One of the interesting features introduced in MySQL 5.7 is that innodb_buffer_pool_size is a dynamic variable (since 5.7.5, to be more specific). Yet, past experience tells us that just because a variable is dynamic, it does not make it is safe to change it on the fly.

To find out how safe this new feature is, I measured throughput on a synthetic workload (sysbench 1.0 running the oltp script) as I made changes to this variable. In this post, I will show the results that came through.

The Environment

For my tests, I used a Google Cloud Compute instance of type n1-standard-4 (that is 4 vCPUs and 15 GB of memory) with 25 GB of persistent …

In this blog, we’ll look at evaluating the performance of an SST data transfer without encryption.

A State Snapshot Transfer (SST) operation is an important part of Percona XtraDB Cluster. It’s used to provision the joining node with all the necessary data. There are three methods of SST operation available: mysqldump, rsync, xtrabackup. The most advanced one – xtrabackup – is the default method for SST in Percona XtraDB Cluster.

We decided to evaluate the current state of xtrabackup, focusing on the process of transferring data between the donor and joiner nodes tp find out if there is any room for improvements or optimizations.

Taking into account that the security of the network connections used for Percona XtraDB Cluster deployment is one of the most important factors that affects SST performance, we will evaluate SST operations in two setups: without network encryption, and in …

In this blog post, I’ll take a look at the performance of the Samsung 960 Pro SSD NVME.

First, I know the Samsung 960 Pro is a consumer SSD NVME drive, not intended for sustained data center workloads. But the AnandTech review looked good enough that I decided to take it for a test spin to see if it would work well with MySQL benchmarks.

Before that, I decided to do a simple sysbench file IO test to see how the drives handled sustained workloads, and if it would start acting up.

My expectation for a consumer SSD drive is that its write consistency will suffer. Many of those drives can sustain high bursts for short periods of time but have to slow down to keep up with write leveling (and other …

The MariaDB subquery cache feature added in MariaDB 5.3 is not widely known. Let’s see what it is and how it works.

What is a subquery cache?

The MariaDB subquery cache optimizes the execution of correlated subqueries. Correlated subqueries refer to a value from the parent query. For example:

SELECT id FROM product WHERE price NOT IN (SELECT MAX(price) FROM product GROUP BY category);

MariaDB only uses this optimization if the parent query is a SELECT, not an UPDATE or a DELETE. The subquery results get cached only for the duration of the parent query.

MariaDB added the subquery cache in v5.3. It is controlled by …

In this blog post, I’ll look for the bottleneck that prevented the performance in my previous post from achieving better results.

The powerful machine I used in the tests in my previous post has a comparatively slow disk, and therefore I expected my tests would hit a point when I couldn’t increase performance further due to the disk speed.

Hardware configuration:

Processors: physical = 4, cores = 72, virtual = 144, hyperthreading = yes
Memory: 3.0T
Disk speed: about 3K …

This procedure can be used to expand an LVM  database volume on Amazon AWS (but also apply to any storage area network environment equally). Let me start with this assumption: when you create volumes for database use in AWS using EBS, you stripe data across them in order to enhance performance.  If you aren't doing this... well, you should :-) Under this assumption, when you need to add more disk space to an existing database volume, you can't just add the disk(s) to the volume, as this would make the added space non striped, and would eventually create hotspots in the dataset. The correct approach in this situation is to create a number of new EBS disks enough to contain entire dataset plus the desired added space,so that you can grow the existing dataset while re-striping properly.
To make this clear, let's suppose you have a dataset volume of  3 TB,  made of 3 1TB EBS volumes which are striped across, but space is running …

In this blog post, we’ll look at Performance Schema benchmarks for OLTP Read/Write workloads.

I am in love with Performance Schema and talk a lot about it. Performance Schema is a revolutionary MySQL troubleshooting instrument, but earlier versions had performance issues. Many of these issues are fixed now, and the default options work quickly and …

Please join Laurynas Biveinis, Percona’s Technical Director – Engineering, on January 25, 2017, at 7 am EST (UTC-8) as he discusses “Percona Server for MySQL 5.7: Key Performance Algorithms.”

In this webinar, Laurynas will discuss selected areas of InnoDB and Percona Server for MySQL 5.7 internals as they relate to buffer pool management and flushing (from a performance and scalability point of view). He will describe the motivation behind the buffer pool mutex split, multi-threaded LRU flusher and parallel doublewrite features in Percona Server for MySQL 5.7, given that MySQL InnoDB 5.7 has re-implemented many of the same features found in Percona Server for MySQL – especially …

In this blog, I’ll look at the impact of swapping on MySQL performance. 

It’s common sense that when you’re running MySQL (or really any other DBMS) you don’t want to see any I/O in your swap space. Scaling the cache size (using

innodb_buffer_pool_size

 in MySQL’s case) is standard practice to make sure there is enough free memory so swapping isn’t needed.   

But what if you make some mistake or miscalculation, and swapping happens? How much does it really impact performance? This is exactly what I set out to investigate.

My test system has the following:

• 32GB of physical memory
• OS (and swap space) on a (pretty old) Intel 520 SSD device
• Database stored on Intel 750 NVMe storage

To simulate a worst case scenario, I’m using Uniform Sysbench Workload:

sysbench …

This blog compares how PostgreSQL and MySQL handle millions of queries per second.

Anastasia: Can open source databases cope with millions of queries per second? Many open source advocates would answer “yes.” However, assertions aren’t enough for well-grounded proof. That’s why in this blog post, we share the benchmark testing results from Alexander Korotkov (CEO of Development, Postgres Professional) and Sveta Smirnova (Principal Technical Services Engineer, Percona). The comparative research of PostgreSQL 9.6 and MySQL 5.7 performance will be especially valuable for environments with multiple databases.

The idea behind this research is to provide an honest comparison for the two popular RDBMSs. Sveta and Alexander wanted to test the most recent versions of both MySQL and PostgreSQL with the same tool, under the same challenging …