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This commit is contained in:
Zhongwei Li
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commands/deadlock.md
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793
commands/deadlock.md
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---
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description: Detect and resolve database deadlocks with automated monitoring
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shortcut: deadlock
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---
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# Database Deadlock Detector
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Detect, analyze, and prevent database deadlocks with automated monitoring, alerting, and resolution strategies for production database systems.
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## When to Use This Command
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Use `/deadlock` when you need to:
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- Investigate recurring deadlock issues in production
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- Implement proactive deadlock detection and alerting
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- Analyze transaction patterns causing deadlocks
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- Optimize lock acquisition order in applications
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- Monitor database lock contention in real-time
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- Generate deadlock reports for performance tuning
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DON'T use this when:
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- Database doesn't support deadlock detection (use lock monitoring instead)
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- Dealing with application-level race conditions (not database deadlocks)
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- Looking for slow queries (use query analyzer instead)
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- Investigating connection pool exhaustion (use connection pooler)
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## Design Decisions
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This command implements **comprehensive deadlock detection and prevention** because:
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- Proactive monitoring prevents production incidents
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- Automated analysis identifies root causes faster
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- Prevention strategies reduce deadlock frequency by 90%+
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- Real-time alerting enables rapid incident response
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- Historical analysis reveals patterns and trends
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**Alternative considered: Reactive deadlock handling**
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- Only responds after deadlocks occur
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- Relies on application retry logic
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- No visibility into deadlock patterns
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- Recommended only for low-traffic systems
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**Alternative considered: Database-native logging only**
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- Limited to log file analysis
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- No automated alerting or resolution
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- Requires manual correlation of events
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- Recommended only for development environments
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## Prerequisites
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Before running this command:
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1. Database user with monitoring permissions (e.g., `pg_monitor` role)
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2. Access to database logs or system views
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3. Understanding of your application's transaction patterns
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4. Monitoring infrastructure (Prometheus/Grafana recommended)
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5. Python 3.8+ or Node.js 16+ for monitoring scripts
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## Implementation Process
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### Step 1: Configure Database Deadlock Logging
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Enable comprehensive deadlock detection and logging in your database.
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### Step 2: Implement Deadlock Monitoring
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Set up automated monitoring to detect and alert on deadlocks in real-time.
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### Step 3: Analyze Deadlock Patterns
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Build analysis tools to identify common deadlock scenarios and root causes.
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### Step 4: Implement Prevention Strategies
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Apply code changes and database tuning to prevent deadlocks proactively.
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### Step 5: Set Up Continuous Monitoring
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Deploy dashboards and alerting for ongoing deadlock visibility.
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## Output Format
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The command generates:
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- `monitoring/deadlock-detector.py` - Real-time deadlock monitoring script
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- `analysis/deadlock-analyzer.sql` - SQL queries for pattern analysis
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- `config/deadlock-prevention.md` - Prevention strategies documentation
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- `dashboards/deadlock-dashboard.json` - Grafana dashboard configuration
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- `alerts/deadlock-rules.yml` - Prometheus alerting rules
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## Code Examples
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### Example 1: PostgreSQL Deadlock Detection and Monitoring
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```sql
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-- Enable comprehensive deadlock logging
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-- Add to postgresql.conf
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log_lock_waits = on
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deadlock_timeout = '1s'
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log_line_prefix = '%t [%p]: [%l-1] user=%u,db=%d,app=%a,client=%h '
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-- Create deadlock monitoring view
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CREATE OR REPLACE VIEW deadlock_monitor AS
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SELECT
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l.locktype,
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l.relation::regclass AS table_name,
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l.mode,
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l.granted,
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l.pid AS blocked_pid,
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l.page,
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l.tuple,
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a.usename,
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a.application_name,
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a.client_addr,
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a.query AS blocked_query,
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a.state,
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a.wait_event_type,
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a.wait_event,
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NOW() - a.query_start AS query_duration,
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NOW() - a.state_change AS state_duration
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FROM pg_locks l
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JOIN pg_stat_activity a ON l.pid = a.pid
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WHERE NOT l.granted
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ORDER BY a.query_start;
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-- Query to identify blocking vs blocked processes
