Data nodes are the distributed, sharded storage core of MySQL NDB Cluster. Its data is usually accessed by MySQL Servers (also called SQL nodes in NDB parlance). The MySQL servers each have their own transactional Data Dictionary (DD) where all the metadata describing tables, databases, tablespaces, logfile groups, foreign keys, and other objects are stored for use by MySQL server.…

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There are certain things in life that you can count on …

FOSDEM is back in town, and together with that a new pre-FOSDEM MySQL day, actually 2 days this year!

And of course, we definitely have not forgotten … the MySQL Community dinner!

We continue the by now well known tradition of dining together in style with members from all over the community, and invite you to the ICAB venue (the same location as where the pre-FOSDEM MySQL days are being held.

Book your tickets now!!!

The listed ticket price includes a selection of Belgian …

If you’re using MySQL’s Performance Schema you may use “query digests” as IDs to identify specific query patterns in the events_statements_summary_by_digest Performance Schema Table.

You might assume these hashes are stable between different versions, so, for example, when upgrading from MySQL 5.7 to MySQL 8, you can compare the query response time and other execution details for the same hashes as part of your upgrade process and have confidence that queries run the same (or better) after the upgrade.   Unfortunately, you can’t.

For some reason, the hashing algorithm is different between MySQL 5.6,  MySQL 5.7, and MySQL 8 even for the most trivial queries:

MySQL 5.6

mysql> select digest,digest_text  from events_statements_summary_by_digest where digest_text='commit';
+----------------------------------+-------------+
| digest                           | digest_text | …

With MySQL 8.0 Oracle adopted a new approach to development. Instead of pushing features with major versions, almost every minor MySQL 8.0 version comes with new features or improvements. One of these new features is what we would like to focus on in this blog post. 

Historically MySQL did not come with good tools for provisioning. Sure, you had mysqldump, but it is just a logical backup tool, not really suitable for larger environments. MySQL enterprise users could benefit from MySQL Enterprise Backup while community users could use xtrabackup. Neither of those came with a clean MySQL Community deployments though. It was quite annoying as provisioning is a task you do quite often. You may need to build a new slave, rebuild a failed one - all of this will …

Percona Server for MySQL 8.0.18 ships all functionality to run Group Replication and InnoDB Cluster setups, so I decided to evaluate how it works and how it compares with Percona XtraDB Cluster in some situations.

For this I planned to use three bare metal nodes, SSD drives, and a 10Gb network available for in-between nodes communication, but later I also added tests on three bare metal nodes with NVMe drives and 2x10Gb network cards.

To simplify deployment, I created simple ansible scripts.

Load Data

The first initial logical step is to load data into an empty cluster, so let’s do this with our sysbench-tpcc …

In my last blog post I showed you how to get the entire Percona “Stack” up and running on a Raspberry Pi. This time around, I would like to show the impact on performance between using an SSD hard disk and a standard hard disk.

Disk performance is a key factor in Percona Server for MySQL (or any RDB platform) performance on a Raspberry Pi 4.

Test set up

Each test below was run three times per Hard Disk and I took the best of the three for comparison.

Hardware

• Raspberry Pi 4+ with 4GB ram.
• Disk 1: USB3 Western Digital My Passport Ultra, 1TB
• Disk 2: USB3 KEXIN 240GB Portable External SSD Drive

Hardware stayed consistent …

As on every release MySQL Shell 8.0.19 includes several bug fixes as well as new features. However, this release includes some significant changes:

• Fixes for bugs in the schema definition:  Cascading keys in multi-primary mode.
• Introduction of InnoDB ReplicaSet.

These changes required updates to the metadata schema definition, some of which incompatible with previous versions.…

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If you are reading this blog post, you likely already know the purpose of user-defined functions (UDF) in MySQL. If you need a quick refresher on UDF’s take a look at the MySQL reference manual.  You may have created your own UDFs as well.…

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Just a fun image from running a benchmark in the Oracle Cloud. The image above
shows 6 hours of benchmark run in a data node on a Bare Metal Server. First creating
the disk data tablespaces, next loading the data and finally running the benchmark.

During loading the network was loaded to 1.8 GByte per second, the disks was writing
4 Gbyte per second. During the benchmark run the disks was writing 5 GByte per
second in addition to reading 1.5 Gbyte per second.

All this while CPUs were never loaded to more than 20 percent. Many interesting
things to consider when running benchmarks against modern disk drives.
Bottlenecks can appear in CPUs, in disk drives, in networks and of course it is
possible to create …

In a previous post Profiling Software Using perf and Flame Graphs, we took a look at how to generate Flame Graphs from perf outputs. In this short follow-up, we will use Flame Graphs to process outputs from pt-pmp. Flame Graphs were not originally thought of for this purpose, but since pt-pmp outputs are similar to the folded samples (the result of using stackcollapse-perf.pl), we can take advantage of its functionality.

There are mainly two differences in the pt-pmp outputs:

• The first column is the number of threads with that same backtrace, and
• The function names are separated by a comma instead of a semicolon

Additionally, pt-pmp will print the date in the first line, so we’ll need to trim that part, too.

Lastly, before …