feat: Implement comprehensive Market Manager with database and logging
- Add complete Market Manager package with in-memory storage and CRUD operations - Implement arbitrage detection with profit calculations and thresholds - Add database adapter with PostgreSQL schema for persistence - Create comprehensive logging system with specialized log files - Add detailed documentation and implementation plans - Include example application and comprehensive test suite - Update Makefile with market manager build targets - Add check-implementations command for verification
This commit is contained in:
Krypto Kajun
173
docs/spec/MARKET_MANAGER_PLAN.md
Normal file
173
docs/spec/MARKET_MANAGER_PLAN.md
Normal file
@@ -0,0 +1,173 @@
|
||||
# Market Manager/BUILDER Planning Document
|
||||
|
||||
## Overview
|
||||
|
||||
This document outlines the plan for implementing a comprehensive Market Manager/BUILDER system for the MEV bot. The system will handle market data collection, storage, and analysis to identify arbitrage opportunities across different DEX protocols on Arbitrum.
|
||||
|
||||
## Core Requirements
|
||||
|
||||
### Data Structure
|
||||
```go
|
||||
type Market struct {
|
||||
Factory common.Address // DEX factory contract address
|
||||
PoolAddress common.Address // Pool contract address
|
||||
Token0 common.Address // First token in pair
|
||||
Token1 common.Address // Second token in pair
|
||||
Fee uint32 // Pool fee (e.g., 500 for 0.05%)
|
||||
Ticker string // Formatted as <symbol>_<symbol> (e.g., "WETH_USDC")
|
||||
RawTicker string // Formatted as <token0>_<token1> (e.g., "0x..._0x...")
|
||||
Key string // <keccak256ofToken0Token1FeeFactoryPoolAddress>
|
||||
}
|
||||
|
||||
// Market storage structure
|
||||
type Markets map[string]map[string]*Market // map[rawTicker]map[marketKey]*Market
|
||||
```
|
||||
|
||||
### Core Functionality
|
||||
|
||||
1. **Market Data Collection**
|
||||
- Parse swap and liquidity events from Arbitrum sequencer
|
||||
- Store data with "possible" status initially
|
||||
- Within 500ms, verify transaction existence on-chain
|
||||
- Update data with confirmed on-chain values
|
||||
|
||||
2. **Market Data Storage**
|
||||
- Cache market data in memory for fast access
|
||||
- Persist data to database for historical analysis
|
||||
- Support data versioning (sequencer vs. on-chain)
|
||||
|
||||
3. **Arbitrage Opportunity Detection**
|
||||
- Iterate through markets by rawTicker
|
||||
- For each rawTicker, examine all associated markets
|
||||
- Sort by price (least to highest)
|
||||
- Check each combination for arbitrage opportunities
|
||||
- Validate profit exceeds threshold (fee1 + fee0 + minArbPct)
|
||||
|
||||
## Implementation Phases
|
||||
|
||||
### Phase 1: Market Data Structure and Storage (Week 1)
|
||||
|
||||
#### 1.1 Core Data Structures
|
||||
- [ ] Implement Market struct with all required fields
|
||||
- [ ] Implement Markets type (map[rawTicker]map[marketKey]*Market)
|
||||
- [ ] Add helper functions for key generation (keccak256 hashing)
|
||||
- [ ] Implement serialization/deserialization for database storage
|
||||
|
||||
#### 1.2 Market Manager Core
|
||||
- [ ] Create MarketManager interface
|
||||
- [ ] Implement in-memory market storage
|
||||
- [ ] Add market CRUD operations (Create, Read, Update, Delete)
|
||||
- [ ] Implement market lookup by various keys (ticker, rawTicker, key)
|
||||
|
||||
#### 1.3 Database Integration
|
||||
- [ ] Design database schema for market data persistence
|
||||
- [ ] Implement database adapter for market storage
|
||||
- [ ] Add data versioning support (sequencer vs. on-chain)
|
||||
- [ ] Implement batch operations for efficient data handling
|
||||
|
||||
### Phase 2: Data Collection and Verification (Week 2)
|
||||
|
||||
#### 2.1 Event Parsing Enhancement
|
||||
- [ ] Extend event parser to handle market-specific data
|
||||
- [ ] Implement swap event parsing with full liquidity data
|
||||
- [ ] Add liquidity event parsing (add/remove liquidity)
|
||||
- [ ] Implement new pool event parsing
|
||||
|
||||
#### 2.2 Sequencer Data Processing
|
||||
- [ ] Implement sequencer data collection pipeline