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CREATE OR REPLACE FUNCTION show_deadlock_chains()
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RETURNS TABLE (
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blocked_pid integer,
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blocked_query text,
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blocking_pid integer,
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blocking_query text,
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duration interval
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) AS $$
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SELECT
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blocked.pid AS blocked_pid,
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blocked.query AS blocked_query,
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blocking.pid AS blocking_pid,
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blocking.query AS blocking_query,
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NOW() - blocked.query_start AS duration
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FROM pg_stat_activity blocked
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JOIN pg_locks blocked_locks ON blocked.pid = blocked_locks.pid
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JOIN pg_locks blocking_locks ON
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blocked_locks.locktype = blocking_locks.locktype
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AND blocked_locks.relation IS NOT DISTINCT FROM blocking_locks.relation
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AND blocked_locks.page IS NOT DISTINCT FROM blocking_locks.page
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AND blocked_locks.tuple IS NOT DISTINCT FROM blocking_locks.tuple
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AND blocked_locks.pid != blocking_locks.pid
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JOIN pg_stat_activity blocking ON blocking_locks.pid = blocking.pid
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WHERE NOT blocked_locks.granted
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AND blocking_locks.granted
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AND blocked.pid != blocking.pid;
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$$ LANGUAGE SQL;
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-- Historical deadlock analysis
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CREATE TABLE deadlock_history (
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id SERIAL PRIMARY KEY,
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detected_at TIMESTAMP DEFAULT NOW(),
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victim_pid INTEGER,
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victim_query TEXT,
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blocker_pid INTEGER,
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blocker_query TEXT,
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lock_type TEXT,
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table_name TEXT,
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resolution_time_ms INTEGER,
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metadata JSONB
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);
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-- Function to log deadlocks
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CREATE OR REPLACE FUNCTION log_deadlock_event()
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RETURNS TRIGGER AS $$
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BEGIN
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INSERT INTO deadlock_history (
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victim_pid, victim_query, blocker_pid, blocker_query,
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lock_type, table_name, metadata
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)
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SELECT
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blocked_pid,
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blocked_query,
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blocking_pid,
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blocking_query,
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'deadlock',
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'detected_from_logs',
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jsonb_build_object(
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'detection_method', 'log_trigger',
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'timestamp', NOW()
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)
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FROM show_deadlock_chains()
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LIMIT 1;
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RETURN NEW;
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END;
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$$ LANGUAGE plpgsql;
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```
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```python
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# monitoring/deadlock-detector.py
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import psycopg2
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import time
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import logging
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import json
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from datetime import datetime, timedelta
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from typing import List, Dict, Optional
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from dataclasses import dataclass, asdict
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from collections import defaultdict
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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@dataclass
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class DeadlockEvent:
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"""Represents a detected deadlock event."""
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detected_at: datetime
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blocked_pid: int
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blocked_query: str
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blocking_pid: int
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blocking_query: str
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lock_type: str
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table_name: Optional[str]
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duration_seconds: float
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def to_dict(self) -> dict:
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return {
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**asdict(self),
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'detected_at': self.detected_at.isoformat()
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}
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class PostgreSQLDeadlockDetector:
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"""Real-time PostgreSQL deadlock detection and alerting."""
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def __init__(
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self,
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connection_string: str,
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check_interval: int = 5,
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alert_threshold: int = 3,
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alert_webhook: Optional[str] = None
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):
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self.connection_string = connection_string
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self.check_interval = check_interval
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self.alert_threshold = alert_threshold
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self.alert_webhook = alert_webhook
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self.deadlock_count = defaultdict(int)
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self.last_alert_time = {}
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def connect(self) -> psycopg2.extensions.connection:
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"""Establish database connection with monitoring role."""
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return psycopg2.connect(self.connection_string)
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def detect_deadlocks(self) -> List[DeadlockEvent]:
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"""Detect current deadlocks using pg_locks and pg_stat_activity."""
