MySQL Server Stability

Started by Erredorgat, Nov 20, 2023, 06:56 AM

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ErredorgatTopic starter

Well, the situation is that there is a separate server for mysql, where a single website with relatively low traffic (100k hits per day) operates.



The website itself is quite extensive, containing a lot of logic and separate services, resulting in slow queries. Surprisingly, the database server remains stable for several weeks, but at times it requires the web server to be temporarily stopped for mysql to complete all requests before returning to service.

I wonder how to identify the specific requests or combination of requests that cause the server to go down. Please advise on the methods for doing this.

When inspecting the slow query log and showing the process list, it doesn't provide much insight since there are slow queries that cannot be avoided. However, the server can still function flawlessly with these slow queries for months.
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alexamata

To identify the specific requests or combination of requests that are causing the server to go down, you can utilize several methods to gather more insights into the performance of your MySQL server and the queries it processes.

1. Profiling Queries: Enable the MySQL query profiler to capture performance metrics for individual queries. This can help you identify which queries are consuming the most resources and taking a long time to execute.

2. Query Analysis Tools: Use query analysis tools such as MySQL Query Analyzer or pt-query-digest to analyze the slow query log and identify patterns in the slow-performing queries. You can then focus on optimizing these specific queries to improve overall performance.

3. Performance Schema: Enable the MySQL Performance Schema, which provides a wealth of information about query execution, resource consumption, and wait events. You can use this data to pinpoint the queries or operations that are causing bottlenecks.

4. Monitoring Tools: Implement monitoring tools like Prometheus with the MySQL exporter or Percona Monitoring and Management (PMM) to gather real-time metrics on MySQL's performance, including query throughput, latency, and resource utilization.

5. Query Optimization: Review the structure of the slow queries identified and consider optimizing them by adding indexes, rewriting queries, or restructuring the database schema to improve their performance.

6. Load Testing: Consider using load testing tools to simulate the website's traffic and observe how the database server responds under different levels of load. This can help identify specific usage patterns that lead to performance issues.

7. Query Log Analysis: In addition to the slow query log, analyze the general query log to get a complete picture of all queries being executed. This can help identify not only slow queries but also frequent or repetitive queries that may be contributing to the server load.

8. Connection Pooling and Resource Management: Evaluate the connection pooling and resource allocation settings for the MySQL server. Tuning these parameters can help manage the number of concurrent connections and optimize resource usage, which may alleviate performance issues caused by high traffic.

9. Application Profiling: Consider profiling the application code that interacts with the MySQL database. Sometimes inefficient data retrieval or processing operations in the application layer can lead to excessive database load. Profiling the application can reveal opportunities to optimize data access patterns.

10. Database Sharding or Replication: Depending on the nature of the website and its data access patterns, consider implementing database sharding or replication to distribute the load across multiple servers. This can help improve scalability and mitigate the impact of heavy traffic on a single database server.

11. Database Server Configuration: Review and fine-tune the configuration of the MySQL server, including settings related to memory allocation, query cache, buffer pool size, and other performance-related parameters. Adjusting these settings can have a significant impact on the server's ability to handle traffic spikes and intensive queries.

12. Capacity Planning: Perform a thorough capacity planning exercise to ensure that the hardware resources allocated to the MySQL server, such as CPU, memory, storage, and I/O, are sufficient to handle the expected workload. Scaling up the server resources or considering cloud-based solutions may be necessary to address performance limitations.

By combining these methods and approaches, you can systematically analyze the behavior of the MySQL server under different conditions, identify the root causes of performance degradation, and take targeted steps to optimize the database and application environment for improved stability and responsiveness.
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zexhibitia

I recently found out about this interesting tool called mysqldumpslow. It's really useful as it analyzes the log of slow queries and then displays the most common slow queries. I'm a bit disappointed that I didn't know about it earlier, but now that I do, I'm hopeful that it will assist in solving at least some of the issues we've been experiencing.

There is a lot of potential here for optimizing our database performance, and I'm looking forward to implementing the insights gained from using this tool. It's always exciting to discover new ways to improve efficiency in our systems.
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ken2011lv99

So, what I gathered from what you said is that the database doesn't crash, but rather there's a backlog of requests, right? What exactly are these requests for? Are they for inserting, selecting, or updating data?

Site traffic doesn't seem to have a major impact on the system load. It appears that the performance is heavily influenced by the database structure, its size, and the operations performed on the data within it. It's interesting to note that a single query can potentially overload MySQL for a significant amount of time.

These factors highlight the importance of optimizing database design and query efficiency to ensure smooth system operation, especially during periods of high demand.
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