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 […]
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.
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 […]
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 […]
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 […]
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 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 […]
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 […]
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.
Quite common beginners mistake is not to understand how indexing works and so index all columns used in the queries…. separately. So you end up with table which has say 20 indexes but all single column ones. This can be spotted with a glance view. If you have queries with multiple column restrictions in WHERE […]