May 18, 2013

A workaround for the performance problems of TEMPTABLE views

MySQL supports two different algorithms for views: the MERGE algorithm and the TEMPTABLE algorithm. These two algorithms differ greatly. A view which uses the MERGE algorithm can merge filter conditions into the view query itself. This has significant performance advantages over TEMPTABLE views. A view which uses the TEMPTABLE algorithm will have to compute the [...]

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 [...]

How number of columns affects performance ?

It is pretty understood the tables which have long rows tend to be slower than tables with short rows. I was interested to check if the row length is the only thing what matters or if number of columns we have to work with also have an important role. I was interested in peak row [...]

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 [...]

Another scalability fix in XtraDB

Recent scalability fixes in InnoDB and also Google’s and your SMP fixes almost made InnoDB results acceptable in primary key lookups queries, but secondary indexes were forgotten for some time. Now having Dell PowerEdge R900 on board (16CPU cores, 16GB RAM) I have some time for experiments, and I played with queries

High-Performance Click Analysis with MySQL

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.  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 [...]

JOIN Performance & Charsets

We have written before about the importance of using numeric types as keys, but maybe you’ve inherited a schema that you can’t change or have chosen string types as keys for a specific reason. Either way, the character sets used on joined columns can have a significant impact on the performance of your queries. Take [...]

Beware of MyISAM Key Cache mutex contention

Today I was working with the client loading data to MyISAM tables at very high rate. Hundreds of millions rows are loaded daily into single MySQL instance with bursts up to 100K of records/sec which need to be inserted (in the table with few indexes). It was good not all records had to go to [...]

Real-Life Use Case for “Barracuda” InnoDB File Format

In one of his recent posts Vadim already gave some information about possible benefits from using new InnoDB file format but in this post I’d like to share some real-life example how compression in InnoDB plugin could be useful for large warehousing tasks.

Testing InnoDB “Barracuda” format with compression

New features of InnoDB – compression format and fast index creation sound so promising so I spent some time to research time and sizes on data we have on our production. The schema of one of shards is