Search Results for: order by not using indexes

Using Apache Hadoop and Impala together with MySQL for data analysis

Apache Hadoop is commonly used for data analysis. It is fast for data loads and scalable. In a previous post I showed how to integrate MySQL with Hadoop. In this post I will show how to export a table from  MySQL to Hadoop, load the data to Cloudera Impala (columnar format) and run a reporting […]

Multiple column index vs multiple indexes with MySQL 5.6

A question often comes when talking about indexing: should we use multiple column indexes or multiple indexes on single columns? Peter Zaitsev wrote about it back in 2008 and the conclusion then was that a multiple column index is most often the best solution. But with all the recent optimizer improvements, is there anything different with […]

Using the new spatial functions in MySQL 5.6 for geo-enabled applications

Geo-enabled (or location enabled) applications are very common nowadays and many of them use MySQL. The common tasks for such applications are: Find all points of interests (i.e. coffee shops) around (i.e. a 10 mile radius) the given location (latitude and longitude). For example we want to show this to a user of the mobile […]

Find unused indexes

I wrote one week ago about how to find duplicate indexes. This time we’ll learn how to find unused indexes to continue improving our schema and the overall performance. There are different possibilites and we’ll explore the two most common here. User Statistics from Percona Server and pt-index-usage. User Statistics User Statistics is an improvement […]

Using Flexviews – part one, introduction to materialized views

If you know me, then you probably have heard of Flexviews. If not, then it might not be familiar to you. I’m giving a talk on it at the MySQL 2011 CE, and I figured I should blog about it before then. For those unfamiliar, Flexviews enables you to create and maintain incrementally refreshable materialized […]

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

(There is an updated version of the content in this post by Percona’s Stephane Combaudon available here.) 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 […]