New Version of Data Traffic Manager Supports Infinite Application Scalability, a Sleek New Look and Easier-than-Ever Deployment BOSTON – February 12, 2013 — ScaleBase, the company that keeps next gen apps and business-critical databases up-and-running, just released Data Traffic Manager 2.0.  It’s the only database scalability software that solves the three biggest challenges next-gen apps face [...] Read More

Wanting to give away the pass at all costs, Shlomi then published a new post, …

MySQL Tech Tour: From the Web to the Cloud
Thursday, 21 February 2013, Oslo Norway

Are you looking to deploy MySQL-based applications either on-premise or in the cloud?
Join us to learn how you can reduce costs and improve business agility while achieving the highest levels of MySQL scalability, security and uptime.

We will help you better understand:

• Why MySQL has become the leading database in the cloud, and how it addresses the critical attributes of cloud-based deployments
• How ISVs can power their SaaS offerings with MySQL
• What are the best practices to deploy the world’s most popular open source database in public and private clouds

You will also find out:

• How you can leverage MySQL together with Hadoop and other technologies to unlock the value of Big Data, either on-premise or in the …

I had an interesting conversation about table functions in Oracle’s PL/SQL; and the fact that they’re not available in MySQL. When I explained they’re available in Microsoft T-SQL User-Defined Functions (UDFs), my students wanted a small example. One of them said they’d tried to do it but couldn’t get it to work because they found the Microsoft web pages difficult to read and use. Specifically, they didn’t like the sparseness of this one on how to create a function.

Here’s a quick definition of a UDF table function that runs in the studentdb schema (created in this post for migrating SQL Server into a MySQL database). The following getConquistador function takes a single string, which acts to filter the result set …

The log files of any applications (LAMP) like apache, mysql, linux, php  needs to be managed, if they are growing frequently on linux servers. Managing log file efficiently, prevents from high disk space utilization.

Logrotate is one of the functionality, available on all the linux based servers to manage log files. This tool rotates, compresses, and mails system logs

Configuration files: /etc/logrotate.conf

        # see "man logrotate" for details
        # rotate log files weekly
        weekly
        # keep 4 weeks worth of backlogs
        rotate 4
        # create new (empty) log files after rotating old ones
        create
        # uncomment this if you want your log files compressed
        #compress
        # RPM packages drop log rotation information into this directory
        include /etc/logrotate.d
        # no packages own wtmp -- we'll rotate them …

Taking the inspiration of Valeriy Kravchuk great series of blog posts “Fun with Bugs” (and not http://funwithbugs.com/ which is about both caring for and eating bugs), and since I recently went and run Coverity against Drizzle, I thought I’d have a small series of posts on bugs that it has found (and I’ve fixed).

An idea that has been pervasive in the Drizzle project (and one that I rather subscribe to) is that there is two types of correct: correct and obviously correct. Being obviously correct is much, much better than merely being correct.

The first category of problems that Coverity …

As promised, this is the first part of details about MySQL 5.6 vs 5.5 benchmark results I've published earlier last week. The following graphs are representing scalability results obtained for both MySQL versions on the published tests (and I have yet more test results to present to you, but these test's are still running)..

Few remarks based on comments and discussions I've got since then:

• I'm using a "true" 32cores server (true 32 cores, each one yet has 2 threads (HT), so 64 threads in total)
• I'm not using "CPU threads" terminology as I'm finding it confusing (for ex. when you're reading "16 CPU threads" you may not really know if there were 16cores with HT-disabled, or 8cores with HT-enabled)..
• during all the tests I've disabled HT (as it took days and days more to test …

Some time ago, I had to convert all tables of a database from MyISAM to InnoDB on a new server. The plan was to take a logical dump on the master, exporting separately the schema and the data, then edit the CREATE TABLE statements to ensure all tables are created with InnoDB, and reload everything on the new server.

Quite easy, isn’t it? Of course I wanted to run a test first before performing the actions on a live system.

So let’s play with the sakila database.

mysqldump has options to export schema and data separately, let’s use them:

# Export schema
$ mysqldump --no-data sakila > schema.sql

# Export data
$ mysqldump --no-create-info sakila > data.sql

Just to check that everything is fine, let’s reimport the data in a new database:

mysql> CREATE DATABASE sakila2;
Query OK, 1 row affected (0.00 sec)

$ mysql sakila2 < schema.sql 
$ mysql sakila2 < data.sql …

Get the most out of the great new release, MySQL 5.6, by taking the MySQL for Database Administrators training course.

During this 5 day instructor-led course you configure replication between multiple instances, design advanced replication topologies and recover from replication, network, or hardware failure taking advantage of MySQL 5.6 replication performance.

You also gain knowledge on the following:

Set up the Server and Databases

This course teaches you how to install, configure, maintain and tune databases for a wide variety of workloads and environments. You will install and configure MySQL and set appropriate configuration options. You will also connect to the server, using …

Archive can solve disk storage issues – but you must always consider the caveats and bugs related to a storage engine before going ahead and using it.

One of our Remote DBA service clients recently had an issue with size on disk for a particular table; in short this table was some 25 million rows of application audit data with an on disk size of 345GB recorded solely for the purposes of debugging which may or may not occur.

Faced with the task of both reducing the size on disk and ensuring that the data is always available at all times (firmly ruling out off device archive), we began to explore the available options for the client.

We settled on the following options for further testing.

1. InnoDB’s inbuilt row compression
2. MySQL’s …