Today, just like many times before, I needed to configure a monitoring server for MySQL using Cacti and awesome Percona Monitoring Templates. The only difference was that this time I wanted to get it to run with 1 min resolution (using ganglia and graphite, both with 10 sec resolution, for all the rest of our monitoring in Swiftype really spoiled me!). And that’s where the usual pain in the ass Cacti configuration gets really amplified by the million things you need to change to make it work. So, this is a short checklist post for those who need to configure a Cacti server with 1 minute resolution and setup Percona Monitoring Plugins on it.

Configuring Cacti for 60-seconds polling

First of all, we need to take a Cacti server, which by default is configured to do polling …

Here are some things to know about our new Node.JS connector:

• It provides an easy-to-use JavaScript API for data management. Developers write JavaScript, not SQL.

• If the data is stored in MySQL Cluster, that JavaScript is turned into fast NDB API calls sent directly to the NDB data nodes.

• You can also use the connector with data stored in InnoDB or some other engine. In this case, our implementation will generate SQL statements from your API calls and send them to MySQL using node-mysql, the all-JavaScript MySQL client built and maintained by Felix Geisendörfer. But we don’t just generate arbitarary SQL and trust the optimizer to make it work. We know where the indexes are, and we require you to use them.

• Because node.js is still a rapidly moving target, we don’t …

MySQL fulltext search (FTS) is old and well known. It has a simple setup and requires only small changes for querying. For many people it’s more than enough to provide fulltext search. So, here’s the question: why add a new variable – Sphinx – into the system when the database already has the basic functionality? [...]

One very interesting feature, “Compact Backup,” is introduced in Percona XtraBackup 2.1. You can run “compact backups” with the  –compact option, which is very useful for those who have limited disk space to keep the database backup. Now let’s first understand how it works. When we are using –compact option with Innobackupex, it will omit the secondary index pages. This will make the backups more compact and this way they will take less space on disk but the downside of this is, the backup prepare process will take longer time because those secondary index pages will be recreated while preparing the backup. Here, we need to consider couple of things before implement …

Hi Visitor, and welcome to the June 2013 issue of the Open Query Newsletter.

In this issue:

• short news
• MariaDB replacing MySQL
• Galera Synchronous Replication
• Training days
• upcoming events
• tip: FULLTEXT indexing or SPHINX

read more

Hi,

We are excited to announce that we just released a new stable version of XAMPP that includes PHP 5.4

http://www.apachefriends.org/xampp.html

This version of XAMPP includes the following improvements:

• Updated main components PHP to 5.4.16, MySQL to 5.5.32, Apache to 2.4.4, phpMyAdmin 4.0.4
• Updated Linux and Mac OS X versions of XAMPP, which had not been updated for a while. Moving forward, we aim to keep them up to date and perform releases at the same time as the Windows version.
• Updated the XAMPP Control Panel to 3.2.1 for Windows
• New manager tools for Linux and OS X that allows starting / stopping servers using a GUI interface.
• New GUI installers for Linux and OS X that match the Windows GUI installer.
• Support for 64bit versions of Linux and OS X.
• Expanded …

This is hypothetical. What would happen if I did the following? alter table mysql.user add unique key(User); I’m tossing this out there for people to think about because I’ve always thought that MySQL’s authentication model is a nuisance: MySQL considers both your host name and user name in identifying you because there is no reason to assume that a given user name belongs to the same person on all hosts.

I’ve posted slides for my Velocity talk on VividCortex’s blog. The talk explained how we use exponentially weighted moving statistics to generate a meta-metric of abnormality for the time-series metrics measured from MySQL. That’s kind of a mouthful. Maybe you had to be there :-)

One of the challenges of big data is that it is, well, big. Computers are optimized for math on 64 bits or less. Any bigger, and extra steps have to be taken to work with the data which is very expensive. This is why a BIGINT is 64 bits.  In MySQL DECIMAL can store more than 64 bits of data using fixed precision.  Large numbers can use FLOAT or DECIMAL but those data types are lossy.

DECIMAL is an expensive encoding. Fixed precision math is expensive and you eventually run out of precision at which point you can't store any more data, right?

What happens when you want to store a counter that is bigger than the maximum DECIMAL?  FLOAT is lossy.  What if you need an /exact/ count of a very big number without using very much space?

I've developed an encoding method that allows you to store very large counters in a very small amount of space. It takes advantage of the fact that counters …

One of the challenges of big data is that it is, well, big. Computers are optimized for math on 64 bits or less. Any bigger, and extra steps have to be taken to work with the data which is very expensive. This is why a BIGINT is 64 bits.  In MySQL DECIMAL can store more than 64 bits of data using fixed precision.  Large numbers can use FLOAT or DECIMAL but those data types are lossy.

DECIMAL is an expensive encoding. Fixed precision math is expensive and you eventually run out of precision at which point you can't store any more data, right?

What happens when you want to store a counter that is bigger than the maximum DECIMAL?  FLOAT is lossy.  What if you need an /exact/ count of a very big number without using very much space?

I've developed an encoding method that allows you to store very large counters in a very small amount of space. It takes advantage of the fact that counters …