|
||||
- [ ] Add "possible" status marking for new market data
|
||||
- [ ] Implement timestamp tracking for verification scheduling
|
||||
- [ ] Add data validation before initial storage
|
||||
|
||||
#### 2.3 On-chain Verification
|
||||
- [ ] Implement verification scheduler (500ms window)
|
||||
- [ ] Add Ethereum client integration for transaction verification
|
||||
- [ ] Implement on-chain data retrieval and comparison
|
||||
- [ ] Update market data with confirmed on-chain values
|
||||
|
||||
### Phase 3: Arbitrage Detection Engine (Week 3)
|
||||
|
||||
#### 3.1 Market Iteration and Sorting
|
||||
- [ ] Implement market iteration by rawTicker
|
||||
- [ ] Add price sorting functionality (least to highest)
|
||||
- [ ] Implement efficient market combination generation
|
||||
- [ ] Add performance optimization for large market sets
|
||||
|
||||
#### 3.2 Profit Calculation
|
||||
- [ ] Implement fee calculation for different pool types
|
||||
- [ ] Add price impact modeling for large trades
|
||||
- [ ] Implement profit threshold validation
|
||||
- [ ] Add gas cost estimation for arbitrage transactions
|
||||
|
||||
#### 3.3 Arbitrage Validation
|
||||
- [ ] Implement arbitrage opportunity detection algorithm
|
||||
- [ ] Add multi-hop arbitrage support
|
||||
- [ ] Implement risk assessment for each opportunity
|
||||
- [ ] Add opportunity scoring and ranking
|
||||
|
||||
### Phase 4: Performance Optimization and Testing (Week 4)
|
||||
|
||||
#### 4.1 Caching and Performance
|
||||
- [ ] Implement intelligent caching strategies
|
||||
- [ ] Add cache warming for frequently accessed markets
|
||||
- [ ] Implement cache expiration and cleanup
|
||||
- [ ] Optimize memory usage for large market datasets
|
||||
|
||||
#### 4.2 Testing and Validation
|
||||
- [ ] Implement unit tests for all core functionality
|
||||
- [ ] Add integration tests with mock blockchain data
|
||||
- [ ] Implement performance benchmarks
|
||||
- [ ] Add stress testing for high-volume scenarios
|
||||
|
||||
#### 4.3 Monitoring and Observability
|
||||
- [ ] Add metrics collection for market operations
|
||||
- [ ] Implement logging for key events and errors
|
||||
- [ ] Add health checks for market data freshness
|
||||
- [ ] Implement alerting for critical system issues
|
||||
|
||||
## Technical Considerations
|
||||
|
||||
### Data Consistency
|
||||
- Handle race conditions between sequencer data and on-chain verification
|
||||
- Implement transactional updates for market data
|
||||
- Add conflict resolution for concurrent data modifications
|
||||
|
||||
### Scalability
|
||||
- Design for horizontal scaling across multiple market segments
|
||||
- Implement sharding for large market datasets
|
||||
- Add load balancing for data processing tasks
|
||||
|
||||
### Security
|
||||
- Validate all incoming market data
|
||||
- Implement rate limiting for data collection
|
||||
- Add authentication for market data access
|
||||
- Implement audit logging for all market operations
|
||||
|
||||
## Dependencies
|
||||
|
||||
1. Existing event parsing infrastructure
|
||||
2. Ethereum client libraries for on-chain verification
|
||||
3. Database system for persistence
|
||||
4. Cache system for in-memory storage
|
||||
|
||||
## Success Metrics
|
||||
|
||||
- Market data processing latency < 100ms
|
||||
- On-chain verification success rate > 99%
|
||||
- Arbitrage detection accuracy > 95%
|
||||
- System uptime > 99.9%
|
||||
- Memory usage < 2GB for 10,000 markets
|
||||
|
||||
## Risk Mitigation
|
||||
|
||||
1. **Data Inconsistency**: Implement robust conflict resolution
|
||||
2. **Performance Issues**: Add caching and optimize algorithms
|
||||
3. **Network Failures**: Implement retry mechanisms with exponential backoff
|
||||
4. **Security Breaches**: Add comprehensive input validation and authentication
|
||||
|
||||
## Timeline
|
||||
|
||||
- Week 1: Market Data Structure and Storage
|
||||
- Week 2: Data Collection and Verification
|
||||
- Week 3: Arbitrage Detection Engine
|
||||
- Week 4: Performance Optimization and Testing
|
||||
Reference in New Issue
Block a user