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On the cluster mailing list (cluster@lists.mysql.com , thread "slow selects") there was recently a very good example of how to optimize queries on Cluster. Thanks to Nick Keefen for raising this problem and Jeff Sturm for the answer how to solve it!

In short the problem is that the Optimizer in the MySQL server does not get adequate statistics from the data nodes about table sizes, indexes etc. This makes the Optimizer clueless in some cases how to order tables in joins, and also in some cases which is the best indexes to use.

So here is the problem that Nick highlighted:

When the tables are stored in MyISAM:
mysql> SELECT v.vid_id, v.vid_title, u.user FROM phpfox_user AS u JOIN phpfox_videos AS v ON(v.vid_userid = u.id) limit 3;
3 rows in set (0.32 sec)

phpfox_user is about 100000 rows and …

HW configuration:

Server A: v20z Server(CPU: 2x2193 Mhz, Memory: 4032 MB)

Server B: x4150 Server(CPU: 8x2826 Mhz, Memory: 16384 MB)

SW configuration:

MySQL5.1.24-rc, MySQL proxy 0.61, Amoeba for MySQL 0.31, DBT2 for MySQL

OS versions: Solaris Nevada snv_91

Test: MySQL DBT2 Test using Amoeba For MySQL

amoeba configuration and query routing rule:

#cat amoeba.xml

<?xml version="1.0" encoding="gbk"?>

<!DOCTYPE amoeba:configuration SYSTEM "amoeba.dtd">

<amoeba:configuration xmlns:amoeba="http://amoeba.meidusa.com/">

<server>

<property name="port">2066</property>

<property …

HW configuration:

Server A: v20z Server(CPU: 2x2193 Mhz, Memory: 4032 MB)

Server B: x4150 Server(CPU: 8x2826 Mhz, Memory: 16384 MB)

SW configuration:

MySQL5.1.24-rc, MySQL proxy 0.61, Amoeba for MySQL 0.31, DBT2 for MySQL

OS versions: Solaris Nevada snv_91

Test: MySQL DBT2 Test using Amoeba For MySQL

amoeba configuration and query routing rule:

#cat amoeba.xml

<?xml version="1.0" encoding="gbk"?>

<!DOCTYPE amoeba:configuration SYSTEM "amoeba.dtd">

<amoeba:configuration xmlns:amoeba="http://amoeba.meidusa.com/">

<server>

<property name="port">2066</property>

<property …

Initiated by a question on the forum I took some time to exercise my Workbench-Scripting-Knowledge. The question was, if it’s possible to do some figure-arrangement/organizing via scripts. To be more precise, the task I had to master was to get tables that have names starting with a given prefix moved into a new layer using scripts.

The function to create a new object - layer in this case - was an easy one. All you have to do is to use the function grtV.newObj(”workbench.model.Layer”). This function returns a handle to the created Layer. Finally, set the visual properties (color, position) and most important, the owner has to be set to the containing Diagram-object. Last step is to add the layer to the “layers” property of the Diagram-object.
The second step, which i put into a separate function, is to ask the user for the prefix to filter the desired tables/objects that should get grouped onto the new layer. Next, loop …

This is the second year for the MySQL User's Conference here in Japan. There is of course a large change from the previous year :)

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Last week I attended an incredibly intense conference in Lalandia, Denmark: Miracle Oracle Open World. According to Mogens Norgaard, the organizer, the conference devotes 80% of the time to intense discussions of Oracle databases and 80% of the time to drinking. During the festivities you get this dim mental image of what it would have been like if Vikings had access to 16-core machines and advanced database software. But I digress.

Anyway, Lalandia is located on just that kind of spare, beautiful coast that clears the mind to look for fundamental truths. And sure enough, a talk by Carel-Jan Engel, nailed one of them: simplicity is the key to availability.

At some level we all …

Few months ago I’ve switched one of our internal projects from doing synchronous database saves of analytics data to an asynchronous processing using starling + a pool of workers. This was the day when I really understood the power of specialized queue servers. I was using database (mostly, MySQL) for this kind of tasks for years and sometimes (especially under a highly concurrent load) it worked not so fast… Few times I worked with some queue servers, but those were either some small tasks or I didn’t have a time to really get the idea, that specialized queue servers were created just to do these tasks quickly and efficiently.

All this time (few months now) I was using starling noticed really bad thing in how it works: if workers die (really die, or lock on something for a long time, or just start lagging) …