April 24, 2014

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 […]

Using Flexviews – part two, change data capture

In my previous post I introduced materialized view concepts. This post begins with an introduction to change data capture technology and describes some of the ways in which it can be leveraged for your benefit. This is followed by a description of FlexCDC, the change data capture tool included with Flexviews. It continues with an […]

How many partitions can you have ?

I had an interesting case recently. The customer dealing with large MySQL data warehouse had the table which was had data merged into it with INSERT ON DUPLICATE KEY UPDATE statements. The performance was extremely slow. I turned out it is caused by hundreds of daily partitions created for this table. What is the most […]

Tokyo Tyrant – The Extras Part I : Is it Durable?

You know how in addition to the main movie you have extras on the DVD.  Extra commentary, bloopers, extra scenes, etc? Well welcome the Tyrant extras.  With my previous blog posts I was trying to set-up a case for looking at NOSQL tools, and not meant to be a decision making tool.  Each solution has […]

Analyzing air traffic performance with InfoBright and MonetDB

Accidentally me and Baron played with InfoBright (see http://www.mysqlperformanceblog.com/2009/09/29/quick-comparison-of-myisam-infobright-and-monetdb/) this week. And following Baron’s example I also run the same load against MonetDB. Reading comments to Baron’s post I tied to load the same data to LucidDB, but I was not successful in this. I tried to analyze a bigger dataset and I took public […]

Quick comparison of MyISAM, Infobright, and MonetDB

Recently I was doing a little work for a client who has MyISAM tables with many columns (the same one Peter wrote about recently). The client’s performance is suffering in part because of the number of columns, which is over 200. The queries are generally pretty simple (sums of columns), but they’re ad-hoc (can access […]

Innodb performance gotcha w Larger queries.

Couple of days ago I was looking for a way to improve update performance for the application and I was replacing single value UPDATE with multiple value REPLACE (though I also saw the same problem with INSERT ON DUPLICATE KEY UPDATE) As I went from 1 value to 3 or 10 in the batch performance […]

Just do the math!

One of the most typical reasons for performance and scalability problems I encounter is simply failing to do the math. And these are typically bad one because it often leads to implementing architectures which are not up for job they are intended to solve. Let me start with example to make it clear. Lets say […]

How multiple disks can benefit for single client workload ?

Let us talk few more about disks. You might have read my previous post and Matt’s Reply and it looks like there are few more things to clarify and explain. Before I get to main topic of the article lets comment on IO vs Disk question. If you look at Disk Based databases all data […]

Heikki Tuuri Innodb answers – Part I

Its almost a month since I promised Heikki Tuuri to answer Innodb Questions. Heikki is a busy man so I got answers to only some of the questions but as people still poking me about this I decided to publish the answers I have so far. Plus we may get some interesting follow up questions […]