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One Million Tables in MySQL 8.0
In my previous blog post, I talked about new general tablespaces in MySQL 8.0. Recently MySQL 8.0.3-rc was released, which includes a new data dictionary. My goal is to create one million tables in MySQL and test the performance. Background questionsQ: Why million tables in MySQL? Is it even realistic? How does this happen? Usually, millions of tables in MySQL is a result of “a schema per customer
New MariaDB Dashboard in Percona Monitoring and Management Metrics Monitor
In honor of the upcoming MariaDB M17 conference in New York City on April 11-12, we have enhanced Percona Monitoring and Management (PMM) Metrics Monitor with a new MariaDB Dashboard and multiple new graphs! The Percona Monitoring and Management MariaDB Dashboard builds on the efforts of the MariaDB development team to instrument the Aria Storage Engine Status Variables related to Aria Pagecache a
Using MyISAM in production
There were recently number of posts about MyISAM, for example Arjen wrote pretty nice article about MyISAM features so I thought I would share my own view on using MyISAM in production. For me it is not only about table locks. Table locks is only one of MyISAM limitations you need to consider using it in production. Especially if you’re comming from “traditional” databases you’re likely to be shoc
MySQL Sharding with ProxySQL
This article demonstrates how MySQL sharding with ProxySQL works. Recently a colleague of mine asked me to provide a simple example on how ProxySQL performs sharding. In response, I’m writing this short tutorial in the hope it will illustrate ProxySQL’s sharding functionalities, and help people out there better understand how to use it. ProxySQL is a very powerful platform that allows us to manipu
ProxySQL 1.2.1 GA Release
The GA release of ProxySQL 1.2.1 is available. You can get it from https://github.com/sysown/proxysql/releases. There are also Docker images for Release 1.2.1: https://hub.docker.com/r/percona/proxysql/. ProxySQL is a high-performance proxy, currently for MySQL and its forks (like Percona Server and MariaDB). It acts as an intermediary for client requests seeking resources from the database. Proxy
Configuring MySQL For High Number of Connections per Second
One thing I noticed during the observation was that there were roughly 2,000 new connections to MySQL per second during peak times. This is a high number by any account. When a new connection to MySQL is made, it can go into the back_log, which effectively serves as a queue for new connections on operating system size to allow MySQL to handle spikes. Although MySQL connections are quite fast compa
Best Practices for Configuring Optimal MySQL Memory Usage
The 5th column here shows VSZ usage (about 11GB). Note that the VSZ is likely to change over time. It is often a good idea to plot it in your monitoring system and set an alert to ping you when it hits a specified threshold. Don’t allow the mysqld process VSZ exceed 90% of the system memory (and less if you’re running more than just MySQL on the system). It’s a good idea to start on the safe side
Amazon Aurora - Looking Deeper
Recently my colleague (by Percona) Yves Trudeau and colleague (by industry) Marco Tusa published their materials on Amazon Aurora. Indeed, Amazon Aurora is a hot topic these days, and we have a stream of customer inquiries regarding this technology. I’ve decided to form my own opinion, and nothing is better than a personal, hands-on experience, which I am going to share. The materials I will refer
Amazon Aurora in sysbench benchmarks
In my previous post Amazon Aurora – Looking Deeper, I promised benchmark results on Amazon Aurora. Amazon used quite a small dataset in their benchmark: 250 tables, with 25000 rows each, which in my calculation corresponds to 4.5GB worth of data. For this datasize, Amazon used r3.8xlarge instances, which provided 32 virtual CPUs and 244GB of memory. So I can’t say their benchmark is particularly i
OOM relation to vm.swappiness=0 in new kernel
I have recently been involved in diagnosing the reasons behind OOM invocation that would kill the MySQL server process. Of course these servers were primarily running MySQL. As such the MySQL server process was the one with the largest amount of memory allocated. But the strange thing was that in all the cases, there was no swapping activity seen and there were enough pages in the page cache. Iron
Practical Tips for Using MySQL as a Scalable Key-Value Store
All of Percona’s open source software products, in one place, to download as much or as little as you need.
innodb_buffer_pool_size - Is 80% of RAM the right amount?
It seems these days if anyone knows anything about tuning InnoDB, it’s that you MUST tune your innodb_buffer_pool_size to 80% of your physical memory. This is such prolific tuning advice, it seems ingrained in many a DBA’s minds. The MySQL manual to this day refers to this rule, so who can blame the DBA? The question is: does it makes sense? What uses the memory on your server?Before we question
An Introduction to InnoDB Internals
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Congratulations to Our Friends at Oracle with the MySQL 8.0 GA Release!
Percona Delivers MyRocks Storage Engine for MySQL
https://www.percona.com/blog/wp-content/uploads/2014/04/Running-MySQL-on-CentOS-Linux.pdf