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Displaying posts with tag: mysql-and-variants (reset)
Attack No-PK Replication Lag with MySQL/Percona Server 8 Invisible Columns!

The most common issue when using row-based replication (RBR) is replication lag due to the lack of Primary keys.

The problem is that any replicated DML will do a full table scan for each modified row on the replica. This bug report explains it more in-depth: https://bugs.mysql.com/bug.php?id=53375

For example, if a delete is executed on the following table definition:

CREATE TABLE `joinit` (
  `i` int NOT NULL,
  `s` varchar(64) DEFAULT NULL,
  `t` time NOT NULL,
  `g` int NOT NULL
) ENGINE=InnoDB DEFAULT CHARSET=latin1

 

With this amount of rows:

mysql> select count(*) from joinit;
+----------+
| count(*) |
+----------+
|  1048576 |
+----------+

 

The delete being:

mysql> flush status ;

mysql> delete from joinit where i > 5 and i < 150;
Query OK, 88 rows affected (0.04 sec) …
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Comparing Graviton (ARM) Performance to Intel and AMD for MySQL (Part 3)

Recently we published the first part (m5, m5a, m6g) and the second part (C5, C5a, C6g) of research regarding comparing Graviton ARM with AMD and Intel CPU on AWS. We selected general-purpose EC2 instances with the same configurations (amount of vCPU in the first part). In the second part, we compared compute-optimized EC2 instances with the same conditions. The main goal was to see the trend and make a general comparison of CPU types on the AWS platform only for MySQL. We didn’t set the goal to compare the performance of different CPU types. Our expertise is in MySQL performance tuning. We share research “as is” with all scripts, and anyone interested could rerun and reproduce it.
All scripts, …

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Online DDL With Group Replication in MySQL 8.0.27

In April 2021, I wrote an article about Online DDL and Group Replication. At that time we were dealing with MySQL 8.0.23 and also opened a bug report which did not have the right answer to the case presented. 

Anyhow, in that article I have shown how an online DDL was de facto locking the whole cluster for a very long time even when using the consistency level set to EVENTUAL.

This article is to give justice to the work done by the MySQL/Oracle engineers to correct that annoying inconvenience. 

Before going ahead, let us remember how an Online DDL was propagated in a group replication cluster, and identify the differences with what happens now, all with the consistency level set to EVENTUAL ( …

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MySQL 8.0 Functional Indexes

Working with hundreds of different customers I often face similar problems around running queries. One very common problem when trying to optimize a database environment is index usage. A query that cannot use an index is usually a long-running one, consuming more memory or triggering more disk iops.

A very common case is when a query uses a filter condition against a column that is involved in some kind of functional expression. An index on that column can not be used.

Starting from MySQL 8.0.13 functional indexes are supported. In this article, I’m going to show what they are and how they work.

The Well-Known Problem

As already mentioned, a very common problem about index usage is when you have a filter condition against one or more columns involved in some kind of functional expression.

Let’s see a simple example.

You have a table called products containing the details of your products, …

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In Application and Database Design, Small Things Can Have a Big Impact

With modern application design, systems are becoming more diverse, varied and have more components than ever before. Developers are often forced to become master chefs adding the ingredients from dozens of different technologies and blending them together to create something tasty and amazing. But with so many different ingredients, it is often difficult to understand how the individual ingredients interact with each other. The more diverse the application, the more likely it is that some seemingly insignificant combination of technology may cause cascading effects.

Many people I talk to have hundreds if not thousands of different libraries, APIs, components, and services making up the systems they support. In this type of environment, it is very difficult to know what small thing could add up to something much bigger. Look at some of the more recent …

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Comparing AMD EPYC Performance with Intel Xeon in GCP

Recently we were asked to check the performance of the new family of AMD EPYC processors when using MySQL in Google Cloud Virtual Machines. This was motivated by a user running MySQL in the N1 machines family and willing to upgrade to N2D generation considering the potential cost savings using the new AMD family. 

The idea behind the analysis is to do a side-by-side comparison of performance considering some factors: 

  • EPYC processors have demonstrated better performance in purely CPU-based operations according to published benchmarks. 
  • EPYC platform has lower costs compared to the Intel Xeon platform. 

The goal of this analysis is to check if cost reductions by upgrading from N1 to N2D are worth the change to avoid suffering from performance problems and eventually reduce the machine size from the current 64 cores based (N1 n1-highmem-64 – Intel Haswell) to either N2D 64 …

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Percona Server for MySQL Encryption Options and Choices

Security will always be a main focal point of a company’s data. A common question I get from clients is, “how do I enable encryption?” Like every good consulting answer, it depends on what you are trying to encrypt. This post is a high-level summary of the different options available for encryption in Percona Server for MySQL.

Different certifications require different levels of encryption. For example, PCI requires both encryptions of data at rest and in transit. Here are the main facets of encryption for MySQL:

  • Data at Rest
    • Full disk encryption (at the OS level)
    • Transparent Data Encryption – TDE
    • Column/field-level encryption
  • Data in Transit
    • TLS Connections

Data at Rest

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Taking a Look at BTRFS for MySQL

Following my post MySQL/ZFS Performance Update, a few people have suggested I should take a look at BTRFS (“butter-FS”, “b-tree FS”) with MySQL. BTRFS is a filesystem with an architecture and a set of features that are similar to ZFS and with a GPL license. It is a copy-on-write (CoW) filesystem supporting snapshots, RAID, and data compression. These are compelling features for a database server so let’s have a look.

Many years ago, in 2012, Vadim wrote a blog post about BTRFS and the results were disappointing. Needless to say that since 2012, a lot of work and effort has been invested in BTRFS. So, this post will examine the BTRFS version that comes with the latest Ubuntu LTS, 20.04. It is not bleeding edge but it is likely the most recent …

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Percona Support Team New Year Greetings!

In Percona Support we spend a few hours per week doing Labs: short collective projects, not directly related to the tickets. One of our last labs was about to get ready for the winter holiday season which means preparing the tree and decorating it. To do it we used our favorite tools: MySQL, and ASCII art (https://en.wikipedia.org/wiki/ASCII_art). As a result, we created a function that prints into the terminal a New Year Tree (https://en.wikipedia.org/wiki/New_Year_tree) and decorates it with symbols we want. For example, to create a three-level tree, decorated with starts, call the function as follow:

$ mysql ny_tree -e "select ny_tree(3, '*')" --vertical --skip-column-names -s
*************************** 1. row ***************************

   /\
  /__\
  /* \
 /____\
 /  * \
/______\
   ||

Since MySQL supports Unicode you can use any symbol, having it has …

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Q & A on Webinar “MySQL Performance for DevOps”

First I want to thank everyone who attended my November 16, 2021 webinar “MySQL Performance for DevOps“. Recording and slides are available on the webinar page.

Here are answers to the questions from participants which I was not able to provide during the webinar.

Q: Hi! We have troubles with DELETE queries. We have to remove some data periodically (like, hourly, daily) and we have short-term server stalls during these DELETEs. Server is running on modern NVMe’s so we wonder why do we have this situation. Those DELETE’s are not so large, like 10 000 – 15 000 records, but tables on which DELETE’s are performed update frequently.

A: I would test if a similar

DELETE

  statement is slow when you run it on …

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