The mistake I commonly see among MySQL users is how indexes are created. Quite commonly people just index individual columns as they are referenced in where clause thinking this is the optimal indexing strategy. For example if I would have something like AGE=18 AND STATE=’CA’ they would create 2 separate indexes on AGE and STATE [...]
3 ways MySQL uses indexes
I often see people confuse different ways MySQL can use indexing, getting wrong ideas on what query performance they should expect. There are 3 main ways how MySQL can use the indexes for query execution, which are not mutually exclusive, in fact some queries will use indexes for all 3 purposes listed here.
Should you move from MyISAM to Innodb ?
There is significant portion of customers which are still using MyISAM when they come to us, so one of the big questions is when it is feasible to move to Innodb and when staying on MyISAM is preferred ? I generally prefer to see Innodb as the main storage engine because it makes life much [...]
How Percona does a MySQL Performance Audit
Our customers or prospective customers often ask us how we do a performance audit (it’s our most popular service). I thought I should write a blog post that will both answer their question, so I can just reply “read all about it at this URL” and share our methodology with readers a little bit. This [...]
JOIN Performance & Charsets
We have written before about the importance of using numeric types as keys, but maybe you’ve inherited a schema that you can’t change or have chosen string types as keys for a specific reason. Either way, the character sets used on joined columns can have a significant impact on the performance of your queries. Take [...]
Multiple column index vs multiple indexes
After my previous post there were questions raised about Index Merge on Multiple Indexes vs Two Column Index efficiency. I mentioned in most cases when query can use both of the ways using multiple column index would be faster but I also went ahead to do some benchmarks today.
How adding another table to JOIN can improve performance ?
JOINs are expensive and it most typical the fewer tables (for the same database) you join the better performance you will get. As for any rules there are however exceptions The one I’m speaking about comes from the issue with MySQL optimizer stopping using further index key parts as soon as there is a range [...]
Missing Data – rows used to generate result set
As Baron writes it is not the number of rows returned by the query but number of rows accessed by the query will most likely be defining query performance. Of course not all row accessed are created equal (such as full table scan row accesses may be much faster than random index lookups row accesses [...]
Learning about MySQL Table Fragmentation
Recently I was working with the customer who need quick warmup – to get Innodb table fetched in memory as fast as possible to get good in memory access performance. To do it I run the query: “SELECT count(*) FROM tbl WHERE non_idx_col=0″ I use this particular form of query because it will do full [...]
The MySQL optimizer, the OS cache, and sequential versus random I/O
In my post on estimating query completion time, I wrote about how I measured the performance on a join between a few tables in a typical star schema data warehousing scenario. In short, a query that could take several days to run with one join order takes an hour with another, and the optimizer chose [...]

