Often times, from a computing perspective, one must run a function on a large amount of input. Often times, the same function must be run on many pieces of input, and this is a very expensive process unless the work can be done in parallel. Shard-Query introduces set based processing, which on the surface appears […]
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 […]
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 […]
While many people are familiar with the MySQL EXPLAIN command, fewer people are familiar with “extended explain” which was added in MySQL 4.1 EXPLAIN EXTENDED can show you what the MySQL optimizer does to your query. You might not know this, but MySQL can dramatically change your query before it actually executes it. This process […]
The problem I am going to describe is likely to be around since the very beginning of MySQL, however unless you carefully analyse and profile your queries, it might easily go unnoticed. I used it as one of the examples in our talk given at phpDay.it conference last week to demonstrate some pitfalls one may […]
We have a lot of customers who do click analysis, site analytics, search engine marketing, online advertising, user behavior analysis, and many similar types of work.Â The first thing these have in common is that they’re generally some kind of loggable event. The next characteristic of a lot of these systems (real or planned) is […]
The PBXT Storage Engine (http://www.primebase.com/xt/) is getting stable and we decided to benchmark it in different workloads. This time I tested only READ queries, similar to ones in benchmark InnoDB vs MyISAM vs Falcon (http://www.mysqlperformanceblog.com/2007/01/08/innodb-vs-myisam-vs-falcon-benchmarks-part-1) The difference is I used new sysbench with Lua scripting language, so all queries were scripted for sysbench.
Several days ago MySQL AB made new storage engine Falcon available for wide auditory. We cannot miss this event and executed several benchmarks to see how Falcon performs in comparison to InnoDB and MyISAM. The second goal of benchmark was a popular myth that MyISAM is faster than InnoDB in reads, as InnoDB is transactional, […]