October 23, 2014

COUNT(*) vs COUNT(col)

Looking at how people are using COUNT(*) and COUNT(col) it looks like most of them think they are synonyms and just using what they happen to like, while there is substantial difference in performance and even query result. Lets look at the following series of examples:

Schema Design in MongoDB vs Schema Design in MySQL

For people used to relational databases and doing MySQL database design, using NoSQL solutions such as MongoDB brings interesting challenges. One of them is schema design: while in the relational world, normalization is a good way to start, how should we design our collections when creating a new MongoDB application? Let’s see with a simple […]

MySQL 5.6 vs MySQL 5.5 and the Star Schema Benchmark

So far most of the benchmarks posted about MySQL 5.6 use the sysbench OLTP workload.  I wanted to test a set of queries which, unlike sysbench, utilize joins.  I also wanted an easily reproducible set of data which is more rich than the simple sysbench table.  The Star Schema Benchmark (SSB) seems ideal for this. […]

UDF -vs- MySQL Stored Function

Few days ago I was working on a case where we needed to modify a lot of data before pushing it to sphinx – MySQL did not have a function to do the thing so I thought I’ll write MySQL Stored Function and we’ll be good to go. It worked! But not so well really […]

More on MySQL transaction descriptors optimization

Since my first post on MySQL transaction descriptors optimization introduced in Percona Server 5.5.30-30.2 and a followup by Dimitri Kravchuk, we have received a large number of questions on why the benchmark results in both posts look rather different. We were curious as well, so we tried to answer that question by retrying benchmarks on […]

Identifying the load with the help of pt-query-digest and Percona Server

Overview Profiling, analyzing and then fixing queries is likely the most oft-repeated part of a job of a DBA and one that keeps evolving, as new features are added to the application new queries pop up that need to be analyzed and fixed. And there are not too many tools out there that can make […]

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 […]

Air traffic queries in LucidDB

After my first post Analyzing air traffic performance with InfoBright and MonetDB where I was not able to finish task with LucidDB, John Sichi contacted me with help to setup. You can see instruction how to load data on LucidDB Wiki page You can find the description of benchmark in original post, there I will […]

Analyzing air traffic performance with InfoBright and MonetDB

Accidentally me and Baron played with InfoBright (see http://www.percona.com/blog/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 […]

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 […]