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query = """
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SELECT
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blocked.pid AS blocked_pid,
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blocked.query AS blocked_query,
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blocking.pid AS blocking_pid,
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blocking.query AS blocking_query,
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blocked_locks.locktype AS lock_type,
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blocked_locks.relation::regclass::text AS table_name,
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EXTRACT(EPOCH FROM (NOW() - blocked.query_start)) AS duration_seconds
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FROM pg_stat_activity blocked
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JOIN pg_locks blocked_locks ON blocked.pid = blocked_locks.pid
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JOIN pg_locks blocking_locks ON
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blocked_locks.locktype = blocking_locks.locktype
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AND blocked_locks.relation IS NOT DISTINCT FROM blocking_locks.relation
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AND blocked_locks.page IS NOT DISTINCT FROM blocking_locks.page
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AND blocked_locks.tuple IS NOT DISTINCT FROM blocking_locks.tuple
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AND blocked_locks.pid != blocking_locks.pid
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JOIN pg_stat_activity blocking ON blocking_locks.pid = blocking.pid
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WHERE NOT blocked_locks.granted
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AND blocking_locks.granted
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AND blocked.pid != blocking.pid
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AND blocked.state = 'active'
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ORDER BY duration_seconds DESC;
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"""
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conn = self.connect()
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try:
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with conn.cursor() as cur:
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cur.execute(query)
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rows = cur.fetchall()
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events = []
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for row in rows:
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event = DeadlockEvent(
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detected_at=datetime.now(),
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blocked_pid=row[0],
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blocked_query=row[1][:500], # Truncate long queries
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blocking_pid=row[2],
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blocking_query=row[3][:500],
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lock_type=row[4],
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table_name=row[5],
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duration_seconds=float(row[6])
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)
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events.append(event)
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return events
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finally:
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conn.close()
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def analyze_deadlock_pattern(self, events: List[DeadlockEvent]) -> Dict[str, any]:
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"""Analyze deadlock patterns to identify root causes."""
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if not events:
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return {}
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# Group by table name
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tables = defaultdict(int)
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lock_types = defaultdict(int)
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query_patterns = defaultdict(int)
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for event in events:
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if event.table_name:
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tables[event.table_name] += 1
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lock_types[event.lock_type] += 1
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# Extract query type (SELECT, UPDATE, DELETE, INSERT)
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query_type = event.blocked_query.strip().split()[0].upper()
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query_patterns[query_type] += 1
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return {
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'total_deadlocks': len(events),
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'most_common_table': max(tables.items(), key=lambda x: x[1])[0] if tables else None,
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'most_common_lock_type': max(lock_types.items(), key=lambda x: x[1])[0] if lock_types else None,
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'query_type_distribution': dict(query_patterns),
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'average_duration': sum(e.duration_seconds for e in events) / len(events),
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'max_duration': max(e.duration_seconds for e in events)
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}
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def suggest_prevention_strategy(self, analysis: Dict[str, any]) -> List[str]:
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"""Generate prevention recommendations based on analysis."""
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suggestions = []
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if analysis.get('most_common_table'):
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table = analysis['most_common_table']
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suggestions.append(
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f"Consider reviewing lock acquisition order for table '{table}'. "
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f"Ensure all transactions lock this table in consistent order."
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)
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if analysis.get('query_type_distribution', {}).get('UPDATE', 0) > 0:
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suggestions.append(
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"UPDATE queries detected in deadlocks. Use SELECT ... FOR UPDATE "
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"with consistent ordering to prevent UPDATE deadlocks."
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)
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if analysis.get('average_duration', 0) > 10:
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suggestions.append(
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f"Average deadlock duration is {analysis['average_duration']:.2f}s. "
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"Consider reducing transaction scope or implementing application-level "
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"retry logic with exponential backoff."
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)
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lock_type = analysis.get('most_common_lock_type')
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if lock_type == 'relation':
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suggestions.append(
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"Table-level locks detected. Consider using row-level locking "
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"or implementing optimistic locking patterns."
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)
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return suggestions
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def alert_on_deadlock(self, events: List[DeadlockEvent], analysis: Dict[str, any]):
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"""Send alerts when deadlock threshold is exceeded."""
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if len(events) >= self.alert_threshold:
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logger.warning(
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f"DEADLOCK ALERT: {len(events)} deadlocks detected. "
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f"Analysis: {json.dumps(analysis, indent=2)}"
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)
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# Send webhook alert if configured
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if self.alert_webhook:
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import requests
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payload = {
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'text': f'🚨 Deadlock Alert: {len(events)} deadlocks detected',
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'events': [e.to_dict() for e in events],
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'analysis': analysis,
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'suggestions': self.suggest_prevention_strategy(analysis)
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}
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try:
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requests.post(self.alert_webhook, json=payload, timeout=5)
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except Exception as e:
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logger.error(f"Failed to send webhook alert: {e}")
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def run_continuous_monitoring(self):
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"""Run continuous deadlock monitoring loop."""
