leader requests and timeouts
- **Candidate**: Manages election process

#### Consensus
- Term-based leadership
- Log replication with consistency checks
- Commit index management
- State machine application

#### Network
- TCP-based peer communication
- Connection management
- Message serialization

#### Storage
- Persistent log storage
- Atomic state updates
- Crash recovery handling

## Testing

The project includes comprehensive tests:

```
test/
├── consensus/                  # Consensus mechanism tests
├── core/                      # Core component tests
├── integration/               # Integration tests
├── network/                   # Network layer tests
├── rpc/                       # Message handling tests
├── server/                    # Role implementation tests
└── storage/                   # Persistence tests
```

To run tests:
```bash
mix test
```

## Quick Start

### Installation

```bash
# Clone repository
git clone https://github.com/ProgMastermind/elixir_raft.git

# Install dependencies
cd elixir_raft
mix deps.get

# Run tests
mix test
```

### Configuration

```elixir
# config/config.exs
config :elixir_raft,
  cluster_size: 3,
  peers: %{
    "node1" => {{127, 0, 0, 1}, 9001},
    "node2" => {{127, 0, 0, 1}, 9002},
    "node3" => {{127, 0, 0, 1}, 9003}
  }
```

## Features Status

✅ Leader Election  
✅ Log Replication  
✅ Safety Guarantees  
✅ Persistent State  
✅ Network Communication  
✅ Membership Changes  
⏳ Log Compaction  
⏳ Client Interaction Layer  
⏳ Metrics/Monitoring

## Contributing

1. Fork the repository
2. Create feature branch (`git checkout -b feature/amazing-feature`)
3. Commit changes (`git commit -m 'Add some amazing feature'`)
4. Push to branch (`git push origin feature/amazing-feature`)
5. Open Pull Request

## Academic Purpose

This implementation prioritizes code clarity and educational value over production readiness. It serves as a learning tool for understanding the Raft consensus algorithm.

## Resources

- [Raft Paper](https://raft.github.io/raft.pdf)
- [Raft Visualization](http://thesecretlivesofdata.com/raft/)
- [Raft Website](https://raft.github.io/)

## Acknowledgments

- Raft authors for the algorithm design
- Elixir community for excellent tooling
- All contributors and reviewers

---
⭐ Star this repository if you find it helpful for learning Raft!

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