May 25, 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 [...]

How innodb_open_files affects performance

Recently I looked at table_cache sizing which showed larger table cache does not always provides the best performance. So I decided to look at yet another similar variable – innodb_open_files which defines how many files Innodb will keep open while working in innodb_file_per_table mode. Unlike MyISAM Innodb does not have to keep open file descriptor [...]

table_cache negative scalability

Couple of months ago there was a post by FreshBooks on getting great performance improvements by lowering table_cache variable. So I decided to investigate what is really happening here. The “common sense” approach to tuning caches is to get them as large as you can if you have enough resources (such as memory). With MySQL [...]

MySQL-Memcached or NOSQL Tokyo Tyrant – part 1

All to often people force themselves into using a database like MySQL with no thought into whether if its the best solution to there problem. Why?  Because their other applications use it, so why not the new application?  Over the past couple of months I have been doing a ton of work for clients who [...]

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 [...]

A micro-benchmark of stored routines in MySQL

Ever wondered how fast stored routines are in MySQL? I just ran a quick micro-benchmark to compare the speed of a stored function against a “roughly equivalent” subquery. The idea — and there may be shortcomings that are poisoning the results here, your comments welcome — is to see how fast the SQL procedure code [...]

What time 18446744073709550.000 means

Sometimes when you do profiling you can see number like this in timestamps. Periodically in our patches there was Query_time: 18446744073709550.000 in slow.log file (well, it was fixed recently, but still appears in other places). I faced this problem several years ago when only 2-core AMD Opteron systems appeared and I noticed sysbench getting crazy [...]

Picking datatype for STATUS fields

Quite commonly in the applications you would need to use some kind of “status” field – status of order – “new”, “confirmed”, “in production”, “shipped” status of job, message etc. People use variety of ways to handle them often without giving enough thought to the choice which can cause problems later. Perhaps worst, though quite [...]

Enum Fields VS Varchar VS Int + Joined table: What is Faster?

Really often in customers’ application we can see a huge tables with varchar/char fields, with small sets of possible values. These are “state”, “gender”, “status”, “weapon_type”, etc, etc. Frequently we suggest to change such fields to use ENUM column type, but is it really necessary (from performance standpoint)? In this post I’d like to present [...]