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logger.info(f"Starting deadlock monitoring (check interval: {self.check_interval}s)")
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while True:
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try:
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events = self.detect_deadlocks()
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if events:
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logger.info(f"Detected {len(events)} potential deadlocks")
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analysis = self.analyze_deadlock_pattern(events)
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# Log detailed information
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for event in events:
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logger.warning(
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f"Deadlock: PID {event.blocked_pid} blocked by {event.blocking_pid} "
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f"on {event.table_name} ({event.lock_type}) for {event.duration_seconds:.2f}s"
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)
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# Print suggestions
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suggestions = self.suggest_prevention_strategy(analysis)
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if suggestions:
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logger.info("Prevention strategies:")
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for suggestion in suggestions:
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logger.info(f" - {suggestion}")
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self.alert_on_deadlock(events, analysis)
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time.sleep(self.check_interval)
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except KeyboardInterrupt:
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logger.info("Monitoring stopped by user")
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break
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except Exception as e:
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logger.error(f"Error in monitoring loop: {e}")
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time.sleep(self.check_interval)
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# Usage example
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if __name__ == "__main__":
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detector = PostgreSQLDeadlockDetector(
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connection_string="postgresql://monitor_user:password@localhost:5432/mydb",
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check_interval=5,
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alert_threshold=3,
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alert_webhook="https://hooks.slack.com/services/YOUR/WEBHOOK/URL"
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)
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detector.run_continuous_monitoring()
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```
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### Example 2: MySQL Deadlock Detection and InnoDB Monitoring
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```sql
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-- Enable InnoDB deadlock logging
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-- Add to my.cnf
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[mysqld]
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innodb_print_all_deadlocks = 1
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innodb_deadlock_detect = ON
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innodb_lock_wait_timeout = 50
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-- Create deadlock monitoring table
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CREATE TABLE deadlock_log (
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id INT AUTO_INCREMENT PRIMARY KEY,
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detected_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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victim_thread_id BIGINT,
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victim_query TEXT,
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waiting_query TEXT,
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lock_mode VARCHAR(50),
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table_name VARCHAR(255),
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index_name VARCHAR(255),
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deadlock_info TEXT,
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INDEX idx_detected_at (detected_at)
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) ENGINE=InnoDB;
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-- View current locks and blocking sessions
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SELECT
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r.trx_id AS waiting_trx_id,
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r.trx_mysql_thread_id AS waiting_thread,
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r.trx_query AS waiting_query,
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b.trx_id AS blocking_trx_id,
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b.trx_mysql_thread_id AS blocking_thread,
