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CPU usage in MySQL refers to the proportion of a computer's processor resources that the MySQL server utilizes to execute operations, including processing queries, managing database transactions, and maintaining the database system. In essence, it measures how much of the CPU's computational capacity is dedicated to running MySQL tasks at any given time.
When MySQL CPU usage is very high this can indicate that your database is actively processing a large number of requests or complex queries. On the other hand, consistently low CPU usage might suggest you are underutilizing resources. This can mean there are inefficiencies or bottlenecks elsewhere in the system.
The top command is a generic tool available in Linux and other Unix-like operating systems (like CentOS). It provides a dynamic real-time view of your system's current state, including the CPU usage of all processes.
Look for the mysql process in the list. The %CPU column will show the current CPU usage of your instance of MySQL.
MySQL's SHOW STATUS command is a powerful tool for fetching a wide array of server status information. Although it doesn't directly show CPU usage, it allows you to infer CPU load through various counters and status indicators.
Access your MySQL server through the CLI or a MySQL client.
Run the SHOW STATUS: like 'Threads_%' command.
From the list of server statuses and variables, threads_running and threads_connected are the two most important indicators for gauging CPU usage:
The SHOW PROCESSLIST command provides a real-time snapshot of all active threads within your MySQL server.
The output includes several columns of data for each thread. Pay close attention to the following:
For a more in-depth analysis, MySQL's Performance Schema can be used. It provides detailed information on server events and can be queried to analyze CPU usage per thread or per query.
To enable Performance Schema (if not already enabled):
Execute a query that joins the performance_schema.threads table with the performance_schema.events_statements_summary_by_thread_by_event_name table. This query will provide detailed insights into the CPU usage associated with different threads and queries executed by the server.
A range of external monitoring solutions, including Percona Monitoring and Management (PMM) and Releem, offer in-depth analysis of MySQL's performance metrics, such as CPU utilization.
These tools provide a comprehensive overview of CPU and associated metrics through an intuitive interface, making it far easier to spot trends and issues.
High CPU usage within MySQL databases impacts the performance and dependability of your dependent applications. To effectively diagnose this issue, it is key to thoroughly examine MySQL's operational mechanics, query execution processes, and the broader system environment.
One of the most common causes of high CPU usage is inefficient or complex SQL queries. Queries that lack proper indexing or involve full table scans can cause the database engine to consume excessive CPU cycles. This inefficiency arises because the database has to read more data than necessary, process each row individually, and perform complex calculations without the aid of indexes.
You can configure the Slow Query Log (enable and then set your preferred long query threshold) or use Releem Query Analytics to identify which specific queries are taking too long to finish executing. These are the queries that need your attention.
MySQL is designed to handle multiple connections and transactions simultaneously. However, as the level of concurrency increases, so does the complexity of managing these simultaneous connections. A separate thread handles each active connection. Managing a large number of threads requires more CPU resources, not just for the execution of queries but also for the overhead of context switching between threads.
Lock contention occurs when multiple transactions attempt to access the same data at the same time, leading to a scenario where they must wait for each other to release locks before proceeding. When transactions compete for locks on rows or tables, the database engine spends additional CPU cycles managing these locks.
You can determine if lock contention is occurring by looking at the information_schema.innodb_lock_waits table. Use the following query to identify transactions that are being locked:
SELECT t.trx_id, t.trx_state, t.trx_started, COUNT(distinct w.requesting_trx_id) AS blocked_trxs FROM information_schema.innodb_lock_waits w INNER JOIN information_schema.innodb_trx t ON t.trx_id = w.blocking_trx_id GROUP BY t.trx_id,t.trx_state, t.trx_started ORDER BY t.trx_id;
Long-running transactions can also provide insights into the level of contention within your database. Use the SHOW ENGINE INNODB STATUS command to view a list of all open transactions from newest to oldest. Inspect the oldest transactions to get an idea of how long they are running, which tables and rows are involved, and what statements are involved.
MySQL's performance is highly dependent on its configuration. Parameters that are not optimized for your workload or hardware can lead to inefficient CPU usage. Some key parameters include:
The physical design of the database, including table structures and data types, can also affect CPU efficiency. If you use larger-than-necessary data types (like BIGINT over INT), MySQL processes more data than needed, consuming more CPU resources.
Normalization is a database design technique used to organize tables in a way that reduces data redundancy and improves data integrity. The process involves dividing a database into two or more tables and defining relationships between the tables. While over-normalization can lead to complex joins, under-normalization can result in redundant data processing and larger scans, both of which increase CPU usage.
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