Prior to version 5.0, MySQL could only use one index per table in a given query without any exceptions; folks that didn’t understand this limitation would often have tables with lots of single-column indexes on columns which commonly appeared in their WHERE clauses, and they’d wonder why the EXPLAIN plan for a given SELECT would [...]
Wow. My 6 year old MySQL Bug is finally fixed in MySQL 5.6
I got the message in the morning today about the bug being fixed in MySQL 5.6.6…. which I reported in Early 2006 (while still being with MySQL) and running MySQL 4.1 I honestly thought this issue was fixed long ago as it was indeed pretty annoying. I must say I’m very impressed with Oracle team [...]
A case for MariaDB’s Hash Joins
MariaDB 5.3/5.5 has introduced a new join type “Hash Joins” which is an implementation of a Classic Block-based Hash Join Algorithm. In this post we will see what the Hash Join is, how it works and for what types of queries would it be the right choice. I will show the results of executing benchmarks [...]
Shard-Query turbo charges Infobright community edition (ICE)
Shard-Query is an open source tool kit which helps improve the performance of queries against a MySQL database by distributing the work over multiple machines and/or multiple cores. This is similar to the divide and conquer approach that Hive takes in combination with Hadoop. Shard-Query applies a clever approach to parallelism which allows it to [...]
Flexviews – part 3 – improving query performance using materialized views
Combating “data drift” In my first post in this series, I described materialized views (MVs). An MV is essentially a cached result set at one point in time. The contents of the MV will become incorrect (out of sync) when the underlying data changes. This loss of synchronization is sometimes called drift. This is conceptually [...]
Multi Column indexes vs Index Merge
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.
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.
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 [...]
Multi-Column IN clause – Unexpected MySQL Issue
We have an application which stores massive amount of urls. To save on indexes instead of using URL we index CRC32 of the URL which allows to find matching urls quickly. There is a bit of chance there would be some false positives but these are filtered out after reading the data so it works [...]