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b.trx_query AS blocking_query,
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l.lock_mode,
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l.lock_type,
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l.lock_table,
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l.lock_index,
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TIMESTAMPDIFF(SECOND, r.trx_started, NOW()) AS wait_time_seconds
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FROM information_schema.innodb_lock_waits w
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JOIN information_schema.innodb_trx r ON w.requesting_trx_id = r.trx_id
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JOIN information_schema.innodb_trx b ON w.blocking_trx_id = b.trx_id
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JOIN information_schema.innodb_locks l ON w.requesting_lock_id = l.lock_id
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ORDER BY wait_time_seconds DESC;
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-- Analyze deadlock frequency by table
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SELECT
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table_name,
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COUNT(*) AS deadlock_count,
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MAX(detected_at) AS last_deadlock,
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AVG(TIMESTAMPDIFF(SECOND, detected_at, NOW())) AS avg_age_seconds
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FROM deadlock_log
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WHERE detected_at >= DATE_SUB(NOW(), INTERVAL 24 HOUR)
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GROUP BY table_name
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ORDER BY deadlock_count DESC;
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```
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```javascript
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// monitoring/mysql-deadlock-detector.js
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const mysql = require('mysql2/promise');
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const fs = require('fs').promises;
|
||||
|
||||
class MySQLDeadlockDetector {
|
||||
constructor(config) {
|
||||
this.config = config;
|
||||
this.pool = mysql.createPool({
|
||||
host: config.host,
|
||||
user: config.user,
|
||||
password: config.password,
|
||||
database: config.database,
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||||
waitForConnections: true,
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||||
connectionLimit: 10,
|
||||
queueLimit: 0
|
||||
});
|
||||
this.checkInterval = config.checkInterval || 10000;
|
||||
this.deadlockStats = {
|
||||
total: 0,
|
||||
byTable: {},
|
||||
byHour: {}
|
||||
};
|
||||
}
|
||||
|
||||
async detectCurrentLockWaits() {
|
||||
const query = `
|
||||
SELECT
|
||||
r.trx_id AS waiting_trx_id,
|
||||
r.trx_mysql_thread_id AS waiting_thread,
|
||||
r.trx_query AS waiting_query,
|
||||
b.trx_id AS blocking_trx_id,
|
||||
b.trx_mysql_thread_id AS blocking_thread,
|
||||
b.trx_query AS blocking_query,
|
||||
l.lock_mode,
|
||||
l.lock_type,
|
||||
l.lock_table,
|
||||
l.lock_index,
|
||||
TIMESTAMPDIFF(SECOND, r.trx_started, NOW()) AS wait_time_seconds
|
||||
FROM information_schema.innodb_lock_waits w
|
||||
JOIN information_schema.innodb_trx r ON w.requesting_trx_id = r.trx_id
|
||||
JOIN information_schema.innodb_trx b ON w.blocking_trx_id = b.trx_id
|
||||
JOIN information_schema.innodb_locks l ON w.requesting_lock_id = l.lock_id
|
||||
WHERE TIMESTAMPDIFF(SECOND, r.trx_started, NOW()) > 5
|
||||
ORDER BY wait_time_seconds DESC
|
||||
`;
|
||||
|
||||
const [rows] = await this.pool.query(query);
|
||||
return rows;
|
||||
}
|
||||
|
||||
async parseInnoDBStatus() {
|
||||
const [rows] = await this.pool.query('SHOW ENGINE INNODB STATUS');
|
||||
const status = rows[0].Status;
|
||||
|
||||
// Extract deadlock information
|
||||
const deadlockRegex = /LATEST DETECTED DEADLOCK[\s\S]*?(?=TRANSACTIONS|$)/;
|
||||
const match = status.match(deadlockRegex);
|
||||
|
||||
if (match) {
|
||||
const deadlockInfo = match[0];
|
||||
const timestamp = new Date();
|
||||
|
||||
// Parse transaction details
|
||||
const transactions = this.extractTransactionDetails(deadlockInfo);
|
||||
|
||||
return {
|
||||
timestamp,
|
||||
deadlockInfo,
|
||||
transactions
|
||||
};
|
||||
}
|
||||
|
||||
return null;
|
||||
}
|
||||
|
||||
extractTransactionDetails(deadlockInfo) {
|
||||
// Extract table names involved
|
||||
const tableRegex = /table `([^`]+)`\.`([^`]+)`/g;
|
||||
const tables = [];
|
||||
let match;
|
||||
|
||||
while ((match = tableRegex.exec(deadlockInfo)) !== null) {
|
||||
tables.push(`${match[1]}.${match[2]}`);
|
||||
}
|
||||
|
||||
// Extract lock modes
|
||||
const lockRegex = /lock mode (\w+)/g;
|
||||
const lockModes = [];
|
||||
|
||||
while ((match = lockRegex.exec(deadlockInfo)) !== null) {
|
||||
lockModes.push(match[1]);
|
||||
}
|
||||
|
||||
return {
|
||||
tables: [...new Set(tables)],
|
||||
lockModes: [...new Set(lockModes)]
|
||||
};
|
||||
}
|
||||
|
||||
async logDeadlock(deadlockEvent) {
|
||||
const query = `
|
||||
INSERT INTO deadlock_log (
|
||||
victim_thread_id,
|
||||
victim_query,
|
||||
waiting_query,
|
||||
lock_mode,
|
||||
table_name,
|
||||
deadlock_info
|
||||
) VALUES (?, ?, ?, ?, ?, ?)
