With the release of MySQL Enterprise Monitor (MEM) 2.2, there is now the ability to monitor queries using the Query Analyzer (QUAN) without needing the agent proxy to be running. You can use a .NET or JDBC connector plugin to directly gather the query statistics. In the example below, we will use the MySQL Enterprise Plugin for Connector/J.

First, make sure both the Connector/J, the Connector/J plugin and the Apache Commons Logging jars are in the $CLASSPATH. At the time of writing, these are the files needed:

mysql-connector-java-5.1.12-bin.jar
c-java-mysql-enterprise-plugin-1.0.0.42.jar
required/commons-logging-1.1.1.jar

Then, add the plugin to the connection string so that it changes from something like this:

conn = …

I was recently struck by a problem which is unusual. In order to keep an eye on the database server I use nagios, cacti, merlin and some local scripts to monitor the database instance and ensure that it is working properly.  That normally works fine.  The different monitor processes do various things, one of which is to monitor the replication status of a slave, and warn me if the replication is not working or if it’s behind. This is done with the command SHOW SLAVE STATUS.

The server I was looking at runs some large local batch jobs aggregating data. Unfortunately, I was experiencing that replication was interfering with these batch jobs so decided to see if things would perform better if I stopped replication and let the batch …

If you’re in London on Thursday 24th June then there’s a great chance to find out what’s new in MySQL.

Join us for an Oracle MySQL Breakfast Seminar to better understand Oracle’s MySQL strategy and what’s new with MySQL!
Agenda:
09:00 a.m.    Welcome Coffee/Tea
09:30 a.m.    Oracle’s MySQL Strategy
10:00 a.m.    What’s New – The MySQL Server & MySQL Cluster
10.45 a.m.    Coffee/Tea Break
11:00 a.m.    What’s New – MySQL Enterprise & MySQL Workbench
11:45 a.m.    Q&A
12:00 noon    End of the Breakfast Seminar

Cost?
None, it’s a free event! But places are limited and the seminar is held on a first come first served basis, so …

Figure 1. Source Location

In a prior post ( Trace SQL From Database to Source Code ), I showed how to enable SQL trace capabilities for java/MySQL application to trace SQL statements from the database to the exact line of code from which the statement was executed (see Figure 1).  In this post, I’ll enable SQL tracing in the sample C# application, which is included with the MySQL Connector/NET (MySQL’s ADO.NET provider ) install.

The following instructions assume that the MySQL Enterprise Agent and Monitor is already installed.  The Monitor is available for support customers at …

MySQL Cluster 7.1 introduced the ndbinfo database which contains views giving real-time access to a whole host of information that helps you monitor and tune your MySQL Cluster deployment. Because this data can be accessed through regular SQL, various systems can be configured to monitor the Cluster. This post gives one example, extending MySQL Enterprise Monitor to keep an eye on the amount of free memory on the data nodes (through a graph) and then raise an alarm when it starts to run low – even generating SNMP traps if that’s what you need.

One of the features of MySQL Enterprise Monitor is that you can define custom data collectors and that those data collectors can run SQL queries to get the data. The information retrieved by those custom data collectors can then be used with rules that the user defines through the MySQL Enterprise …

A colleague pointed me at More fun with the MySQL Audit Plugin API which looks very interesting.  Analysis of the queries going on inside a msyqld has been something that has been wanted for some time.  Until now it’s only been possible with external addons such as MySQL Enterprise Monitor which do a good job. However, really the place for this functionality is inside the db server itself. If 5.5 m3 provides the hooks to do this that’s great news and while Anders’ first implementation may be simple, this can surely be extended in many ways.

The things I would like to see added to this plugin are the following many of which are safeguards to ensure you can use functionality on a system like this in production without …

You may have read Bernd’s recent post that explained how to try out some new beta functionality for MySQL Cluster and wondered what kind of use you could put the new ndb$info to. ndb$info uses tables/views to give real-time access to a whole host of information that helps you monitor and tune your MySQL Cluster deployment. This article gives one example, extending MySQL Enterprise Monitor to keep an eye on the amount of free memory on the data nodes and then raise an alarm when it starts to run low – even generating SNMP traps if that’s what you need.

One of the features of MySQL Enterprise Monitor is that you can define custom data collectors and that those data collectors can run SQL queries to get the data. The information …

I just wanted to tip my hat to the MySQL Enterprise Tools Engineering team for another great release of the Enterprise Monitor. Not to name names, but I want to give a special thanks to a team that always over delivers on a collective commitment to producing quality software. So, a mega thanks to:

Andy Bang, Sloan Childers, Darren Oldag, Eric Herman, Jan Kneschke, Kay Roepke, Mark Matthews, Bill Weber, Diego Medina, Marcos Palacios, Carsten "Pino" Segieth, Josh Sled, Keith Russell, Mark Leith, Heidi Bergh-Hoff, and Gary Whizin (and also welcome Michael Schuster!)

Yet another great job guys!

The new version, 2.1, was posted as GA early on Tuesday and it is quite possibly the best release of the Enterprise Monitor to date.

For those not familiar with the Enterprise Monitor, it is included in a MySQL Enterprise …

From a performance standpoint, sometimes even tightly tuned queries can cause a performance drag. The common problem here is not one of actual query performance, rather it is a function of:

- the velocity and frequency that a query is submiited for execution
- the total execution time of the aggregated executions

This could be symptomatic of an application not properly configured for caching (see Darren Oldag's blog on this!), or just overall poor design. Regardless of why, when or how we all know it happens. The trouble with this particular problem is that when a query is tuned, or very simple, it is usually not suspect for being a resource hog. Pulling aggregates for number of execs and total exec time for specific queries is a little tricky and labor intensive with the Slow Query Log, and not really a good …

One of the biggest problems I faced as a field DBA was defending my production databases against poorly performing SQL code. Talking to folks at the MySQL UC, during customer visits and trolling the MySQL forums/blogs confirms that this is a common problem and even more challenging when a performance problem pops up during times when no code promotions have taken place.

Traditional/popular way of finding bad SQL code
For MySQL DBAs the challenge to identify and isolate resource intensive SQL code is really two-fold; job #1 is to find the offending code (after that the chore becomes fixing it so it performs, but that is a topic for another post). Most MySQL DBAs have used the MySQL Slow Query Log ("SQ Log") at some point to help with job #1. For those not familiar, the SQ Log is enabled by starting MySQL with --log-slow-queries[=file_name] option. Once enabled the SQ Log captures queries that took longer than X seconds (user …