October 30, 2014

PERFORMANCE_SCHEMA vs Slow Query Log

A couple of weeks ago, shortly after Vadim wrote about Percona Cloud Tools and using Slow Query Log to capture the data, Mark Leith asked why don’t we just use Performance Schema instead? This is an interesting question and I think it deserves its own blog post to talk about. First, I would say main […]

Increasing slow query performance with the parallel query execution

MySQL and Scaling-up (using more powerful hardware) was always a hot topic. Originally MySQL did not scale well with multiple CPUs; there were times when InnoDB performed poorer with more  CPU cores than with less CPU cores. MySQL 5.6 can scale significantly better; however there is still 1 big limitation: 1 SQL query will eventually use only […]

Analyzing Slow Query Table in MySQL 5.6

Next week I’m teaching an online Percona Training class, called Analyzing SQL Queries with Percona Toolkit.  This is a guided tour of best practices for pt-query-digest, the best tool for evaluating where your database response time is being spent. This month we saw the GA release of MySQL 5.6, and I wanted to check if any […]

A (prototype) lower impact slow query log

Yesterday, over at my personal blog, I blogged about the impact of the MySQL slow query log. Since we’re working on Percona Server 5.6, I did wonder if this was a good opportunity to re-examine how we could provide slow query log type functionality to our users. The slow query log code inside the MySQL […]

Solving INFORMATION_SCHEMA slowness

Many of us find INFORMATION_SCHEMA painfully slow to work it when it comes to retrieving table meta data. Many people resort to using file system tools instead to find for example how much space innodb tables are using and things like it. Besides being just slow accessing information_schema can often impact server performance dramatically. The […]

A common problem when optimizing COUNT()

When optimizing queries for customers, the first thing I do with a slow query is figure out what it’s trying to do. You can’t fully optimize a query unless you know how to consider alternative ways to write it, and you can’t do that unless you know what the query “means.” I frequently run into […]

COUNT(*) vs COUNT(col)

Looking at how people are using COUNT(*) and COUNT(col) it looks like most of them think they are synonyms and just using what they happen to like, while there is substantial difference in performance and even query result. Lets look at the following series of examples:

Using delayed JOIN to optimize count(*) and LIMIT queries

In many Search/Browse applications you would see main (fact) table which contains search fields and dimension tables which contain more information about facts and which need to be joined to get query result. If you’re executing count(*) queries for such result sets MySQL will perform the join even if you use LEFT JOIN so it […]

COUNT(*) for Innodb Tables

I guess note number one about MyISAM to Innodb migration is warning what Innodb is very slow in COUNT(*) queries. The part which I often however see omitted is fact it only applies to COUNT(*) queries without WHERE clause. So if you have query like SELECT COUNT(*) FROM USER It will be much faster for […]