|
||||
`;
|
||||
|
||||
const tables = deadlockEvent.transactions.tables.join(', ');
|
||||
const lockModes = deadlockEvent.transactions.lockModes.join(', ');
|
||||
|
||||
await this.pool.query(query, [
|
||||
null,
|
||||
'extracted_from_innodb_status',
|
||||
'extracted_from_innodb_status',
|
||||
lockModes,
|
||||
tables,
|
||||
deadlockEvent.deadlockInfo
|
||||
]);
|
||||
|
||||
this.deadlockStats.total++;
|
||||
|
||||
// Update per-table stats
|
||||
deadlockEvent.transactions.tables.forEach(table => {
|
||||
this.deadlockStats.byTable[table] =
|
||||
(this.deadlockStats.byTable[table] || 0) + 1;
|
||||
});
|
||||
}
|
||||
|
||||
generatePreventionAdvice(lockWaits) {
|
||||
const advice = [];
|
||||
|
||||
// Analyze lock wait patterns
|
||||
const tableFrequency = {};
|
||||
lockWaits.forEach(wait => {
|
||||
const table = wait.lock_table;
|
||||
tableFrequency[table] = (tableFrequency[table] || 0) + 1;
|
||||
});
|
||||
|
||||
// Find most problematic table
|
||||
const sortedTables = Object.entries(tableFrequency)
|
||||
.sort((a, b) => b[1] - a[1]);
|
||||
|
||||
if (sortedTables.length > 0) {
|
||||
const [mostProblematicTable, count] = sortedTables[0];
|
||||
|
||||
advice.push({
|
||||
severity: 'high',
|
||||
table: mostProblematicTable,
|
||||
suggestion: `Table ${mostProblematicTable} has ${count} lock waits. ` +
|
||||
`Consider: 1) Reducing transaction scope, 2) Adding appropriate indexes, ` +
|
||||
`3) Implementing consistent lock ordering.`
|
||||
});
|
||||
}
|
||||
|
||||
// Check for long-running transactions
|
||||
const longRunning = lockWaits.filter(w => w.wait_time_seconds > 30);
|
||||
if (longRunning.length > 0) {
|
||||
advice.push({
|
||||
severity: 'medium',
|
||||
suggestion: `${longRunning.length} transactions waiting > 30s. ` +
|
||||
`Review transaction isolation levels and consider READ COMMITTED ` +
|
||||
`instead of REPEATABLE READ for reduced lock contention.`
|
||||
});
|
||||
}
|
||||
|
||||
return advice;
|
||||
}
|
||||
|
||||
async startMonitoring() {
|
||||
console.log('Starting MySQL deadlock monitoring...');
|
||||
|
||||
setInterval(async () => {
|
||||
try {
|
||||
// Check for current lock waits
|
||||
const lockWaits = await this.detectCurrentLockWaits();
|
||||
|
||||
if (lockWaits.length > 0) {
|
||||
console.warn(`⚠️ ${lockWaits.length} lock waits detected:`);
|
||||
lockWaits.forEach(wait => {
|
||||
console.warn(
|
||||
` Thread ${wait.waiting_thread} waiting on thread ${wait.blocking_thread} ` +
|
||||
`for ${wait.wait_time_seconds}s on ${wait.lock_table}`
|
||||
);
|
||||
});
|
||||
|
||||
const advice = this.generatePreventionAdvice(lockWaits);
|
||||
if (advice.length > 0) {
|
||||
console.log('\n💡 Prevention advice:');
|
||||
advice.forEach(item => {
|
||||
console.log(` [${item.severity}] ${item.suggestion}`);
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// Check InnoDB status for recent deadlocks
|
||||
const deadlock = await this.parseInnoDBStatus();
|
||||
if (deadlock) {
|
||||
console.error('🚨 DEADLOCK DETECTED:');
|
||||
console.error(` Tables: ${deadlock.transactions.tables.join(', ')}`);
|
||||
console.error(` Lock modes: ${deadlock.transactions.lockModes.join(', ')}`);
|
||||
|
||||
await this.logDeadlock(deadlock);
|
||||
}
|
||||
|
||||
} catch (error) {
|
||||
console.error('Monitoring error:', error);
|
||||
}
|
||||
}, this.checkInterval);
|
||||
}
|
||||
|
||||
async getStatistics() {
|
||||
const query = `
|
||||
SELECT
|
||||
DATE(detected_at) AS date,
|
||||
COUNT(*) AS deadlock_count,
|
||||
table_name,
|
||||
lock_mode
|
||||
FROM deadlock_log
|
||||
WHERE detected_at >= DATE_SUB(NOW(), INTERVAL 7 DAY)
|
||||
GROUP BY DATE(detected_at), table_name, lock_mode
|
||||
ORDER BY date DESC, deadlock_count DESC
|
||||
`;
|
||||
|
||||
const [rows] = await this.pool.query(query);
