Do you know how to use MySQL 8 Multiple Data Caches?
In MySQL 8, the InnoDB storage engine introduced the concept of multiple data caches, also known as buffer pool instances.
A buffer pool is a memory area used to cache data pages, and it is used to improve performance by reducing the number of disk I/O operations. In previous versions of MySQL, there was only one buffer pool for the entire instance. However, with multiple buffer pool instances, it is now possible to divide the buffer pool into multiple smaller pools, each with its own dedicated memory area.
Each buffer pool instance is controlled by a separate set of configuration parameters, such as the size of the buffer pool, the number of pages to be flushed per second, and the number of pages to be read per second. This allows for more fine-grained control over the buffer pool and can help to optimize performance for different workloads and usage patterns.
Multiple buffer pool instances can also be used to separate different types of data, such as table data and index data, or to separate data for different schemas or tables. This can help to improve performance by reducing contention for the buffer pool and by allowing the buffer pool to be optimized for different types of data.
You can create multiple buffer pool instances using the innodb_buffer_pool_instances configuration option. This option takes an integer value that specifies the number of buffer pool instances to create.
It’s worth noting that, configuring multiple buffer pool instances may not be beneficial in all cases, and it’s important to monitor performance and usage of the buffer pool instances before and after the change, to ensure that the configuration is optimal for your workload.
Python script to monitor Data Caches in MySQL:
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import pymysql # Connect to the MySQL server connection = pymysql.connect(host='your_host', user='your_user', password='your_password', db='performance_schema') # Create a cursor object cursor = connection.cursor() # Retrieve the buffer pool statistics from the performance_schema.buffer_pool_stats_by_instance table cursor.execute("SELECT * FROM performance_schema.buffer_pool_stats_by_instance") buffer_pool_stats = cursor.fetchall() # Print out the results print("Buffer Pool Instance Statistics:") for i, stats in enumerate(buffer_pool_stats): print(" Instance {}:".format(i)) print(" Pages Data: {}".format(stats[2])) print(" Pages Dirty: {}".format(stats[3])) print(" Pages Free: {}".format(stats[4])) print(" Pages Flushed: {}".format(stats[5])) print(" Pages Read: {}".format(stats[6])) print(" Pages Written: {}".format(stats[7])) # Close the cursor and the connection cursor.close() connection.close() |
This script will print out the buffer pool statistics for each buffer pool instance. The statistics include the number of pages of data, the number of dirty pages, the number of free pages, the number of pages flushed, the number of pages read, and the number of pages written.
You can use this script as a base and add more code to it, like to write the data to a log file, visualize the data with graphs, or send alerts when certain thresholds are met.
It’s important to keep in mind that monitoring data caches is just one aspect of monitoring the performance of your MySQL server, and other metrics such as CPU usage, memory usage, and disk I/O should also be monitored to get a complete picture of your MySQL server’s performance.
You can also use the SHOW STATUS LIKE 'innodb_buffer_pool_%' command to get more information about buffer pool statistics, this command will give you a more detailed view of the buffer pool statistics.
