The latest release of Percona Monitoring and Management (PMM) 1.8.0 is available as of February 27, 2018.

Percona Monitoring and Management is a free and open-source platform for managing and monitoring MySQL and MongoDB performance. You can run PMM in your own environment for maximum security and reliability. It provides thorough time-based analysis for MySQL and MongoDB servers to ensure that your data works as efficiently as possible.

This release introduces many improvements in the user interface and optimizations of performance.

New landing page

The home page has been removed in favor of the …

The conference session schedule for the seventh annual Percona Live 2018 Open Source Database Conference, taking place April 23-25 at the Santa Clara Convention Center in Santa Clara, CA is now live and available for review! Advance Registration Discounts can be purchased through March 4, 2018, 11:30 p.m. PST.

Percona Live Open Source Database Conference 2018 is the premier open source database event. With a theme of “Championing Open Source Databases,” the conference will feature multiple tracks, including MySQL, MongoDB, Cloud, PostgreSQL, Containers and Automation, Monitoring and Ops, and Database Security. Once again, Percona will be …

How it happened

A few years ago I started thinking about refactoring MySQL-Sandbox. I got lots of ideas and a name for the project (dbdeployer) but went no further. The initial idea (this was 2013!) was to rewrite the project in Ruby: I had been using Ruby at work and it looked like a decent replacement for Perl. My main problem was the difficulty of installation in an uncontrolled environment. If you have control over your environment (it's your laptop or you are in charge of the server configuration via Puppet or similar) then the task is easy. But if you ever need to deploy somewhere with little or no notice, it becomes a problem: there are servers where Perl is not installed, and is common that the server also have a policy forbidding all scripting languages from being deployed. …

In this blog post, we’ll review additional Amazon Aurora MySQL monitoring capabilities we’ve added in Percona Monitoring and Management (PMM) 1.7.0. You can see them in action in the MySQL Amazon Aurora Metrics dashboard.

Amazon Aurora MySQL Transaction Commits

This graph looks at the number of commits the Amazon Aurora engine performed, as well as the average commit latency. As you can see from this graph, latency does not always correlate with the number of commits performed and can be quite high in certain situations.

Amazon Aurora MySQL …

Percona has revealed the line-up of in-depth tutorials for the Percona Live 2018 Open Source Database Conference, taking place April 23-25, 2018 at the Santa Clara Convention Center in Santa Clara, Calif. Secure your spot now with Advanced Registration prices (available until March 4, 2018). Sponsorship opportunities for the conference are still available.

Percona Live 2018 Open Source Database Conference is the premier open source database event. The theme for the upcoming conference is “Championing Open Source Databases,” with a range of topics on …

In this blog post, I’ll present the ProxySQL query cache functionality. This is a query caching mechanism on top of ProxySQL. As there are already many how-tos regarding the ProxySQL prerequisites and installation process, we are going to skip these steps. For those who are already familiar with ProxySQL query cache configuration, let’s go directly to the query rules and the performance results.

Before talking about the ProxySQL query cache, let’s take a look at other caching mechanisms available for MySQL environments.

MySQL query cache is a query caching mechanism – deprecated as of MySQL 5.7.20 and removed in MySQL 8.0 – on top of MySQL itself (based on the official MySQL documentation).

The MySQL query cache stores the text of a SELECT statement together with the corresponding result sent to the client. If an identical statement is …

In this blog post, we’ll introduce how you can look at some experimental Percona Monitoring and Management (PMM) features using Percona Labs builds on GitHub.

Note: PerconaLabs and Percona-QA are open source GitHub repositories for unofficial scripts and tools created by Percona staff. While not covered by Percona support or services agreements, these handy utilities can help you save time and effort.

Percona software builds located in the PerconaLabs and Percona-QA repositories are not officially released software, and also aren’t covered by Percona support or services agreements. 

Percona Monitoring and Management (PMM) is a free and open-source platform for managing and …

In this blog post, I’ll look into four ways MySQL executes GROUP BY. 

In my previous blog post, we learned that indexes or other means of finding data might not be the most expensive part of query execution. For example, MySQL GROUP BY could potentially be responsible for 90% or more of the query execution time. 

The main complexity when MySQL executes GROUP BY is computing aggregate functions in a GROUP BY statement. How this works is shown in the documentation for UDF Aggregate Functions. As we see, the requirement is that UDF functions get all values that constitute the single group one …

In this blog post, we’ll look at ways you can use MySQL 5.7 generated columns (or virtual columns) to improve query performance.

Introduction

About two years ago I published a blog post about Generated (Virtual) Columns in MySQL 5.7. Since then, it’s been one of my favorite features in the MySQL 5.7 release. The reason is simple: with the help of virtual columns, we can create fine-grained indexes that can significantly increase query performance. I’m going to show you some tricks that can potentially fix slow reporting queries with GROUP BY and ORDER BY.

The Problem

Recently I was working with a customer who was struggling with this query:

SELECT
CONCAT(verb, ' - …

In this post, we’ll look at updating and deleting rows with ClickHouse. It’s the second of two parts.

In the first part of this post, we described the high-level overview of implementing incremental refresh on a ClickHouse table as an alternative support for UPDATE/DELETE. In this part, we will show you the actual steps and sample code.

Prepare Changelog Table

First, we create the changelog table below. This can be stored on any other MySQL instance separate from the source of our analytics table. When we run the change capture script, it will record the data on this table that we can consume later with the incremental refresh script:

CREATE TABLE `clickhouse_changelog` (
  `db` varchar(255) NOT NULL …