Recently, Dimitri published the results of measuring MySQL 8.0 on Intel Optane storage device. In this blog post, I wanted to look at this in more detail and explore the performance of MySQL 8, MySQL 5.7 and Percona Server for MySQL using a similar set up. The Intel Optane is a very capable device, so I was puzzled that Dimitri chose MySQL options that are either not safe or not recommended for production workloads.

Since we have an Intel Optane in our labs, I wanted to run a similar benchmark, but using settings that we would recommend our customers to use, namely:

• use innodb_checksum
• use innodb_doublewrite
• use binary logs with sync_binlog=1
• enable (by default) Performance …

MySQL stored procedures, functions and triggers are tempting constructs for application developers. However, as I discovered, there can be an impact on database performance when using MySQL stored routines. Not being entirely sure of what I was seeing during a customer visit, I set out to create some simple tests to measure the impact of triggers on database performance. The outcome might surprise you.

Why stored routines are not optimal performance wise: short version

Recently, I worked with a customer to profile the performance of triggers and stored routines. What I’ve learned about stored routines: “dead” code (the code in a branch which will never run) can still significantly slow down the response time of a function/procedure/trigger. We will need to be careful to clean up what we do not need.

Profiling MySQL stored functions

Let’s compare these four simple stored functions (in MySQL 5.7): …

Ever since AMD released their EPYC CPU for servers I wanted to test it, but I did not have the opportunity until recently, when Packet.net started offering bare metal servers for a reasonable price. So I started a couple of instances to test Percona Server for MySQL under this CPU. In this benchmark, I discovered some interesting discrepancies in performance between  AMD and Intel CPUs when running under systemd .

The set up

To test CPU performance, I used a read-only in-memory sysbench OLTP benchmark, as it burns CPU cycles and no IO is performed by Percona Server.

For this benchmark I used Packet.net c2.medium.x86 instances powered by AMD EPYC …

Please join Percona’s Principal Support Escalation Specialist Sveta Smirnova as she presents Troubleshooting Best Practices: Monitoring the Production Database Without Killing Performance on Wednesday, June 27th at 11:00 AM PDT (UTC-7) / 2:00 PM EDT (UTC-4).

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During the MySQL Troubleshooting webinar series, I covered many monitoring and logging tools such as:

• General, slow, audit, binary, error log files
• Performance Schema
• Information Schema
• System …

Please join Percona’s CEO, Peter Zaitsev as he presents Performance Analysis and Troubleshooting Methodologies for Databases on Wednesday, June 13th, 2018 at 11:00 AM PDT (UTC-7) / 2:00 PM EDT (UTC-4).

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Have you heard about the USE Method (Utilization – Saturation – Errors)? RED (Rate – Errors – Duration), or Golden Signals (Latency – Traffic – Errors – Saturations)?

In this presentation, we will talk briefly about these different-but-similar “focuses”. We’ll discuss how we can apply them to data infrastructure performance analysis, troubleshooting, and monitoring.

We will use MySQL as an …

Please join Percona’s Principal Support Escalation Specialist, Sveta Smirnova, as she presents Troubleshooting MySQL Concurrency Issues with Load Testing Tools on Wednesday, May 23, 2018 at 11:00 AM PDT (UTC-7) / 2:00 PM EDT (UTC-4).

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Normally, we use benchmarking tools when we are developing applications. When applications are deployed, benchmarks tests are usually too late to help.

This webinar doesn’t cover actual benchmarks, but it does look at how you can use benchmarking tools for troubleshooting. When you need to repeat a situation caused by concurrent client execution, they can be your best …

In this blog post, I will talk about archiving MySQL tables in ClickHouse for storage and analytics.

Why Archive?

Hard drives are cheap nowadays, but storing lots of data in MySQL is not practical and can cause all sorts of performance bottlenecks. To name just a few issues:

1. The larger the table and index, the slower the performance of all operations (both writes and reads)
2. Backup and restore for terabytes of data is more challenging, and if we need to have redundancy (replication slave, clustering, etc.) we will have to store all the data N times

The answer is archiving old data. Archiving does not necessarily mean that the data will be permanently removed. Instead, the archived data can be placed into long-term storage (i.e., AWS S3) or loaded into a …

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):

…

As a DBA, your top priority is to keep your databases and dependent applications running smoothly at all times. To this end, your best weapon is judicious monitoring of key performance metrics. In a perfect world, you’d want to be up-to-date regarding every aspect of your database’s activity – i.e. how many events occurred, how big they were, precisely when they happened and how long they took.

There certainly is no shortage of tools that can monitor resource consumption, provide instantaneous status snapshots, and generate wait analysis and graphs. The challenge is that some metrics can be expensive to measure, and, perhaps even more importantly, they can require a lot of work to analyze.

The purpose of Part-2 of the blog series is to narrow down the field to those performance metrics that provide the most value for the effort as well as present some tangible ways to capture and study them. It is by tracking the most useful …

Monyog MySQL Monitor v8.3.0 is a feature-rich release which adds a large number of user requests for quick access to relevant monitoring information, for ‘cross-plotting’ multiple servers in a unified chart and more.  Additionally, it adds a number of non-critical bug fixes.

Changes as compared to Monyog MySQL Monitor v8.2.0 include: Features:

Added option to set a distinct email distribution list for warning alerts and critical alerts. Trend Graph Analysis: Added option to group a single metric (which one you find most important) from different servers into one unified chart. This allows you to visually analyse a metric across servers at various points in time.

Choose the monitor group >> Click on the trend graph icon next to the metric as shown below.

Select the trend graph corresponding to the required metric

Monitor single metric across …