Mastering MySQL Performance: Advanced Counters and Linux Metrics with Expert Scripts

Shiv IyerShiv Iyer
2 min read

Advanced performance counters in MySQL, coupled with Linux metrics, provide a comprehensive view necessary for effective performance troubleshooting. Incorporating advanced scripts enhances this process, allowing for more automated, detailed analysis. Here are some advanced performance counters and Linux metrics, along with commented advanced scripts, that are crucial in MySQL performance troubleshooting:

MySQL Advanced Performance Counters

1. InnoDB Metrics

  • Script for Buffer Pool Usage:
  -- Shows InnoDB buffer pool usage details
 SELECT
    page_number, page_type,
    flush_type, IO_FIX, FIX_COUNT
FROM information_schema.innodb_buffer_page;

2. Threads Metrics

  • Script for Threads Analysis:
  -- Analyze threads connected and running
  SHOW STATUS LIKE 'Threads%';

3. Query Execution Metrics

  • Script for Slow Queries:
  -- Fetch count of slow queries
  SHOW GLOBAL STATUS LIKE 'Slow_queries';

4. Replication Metrics

  • Script for Replication Lag:
  -- Check replication delay
  SHOW SLAVE STATUS\G

Linux System Metrics

1. CPU Usage

  • Script for CPU Utilization:
  #!/bin/bash
  # Displays CPU usage
  top -bn1 | grep load

2. Memory Usage

  • Script for Memory Check:
  #!/bin/bash
  # Check free and used memory
  free -m

3. Disk I/O Metrics

  • Script for Disk I/O:
  #!/bin/bash
  # Display I/O statistics
  iostat -mx

4. Network Metrics

  • Script for Network Throughput:
  #!/bin/bash
  # Network throughput check
  iftop

Advanced Monitoring Scripts

  • MySQL Performance Schema Analysis:
  -- Query Performance Schema for detailed metrics
  SELECT * FROM performance_schema.events_statements_summary_by_digest
  ORDER BY SUM_TIMER_WAIT DESC LIMIT 10;
  • Advanced System Monitoring:
  #!/bin/bash
  # Detailed system performance monitoring
  vmstat 1 10
  sar -u 1 10

Conclusion

Utilizing advanced performance counters and Linux metrics, combined with insightful scripts, offers a powerful approach to diagnosing and resolving performance issues in MySQL environments. Regular monitoring with these tools and scripts can lead to early detection of potential problems and more efficient database operations, ultimately contributing to the overall health and performance of the MySQL server.

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Written by

Shiv Iyer
Shiv Iyer

Over two decades of experience as a Database Architect and Database Engineer with core expertize in Database Systems Architecture/Internals, Performance Engineering, Scalability, Distributed Database Systems, SQL Tuning, Index Optimization, Cloud Database Infrastructure Optimization, Disk I/O Optimization, Data Migration and Database Security. I am the founder CEO of MinervaDB Inc. and ChistaDATA Inc.