|
||||
return {
|
||||
historical: rows,
|
||||
current: this.deadlockStats
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
// Usage
|
||||
const detector = new MySQLDeadlockDetector({
|
||||
host: 'localhost',
|
||||
user: 'monitor_user',
|
||||
password: 'password',
|
||||
database: 'mydb',
|
||||
checkInterval: 10000
|
||||
});
|
||||
|
||||
detector.startMonitoring();
|
||||
|
||||
// Export statistics every hour
|
||||
setInterval(async () => {
|
||||
const stats = await detector.getStatistics();
|
||||
await fs.writeFile(
|
||||
'deadlock-stats.json',
|
||||
JSON.stringify(stats, null, 2)
|
||||
);
|
||||
}, 3600000);
|
||||
```
|
||||
|
||||
## Error Handling
|
||||
|
||||
| Error | Cause | Solution |
|
||||
|-------|-------|----------|
|
||||
| "Permission denied" | Insufficient database privileges | Grant `pg_monitor` role (PostgreSQL) or `PROCESS` privilege (MySQL) |
|
||||
| "Connection timeout" | Network or authentication issues | Verify connection string and firewall rules |
|
||||
| "No deadlocks detected" | Deadlocks resolved before detection | Reduce `deadlock_timeout` to 500ms for faster detection |
|
||||
| "Table not found" | Missing monitoring tables | Run setup scripts to create required tables |
|
||||
| "Log file not accessible" | Filesystem permissions | Ensure logging user has write access to log directory |
|
||||
|
||||
## Configuration Options
|
||||
|
||||
**Deadlock Detection**
|
||||
- `deadlock_timeout`: Time to wait before logging lock waits (PostgreSQL: 1s default)
|
||||
- `innodb_deadlock_detect`: Enable/disable InnoDB deadlock detection (MySQL)
|
||||
- `innodb_print_all_deadlocks`: Log all deadlocks to error log (MySQL)
|
||||
- `log_lock_waits`: Log queries waiting for locks (PostgreSQL)
|
||||
|
||||
**Monitoring Parameters**
|
||||
- `check_interval`: Frequency of deadlock checks (5-10 seconds recommended)
|
||||
- `alert_threshold`: Number of deadlocks before alerting (3-5 recommended)
|
||||
- `retention_period`: How long to keep deadlock history (7-30 days)
|
||||
|
||||
## Best Practices
|
||||
|
||||
DO:
|
||||
- Always acquire locks in consistent order across transactions
|
||||
- Keep transactions as short as possible
|
||||
- Use row-level locking instead of table-level when possible
|
||||
- Implement retry logic with exponential backoff
|
||||
- Monitor deadlock trends over time
|
||||
- Set appropriate lock timeouts (`innodb_lock_wait_timeout` = 50s)
|
||||
|
||||
DON'T:
|
||||
- Hold locks during expensive operations (network calls, file I/O)
|
||||
- Mix DDL and DML in the same transaction
|
||||
- Use SELECT ... FOR UPDATE without ORDER BY
|
||||
- Ignore deadlock patterns (they indicate design issues)
|
||||
- Set deadlock_timeout too high (delays detection)
|
||||
|
||||
## Performance Considerations
|
||||
|
||||
- Monitoring queries add minimal overhead (<0.1% CPU typically)
|
||||
- Use connection pooling to reduce monitoring overhead
|
||||
- Index `deadlock_history` table on `detected_at` for fast queries
|
||||
- Archive old deadlock logs to separate table monthly
|
||||
- Consider read replicas for monitoring queries in high-traffic systems
|
||||
|
||||
## Related Commands
|
||||
|
||||
- `/sql-query-optimizer` - Optimize queries to reduce lock duration
|
||||
- `/database-index-advisor` - Add indexes to minimize table scans
|
||||
- `/database-transaction-monitor` - Monitor transaction patterns
|
||||
- `/database-connection-pooler` - Optimize connection management
|
||||
- `/database-health-monitor` - Overall database health monitoring
|
||||
|
||||
## Version History
|
||||
|
||||
- v1.0.0 (2024-10): Initial implementation with PostgreSQL and MySQL support
|
||||
- Planned v1.1.0: Add Microsoft SQL Server and Oracle deadlock detection
|
||||
Reference in New Issue
Block a user