I'm very happy to announce the release of common_schema, version 1.1 (revision 300).

This version boasts with compelling new features: innovative QueryScript syntax, libraries, views which add to your skills as a DBA, making some maintenance and management tasks a breeze.

• QueryScript, split statement: automagically break long queries into smaller chunks, avoid long locks and reduce query/transaction overhead
• QueryScript, try-catch statement: just try { something; } catch { act_on_error; }.
• killall(): quickly kill connections based on grantee/user/host information.
• profiling/profiling_last: utility views to assist in query

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Even in times of a growing market of specialized NoSQL databases, the relevance of traditional RDBMS doesn't decline. Especially when it comes to the calculation of aggregates based on complex data sets that can not be processed as a batch like Map&Reduce. MySQL is already bringing in a handful of aggregate functions that can be useful for a statistical analysis. The best known of this type are certainly:

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common_schema, revision 178 is now released, with major additions. This revision turns common_schema into a framework, rather than a set of views and functions.

common_schema provides with query scripting, analysis & informational views, and a function library, allowing for easier administration and diagnostics for MySQL. It introduces SQL based tools which simplify otherwise complex shell and client scripts, allowing the DBA to be independent of operating system, installed packages and dependencies.

There's no Perl nor Python, and no dependencies to install. It's just a schema.

Some highlights for the new revision:

• foreach(), aka $(): loop through a collection,

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Have just read MySQL Global status difference using MySQL procedures / functions, by Andres Karlsson. Have commented, but realized I did not provide with a direct answer. In the comment, I suggested checking out a solution based on views, found in common_schema. But the solution in common_schema is split into two views, due to the fact views cannot handle derived tables subqueries.

Well, here's a single query to do that: it checks GLOBAL_STATUS twice, 10 seconds apart in the following sample. It uses SLEEP() to actually wait between the

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Today I have released common_schema, a utility schema for MySQL which includes many views and functions, and is aimed to be installed on any MySQL server.

What does it do?

There are views answering for all sorts of useful information: stuff related to schema analysis, data dimensions, monitoring, processes & transactions, security, internals... There are basic functions answering for common needs.

Some of the views/routines simply formalize those queries we tend to write over and over again. Others take the place of external tools, answering complex questions via SQL and metadata. Still others help out with SQL generation.

Here are a few highlights:

• Did you know you can work out

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The internet really is full of stuff, and we are starting to fill the Clouds with all sorts of software that moves from the serverrooms and in to the clouds. One aspect here that is often missing is what a Cloud environment and the Internet in itself can add to what we already know and have. Or in other words, running in the cloud is not only about lowering costs, and if you look at it by lowering costs by running things in the cloud the same way you used to run it on your private server, then chances are you might not gain anything, running in a cloud is also about having distinct advantages not easily available somewhere else.

Christopher Ahlberg here at Recorded Future just blogged about another way of looking at it: What do we have access to on the internet that is not readily available in the Server room, and the answer is: data. A lot of data.

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Darn! This means oak-show-limits becomes redundant. Am I not supposed to speak about it on my coming presentation? Bad timing!

You have AUTO_INCREMENT columns. How far are you pushing the limits? Are you going to run out of AUTO_INCREMENT values soon? Perhaps you wonder whether you should ALTER from INT to BIGINT?

The answer is all there in INFORMATION_SCHEMA. The TABLES table shows the current AUTO_INCREMENT value per table, and the COLUMNS table tells us all about a column’s data type.

It takes some

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Phew, here we go, this blog post has been long time coming! A few months ago I started toying around with the idea of analyzing the PlanetMySQL public blog feed. It doesn’t take long to extract the data and prepare it for analysis but between lots of work and procrastination this blog post was left unfinished.

It was partly out of pure curiosity and partly the fact that it seemed to me there were less posts than previous years that I decided to trend out the number of posts over the past years and here we go.

The blue line shows the blog posts per month over the past six years and the black line is a polynomial

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The latest release of openark kit introduces oak-hook-general-log, a handy tool which allows for some analysis of executing queries.

Initially I just intended for the tool to be able to dump the general log to standard output, from any machine capable to connect to MySQL. Quick enough, I realized the power it brings.

With this tool, one can dump to standard output all queries using temporary tables; or using a specific index; or doing a full index scan; or just follow up on connections; or… For example, the following execution will only log queries which make for filesort:

oak-hook-general-log --user=root --host=localhost --password=123456

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I’m pleased to announce a new release of the openark kit. There’s a lot of new functionality inside; following is a brief overview.

