Next Wednesday, March-21, 11:00am Pacific Time, Baron and me will be co-presenting with Virident webinar: “How to Turbocharge Your MySQL Performance Using Flash Storage” (From Virident side: Shridar Subramanian and Shirish Jamthe).

Running MySQL on SSD in interesting topic and on the webinar we will cover:

• Configuration and optimization techniques to fully leverage flash-based storage solutions in MySQL environments
• Evaluation criteria and techniques for selecting the suitable flash-storage technology for the relevant MySQL workloads
• Price/performance advantages (ROI) when flash storage is used appropriately for MySQL workloads
• Approaches for scaling MySQL instances on fewer servers while delivering optimal performance using flash drives

The registration is free and …

I have been working with Peter in preparation for the talk comparing the optimizer enhancements in MySQL 5.6 and MariaDB 5.5. We are taking a look at and benchmarking optimizer enhancements one by one. So in the same way this blog post is aimed at a new optimizer enhancement Index Condition Pushdown (ICP). Its available in both MySQL 5.6 and MariaDB 5.5

Now let’s take a look briefly at what this enhancement actually is, and what is it aimed at.

Index Condition Pushdown

Traditional B-Tree index lookups have some limitations in cases such as range scans, where index parts after the part on which range condition is applied cannot be used for filtering records. For example, suppose you have a key defined as:

KEY `i_l_partkey` …

For about the past year I’ve been formulating a series of tools and practices that can provide deep insight into system performance simply by looking at TCP packet headers, and when they arrive and depart from a system. This works for MySQL as well as a lot of other types of systems, because it doesn’t require any of the contents of the packet. Thus, it works without knowledge of what the server and client are conversing about. Packet headers contain only information that’s usually regarded as non-sensitive (IP address, port, TCP flags, etc), so it’s also very easy to get access to this data even in highly secure environments.

I’ve finally written up a paper that shows some of my techniques for detecting problems in a system, which can be an easy way to answer questions such as “is there something we should look into more deeply?” without launching a full-blown analysis project first. It’s available from the white paper …

In this post, I’ll cover the new MySQL monitoring plugins we created for Nagios, and explain their features and intended purpose.

I want to add a little context. What problem were we trying to solve with these plugins? Why yet another set of MySQL monitoring plugins?

The typical problem with Nagios monitoring (and indeed with most other monitoring systems) is the alert spam. I’ve spoken to a lot of users with monitoring systems over the years, and everyone says that they get a lot of false alarms, and that they have email filters set up for alerts. Recently I spoke to one person who gets about thirty thousand alerts per week (!!!) in his email. I’m sure you can see that this makes the monitoring system much less effective. The usual cause of such noisy monitoring is when you alert on things that don’t really indicate problems.

…

DBD::mysql 4.014 breaks pt-table-checksum 2.0.  The cause is unknown, but the effect is a lot of errors like:

DBD::mysql::st execute failed: called with 2 bind variables when 6 are needed [for Statement "..." with ParamValues: ...] at ./pt-table-checksum line 7216.

The fix is simple: upgrade (or even downgrade) DBD::mysql to any version except 4.014. To see which version of DBD::mysql a system has, execute:

perl -MDBD::mysql -e 'print $DBD::mysql::VERSION, "\n";'

This bug may affect other Percona Toolkit tools, but currently pt-table-checksum 2.0 is the only victim. This bug does not affect pt-table-checksum 1.0, and it cannot be worked around in pt-table-checksum 2.0 because the bug in in DBD::mysql.

This bug affects …

In my previous post I explained how it could be possible to recover, on some specific cases, a single table from a full backup in order to save time and make the recovery process more straightforward. Now the scenario is worse because we don’t have a backup or the backup restore process doesn’t work. How can I recover deleted rows?

We’re going to follow the same example as in my previous post so we need to delete the records of the employee 10008 from the table “salaries”. After the “accidental” deletion of rows you should stop MySQL, take a copy of the salaries.ibd and start it again. Later, we’ll extract those deleted rows from the ibd file and import them into the database. The time between the deletion of rows and the database stop is crucial. If pages are reused you can’t recover the …

In response to the release of our new MySQL monitoring plugins on Friday, one commenter asked why the new Nagios plugins don’t use caching. It’s worth answering in a post rather than a comment, because there is an important principle that needs to be understood to monitor servers correctly. But first, some history.

When I wrote a set of high-quality Cacti templates for MySQL a few years ago (which are now replaced by the new project), making the Cacti templates use caching was important for two reasons:

1. Performance. Cacti runs some of its polling processes serially, so if each graph has to reach out to the MySQL server and retrieve a bunch of data, the polling can take too long. I’ve seen cases where a Cacti server that’s graphing too many MySQL servers doesn’t …

We’ve released a new set of monitoring plugins for MySQL servers and related software. With these plugins, you can set up world-class graphing and monitoring for your MySQL servers, using your own on-premises Cacti and Nagios software. The Cacti plugins are derived from an existing set of templates we’ve been using for several years, but the Nagios check plugins are brand new. They are informed by the research we did into the causes and preventions of MySQL downtime.

Like all Percona software, the plugins are open-source and free, licensed under the GNU GPL. The source code and issue tracker are hosted at …

Wouldn’t it be nice if you could get expert advice on your SQL queries to find problems in them, the same way that programmers can use lint-check tools to warn about bugs in their C?

if ( execute = 1 ) {
   launch_missile();
}

Such a simple mistake, but it’s the kind of thing that James Bond movies are made of, isn’t it? Well, a lot of SQL queries have similar bugs, and thanks to Miguel Trias, now there’s a tool to help you find them. This is the second addition to our online suite of tools for MySQL users. You paste a query, it tells you what’s wrong with it. Simple as that.

Find the bug in this query:

select * from t1
   left join t2 using(id)
where t2.created_date < 2012-02-15;

Do you see it? Congratulations! I've analyzed that query with the tool, and shared the results with you. …

So lets say you upgraded from MySQL 5.1 to Percona Server 5.5 and instead of expected performance improvement you see your performance being worse. What should you do ?
First if you followed MySQL upgrade best practices such as testing your workload with pt-upgrade the chances of this happening are rather slim. But lets assume you have not followed these recommendations to the book or some things just slipped through.

First lets talk about what you should not do. You should not panic and go change all kind of configuration options in case you get lucky. Sometimes you do but more often you just waste your time. Instead try to understand what has changed and what exactly changed for worse.

I am speaking about MySQL …