May 24, 2012

Post: Why you should ignore MySQL's key cache hit ratio

MySQL‘s key cache hit ratio is wrong, even when you hear it from experts. There are two major problems with the key buffer hit ratioHow to choose a key_buffer_size Let’s recap. So far I’ve shown you the fallacy of tuning by ratio

Post: What to tune in MySQL Server after installation

to grow dramatically do not oversize innodb_buffer_pool_size you might findto 512M normally make sense. Check it however after a while and see if it is well used. For certain workloads cache hit ratio

Post: SHOW INNODB STATUS walk through

…and how to use this info to improve MySQL Performance. To… need to look at the log files to findto ensure data makes it to the disk – just passing it to OS cachebuffer pool hit ratio which measures buffer pool efficiency. 1000/1000 corresponds to 100% hit rate. It is hard to tell what buffer pool hit

Post: Shard-Query EC2 images available

to contain the following: #!/bin/bash while [ 1 ] do ./worker >> /dev/null 2>&1 < /dev/null done; Where to findratio(compared to Innodb, 8:1 compared tomysql-inno.sock [mysqld] socket=/tmp/mysql-inno.sock default-storage-engine=INNODB innodb-buffer-pool-instances=2 innodb-buffer

Post: Predicting Performance improvements from memory increase

finding their data in buffer pool so they start to compete on hot latches and performance go down. Now back to original question – howto. Using this approach you also should be careful with your estimations and take IO subsystem into account – even with same cache hit ratio