The openark kit is a set of utilities for MySQL. They solve everyday maintenance tasks, which may be complicated or time consuming to work by hand.

It’s been a while since the last announced release. Most of my attention was on mycheckpoint, building new features, writing documentation etc. However my own use of openark kit has only increased in the past few months, and there’s new useful solutions to common problems that have been developed.

I’ve used and improved many tools over this time, but doing the final cut, along with proper documentation, took

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Just a quick note to let everyone know that our new benchmarking script now supports OSX 10.6 on Intel hardware. That means you can run one simple command and get all of the sequential and random INSERT and SELECT performance statistics about your database performance. As usual the script is open source and released under the new BSD license. Give is a try by downloading now! See the download page for more details.

You can download the first release of the benchmarking script here: http://code.google.com/p/dbbenchmark/

Please read the README file or consult the Support page before running the benchmarks.

I’m further developing a general log hook, which can stream queries from the general log.

A particular direction I’m taking is to filter queries by their type of actions. For example, the tool (oak-hook-general-log) can be instructed to only stream out those queries which involve creation of a temporary table; or those which cause for a filesort, or full index scan, etc.

This is done by evaluating of query execution plans on the fly. I suspect the MySQL query analyzer (http://www.mysql.com/why-mysql/white-papers/mysql_wp_queryanalyzer.php) roughly does the same (as a small part of what it does).

It’s almost nothing one cannot do with sed/awk. However, I bumped into a couple of problems:

The general log (and the

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I’m having my usual fun with charts. Working on mycheckpoint, I’ve generated monitoring charts using the Google Chars API. But I’ve also had chance to experiment and deploy interactive charts, JavaScript based. In particular, I used and tweaked dygraphs.

I’d like to note some differences in using charts of both kinds. And I think it makes a very big difference.

Static charts

I’ll call any image-based chart by “static chart”. It’s just a static image. Example of such charts are those generated by Google Image Charts (they now also have new, interactive charts), or RRDtool. Show below is

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mycheckpoint (see announcement) allows for both graph presentation and quick SQL access to monitored & analyzed data. I’d like to show the power of combining them both.

InnoDB performance

Taking a look at one of the most important InnoDB metrics: the read hit ratio (we could get the same graph by looking at the HTML report):

SELECT innodb_read_hit_percent FROM sv_report_chart_sample \G
*************************** 1. row ***************************
innodb_read_hit_percent:

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I’m proud to announce mycheckpoint, a monitoring utility for MySQL, with strong emphasis on user accessibility to monitored data.

mycheckpoint is a different kind of monitoring tool. It leaves the power in the user’s hand. It’s power is not with script-based calculations of recorded data. It’s with the creation of a view hierarchy, which allows the user to access computed metrics directly.

mycheckpoint is needed first, to deploy a monitoring schema. It may be needed next, so as to INSERT recorded data (GLOBAL STATUS, GLOBAL VARIABLES, MASTER STATUS, SLAVE STATUS) — but this is just a simple INSERT; anyone can do that, even another monitoring tool.

It is then that you do not need it anymore: everything is laid at

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I had a call from a new customer last week. They had issues with their MySQL server. Apparently, it was repeatingly crashing, every few hours. To have their production system kept alive, they used a script to periodically see if MySQL was still alive, and if not – start it.

I was first thinking in directions of old installations; wrong memory allocations (too little memory for large content; to large memory allocation for weak machine). When I reached the customer’s premises, I quickly reviewed general settings, while explaining some basic configuration guidelines. There were peculiarities (e.g. query_cache_limit being larger than query_cache_size), but nothing to obviously suggest a reason for crash.

I then observed the error log. Took some time to find it, since the log_error parameter appeared twice

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A set of useful queries on INFORMATION_SCHEMA follows. These queries can be used when approaching a new database, to learn about some of its properties, or they can be regularly used on an existing schema, so as to verify its integrity.

I will present queries for:

• Checking on database engines and size
• Locating duplicate and redundant indexes
• Checking on character sets for columns and tables, looking for variances
• Checking on processes and long queries (only with MySQL 5.1)

Dimensions

The following query returns the total size per engine per database. For example, it is common that in a given database, all tables are InnoDB. But once in a while, and even though default-engine is set to InnoDB, someone creates a MyISAM table. This may break transactional behavior, or may cause a mysqldump --single-transaction to be ineffective.

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