In the article about the role of a primary key, I mentioned that a secondary index in an InnoDB table consists not only of the values of its member columns, but also values of the table’s primary key are concatenated to the index. I.e. the primary key contents is part of every other index.

Assuming the following table structure:

CREATE TABLE `bets` (
  `id` int(10) unsigned NOT NULL,
  `user_id` int(10) unsigned NOT NULL,
  `game_id` int(10) unsigned NOT NULL,
...
  PRIMARY KEY (`id`),
  KEY `user_id` (`user_id`)
) ENGINE=InnoDB

Here is the visualization:

If MySQL could use in queries these implicitly added values, it would maybe allow to save some space on listing the primary key columns at the end of an index explicitly. Let’s check various cases.

Row filtering

In (My)SQL, join is a means for combining records from two tables into a single set which can be either returned as is or used in another join. In order to perform the operation a join has to define the relationship between records in either table, as well as the way it will evaluate the relationship. The relationship itself is created through a set of conditions that are part of the join and usually are put inside ON clause. The rest is determined through a join type, which can either be an inner join or an outer join.

The SQL clauses that set the respective join type in a query are [INNER] JOIN and {LEFT | RIGHT} [OUTER] JOIN. As you can see the actual keywords INNER and OUTER are optional and can be omitted, however outer joins require specifying the direction – either left or right (more on that later).

Examples of queries using …

I’m going to deliver MySQL Training next week (May 21-24) in London.
This is a rare opportunity as I do not personally deliver a lot of Training, especially outside of US. There are still some places left if you want to sign up.

You will also get a signed copy of High Performance MySQL 3rd edition as an attendee.

The MySQL Developer Tools team is announcing the next maintenance release of it’s flagship product, MySQL Workbench, version 5.2.40.
This version contains more than 28 bug fixes applied over version 5.2.39.

MySQL Workbench 5.2 GA

• Data Modeling

• Query

• Administration

Please get your copy from our Download site.

Sources and binary packages are available for several platforms, including Windows, Mac OS X and Linux.

http://dev.mysql.com/downloads/workbench/

Workbench Documentation can be found here.

http://dev.mysql.com/doc/workbench/en/index.html

Utilities Documentation can be found here.
…

The MySQL Developer Tools team is announcing the next maintenance release of it’s flagship product, MySQL Workbench, version 5.2.40. This version contains more than 28 bug fixes applied over version 5.2.39.

MySQL Workbench 5.2 GA

• Data Modeling

• Query

• Administration

Please get your copy from our Download site.

Sources and binary packages are available for several platforms, including Windows, Mac OS X and Linux.

http://dev.mysql.com/downloads/workbench/

Workbench Documentation can be found here.

http://dev.mysql.com/doc/workbench/en/index.html

Utilities Documentation can be found here.
…

Download PDF Presentation

A hardware, software or human failure can occur at any time. Are you prepared?
Many organizations take a risk of serious data loss and system downtime with inadequate procedures in place to support a disaster recovery. This presentation covers the essentials of MySQL backup and recovery options, identifying the necessary tools for an effective strategy to support data resilience and business continuity for your organization. MySQL has no one single unbreakable backup solution, so it is important to understand the impact of MySQL replication, storage engines, configuration options for durability, hardware configuration and the impact on locking and uptime for the various hot/warm/cold options …

I have been working for a customer benchmarking insert performance on Amazon EC2, and I have some interesting results that I wanted to share. I used a nice and effective tool iiBench which has been developed by Tokutek. Though the “1 billion row insert challenge” for which this tool was originally built is long over, but still the tool serves well for benchmark purposes.

OK, let’s start off with the configuration details.

Configuration

First of all let me describe the EC2 instance type that I used.

EC2 Configuration

I chose m2.4xlarge instance as that’s the instance type with highest memory available, and memory is what really really matters.

High-Memory Quadruple Extra Large Instance
68.4 GB of memory
26 EC2 Compute Units (8 virtual cores with 3.25 EC2 Compute …

Dynamic Data Masking is an emerging technology that provides real-time data masking in changing environments, typically in production databases.

GreenSQL Dynamic Data Masking enables you to mask or randomize any sensitive information stored on MS SQL Server, MySQL and PostgreSQL databases.

Register Now!

When? Wednesday, May 23, 2012 (9:00 am PDT; 12:00 pm EST; 16:00 pm GMT; 19:00 pm GMT+3:00)

In this webinar, David Maman, GreenSQL Founder and CTO, will explain:

• What Real-Time Dynamic Data Masking is?
• How to dramatically reduce the risk of a data breach?
• How to better comply with regulations?
• How to enforce real-time …

Tackling machine data on the ground to ensure successful operations for NASA in space

Issues addressed:

• Scaling MySQL to multi-terabytes
• Insertion rates as InnoDB hit a performance wall
• Schema flexibility to handle an evolving data model

The Company:  Southwest Research Institute (SwRI) is an independent, nonprofit applied research and development organization. The staff of more than 3,000 specializes in the creation and transfer of technology in engineering and the physical sciences. Currently, SwRI is part of an international team working on the NASA Magnetospheric Multiscale (MMS) mission. MMS is a Solar Terrestrial Probes mission comprising four identically …

We've recently seen some great announcements of MySQL Cluster delivering amazing results for both selects and updates. The posts (see related articles below) are full of juicy technical details and proofs, but today I'd like to change the perspective a bit. Let's compare those figures with real-world data and imagine what could be done. Please note that I'm not using any scientific method here, just dreaming about the unlimited opportunities offered by MySQL Cluster today.

Cluster can deliver 1B+ selects per minute with 8 nodes …