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Displaying posts with tag: Benchmarks (reset)
Calculating InnoDB Buffer Pool Size for your MySQL Server

What is an InnoDB Buffer Pool?

InnoDB buffer pool is the memory space that holds many in-memory data structures of InnoDB, buffers, caches, indexes and even row-data. innodb_buffer_pool_size is the MySQL configuration parameter that specifies the amount of memory allocated to the InnoDB buffer pool by MySQL. This is one of the most important settings in the MySQL configuration and should be configured based on the available system RAM.

In this post, we’ll walk you through two approaches of setting your InnoDB buffer pool size value, examine the pros and cons of those practices, and also propose a unique method to arrive at an optimum value based on the size of …

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Sneak Peek at Proxytop Utility

In this blog post, I’ll be looking at a new tool Proxytop for managing MySQL topologies using ProxySQL. Proxytop is a self-contained, real-time monitoring tool for ProxySQL. As some of you already know ProxySQL is a popular open source, high performance and protocol-aware proxy server for MySQL and its forks (Percona and MariaDB).

My lab uses MySQL and ProxySQL on Docker containers provided by Nick Vyzas. This lab also uses Alexey Kopytov’s Sysbench utility to perform benchmarking against ProxySQL.

Pre-requisites:

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TPCC-Like Workload for Sysbench 1.0

In this post I’ll look at some of our recent work for benchmark enthusiasts: a TPCC-like workload for Sysbench (version 1.0 or later).

Despite being 25 years old, the TPC-C benchmark can still provide an interesting intensive workload for a database in my opinion. It runs multi-statement transactions and is write-heavy. We also decided to use Sysbench 1.0, which allows much more flexible LUA scripting that allows us to implement TPCC-like workload.

For a long time, we used the tpcc-mysql (https://github.com/Percona-Lab/tpcc-mysql) tool for performance evaluations of MySQL and Percona Server for MySQL, but we recognize that the tool is far from being intuitive and simple to use. So we hope the adaptation for Sysbench will …

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MyISAM and KPTI – Performance Implications From The Meltdown Fix

Recently we had a report from a user who had seen a stunning 90% performance regression after upgrading his server to a Linux kernel with KPTI (kernel page-table isolation – a remedy for the Meltdown vulnerability). A big deal of those 90% was caused by running in an old version of VMware which doesn’t pass […]

The post MyISAM and KPTI – Performance Implications From The Meltdown Fix appeared first on MariaDB.org.

MySQL Performance : my slides from MySQL Day & FOSDEM Feb.2018

As promised, the following are links to slides from my talks during MySQL Day and FOSDEM @Brussels in Feb.2018 :

NOTE : for those who did not follow, CATS is not the only change in InnoDB ;-))

Rgds,
-Dimitri

Percona Database Performance Blog Year in Review: Top Blog Posts

Let’s look at some of the most popular Percona Database Performance Blog posts in 2017.

The closing of a year lends itself to looking back. And making lists. With the Percona Database Performance Blog, Percona staff and leadership work hard to provide the open source community with insights, technical support, predictions and metrics around multiple open source database software technologies. We’ve had over three and a half million visits to the blog in 2017: thank you! We look forward to providing you with even better articles, news and information in 2018.

As 2017 moves into 2018, let’s take a quick look back at some of the most popular posts on the blog this year.

Top 10 Most Read

These posts had the most number of views (working down from the highest):

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Best Practices for Percona XtraDB Cluster on AWS

In this blog post I’ll look at the performance of Percona XtraDB Cluster on AWS using different service instances, and recommend some best practices for maximizing performance.

You can use Percona XtraDB Cluster in AWS environments. We often get questions about how best to deploy it, and how to optimize both performance and spend when doing so. I decided to look into it with some benchmark testing.

For these benchmark tests, I used the following configuration:

  • Region:
    • Availability zones: US East – 1, zones: b, c, d
    • Sysbench 1.0.8
    • ProxySQL 1.4.3
    • 10 tables, 40mln records – ~95GB dataset
    • Percona XtraDB Cluster 5.7.18
    • Amazon Linux AMI

We …

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MySQL Performance: 8.0 re-designed REDO log & ReadWrite Workloads Scalability

This post is following the story of MySQL 8.0 Performance & Scalability started with article about 2.1M QPS obtained on Read-Only workloads. The current story will cover now our progress in Read-Write workloads..
Historically our Read-Only scalability was a big pain, as Read-Only (RO) workloads were often slower than Read-Write (sounds very odd: "add Writes to your Reads to go faster", but this was our reality ;-)) -- and things were largely improved here since MySQL 5.7 where we broke 1M QPS barrier and reached 1.6M QPS for the first time. However, improving Writes or mixed Read+Writes (RW) workloads is a much more complex story..
What are the main scalability show-stoppers …

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MySQL Performance : 2.1M QPS on 8.0-rc

The first release candidate of MySQL 8.0 is here, and I'm happy to share few performance stories about. This article will be about the "most simple" one -- our in-memory Read-Only performance ;-))
However, the used test workload was here for double reasons :


Going ahead to the second point, the main worry about New Sysbench was about its LUA overhead (the previous version 0.5 was running slower than the old one 0.4 due LUA) -- a long story short, I can confirm now that the New Sysbench is running as fast as the oldest "most lightweight" Sysbench binary I have in use ! so, KUDOS Alex !!! ;-)) …

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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 questions

Q: 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” Software as a Service (SaaS) approach. For the purposes of customer data isolation (security) and logical data partitioning (performance), each “customer” has a dedicated schema. You can think of a WordPress hosting service (or any CMS based hosting) where each …

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