Support Channel. “Hi, I am getting deadlocks in the database and they occur when I have to rollback the transactions but if we don’t have to roll back all transactions get executed.” Wait, what? After some back and forth it becomes clear that the Dev experiences deadlocks and has data:

mysql> pager less
mysql> show engine innodb status\G
...
MySQL thread id 142531, OS thread handle 139990258222848, query id 4799571
somehost.somedomain someuser update
INSERT into sometable (identifier_id, currency, balance ) VALUES ('d4e84cb1-4d56-4d67-9d16-1d548fd26b55', 'EUR', '0')
*** (2) HOLDS THE LOCK(S):
RECORD LOCKS space id 3523 page no 1106463 n bits 224 index PRIMARY of table `somedb`.`sometable` trx id 9843342279 lock mode S locks gap before rec

and that is weird because of the lock mode S locks gap in the last line. We get the exact same statement with the exact same value on the second thread, but with …

In a previous article we wrote data to the database using atomic update statements, and then using transactions with SELECT ... FOR UPDATE. In this article we will look at what happens when we continue doing this, in a more complicated way. Source code for this article is also available on github.com.

A simple row lock

But first let’s do things manually: We create a table kris with an integer primary key column and a secondary unindexed data column. We are filling it with some records with gaps between the primary keys.

We then START TRANSACTION READ WRITE and SELECT ... FOR UPDATE a record:

Session1> create table kris ( id serial, …

A student question: Does JavaScript make context switching for web-based applications obsolete? Wow! I asked what that meant. He said, it means JavaScript replaces all other server-side programming languages, like PHP, C#, or Python. I asked the student why he believed that. His answer was that’s what two interviewing managers told him.

I thought it would be interesting to put the idea to a test. Below is a Node.js script that acts as a utility that queries the MySQL database with substitution variables in query. It also returns a standard out (stdout) stream of the MySQL query’s results. It also supports three flag and value pairs as arguments, and optionally writes the results of the MySQL query to a log file while still returning result as the stdout value. All errors are written to the standard error (stderr) stream.

The Node.js solution is completely portable between Windows …

Watch this on-demand webinar to learn the right way to deploy geo-distributed databases. We look at the pitfalls of deploying a single site and passive sites, and from there we show how to provide the best user experience by leveraging geo-distributed MySQL.

Tags:  MySQL Geo-Distributed mysql clustering single site passive site best practices Webinar …

This is the kick-off of our Tungsten MySQL Use Case Webinar Series presented by Continuent CEO Eero Teerikorpi. Our first three webinars offer a choice of topics ranging from Global MySQL Availability, MySQL Data Protection to MySQL High Availability.

Tags:  Webinar MySQL use case tungsten clustering mysql cluster global availability mysql data protection …

So this has turned into a small series, explaining how to work with MYSQL from a developers perspective. This post is intended as a directory for the individual articles. It will be amended and re-dated as necessary.

The code for the series is also available in isotopp/mysql-dev-examples on GitHub.

The Tag #mysqldev will reference all articles from this series.

• MySQL Transactions - the physical side. Looking at how MySQL InnoDB handles transactions on the physical media, enabling rollback and commit. Introduces a number of important concepts: The Undo Log, the Redo Log, the Doublewrite Buffer, and the corrosponding in memory …

Using the framework for testing we created in earlier articles, let’s try to modify some data. We are writing a small program that increments a counter. Our table looks like this, and contains 10 counters:

CREATE TABLE `demo` (
  `id` bigint unsigned NOT NULL AUTO_INCREMENT,
  `counter` int NOT NULL DEFAULT '0',
  UNIQUE KEY `id` (`id`)
)
INSERT INTO `demo` VALUES (1,0);
INSERT INTO `demo` VALUES (2,0);
...
INSERT INTO `demo` VALUES (10,0);

We are using some very simple programming to increment a counter:

@sql.command()
@click.option("--name", default="demo", help="Table name to count in")
@click.option("--id", default=0, help="Counter to use")
@click.option("--count", default=1000, help="Number of increments")
def count(name, id, count):
    """ Increment counter --id by --count many steps in table --name """
    for i in range(0, count):
        cmd = f"update {name} set counter=counter+1 where id = {id}"

        c …

As Group Replication (GR) matures and it is deployed in a myriad of different systems, we begin to witness specific network conditions that we must be able to cope with in order to make Group Replication more tolerant and robust to those failures.…

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I wanted to be brave and I installed MySQL Group Replication manually…. it was painful !

Then I realized that managing those servers and especially deal with MySQL Routers was even more painful !

What are my options now ? Is there a solution or do I need to restart from scratch ?

Asking the answer is already answering it… and once again MySQL Shell at the rescue.

MySQL Group Replication

I’ve configured everything manually. I also loaded group_replication and clone plugins and finally after having bootstrapped my Group here is what I have:

mysql> select member_host, member_port port, member_state state, 
       member_role role, member_version version 
       from performance_schema.replication_group_members;
+-------------+------+--------+-----------+---------+
| member_host | port | state  | role      | version | …

After having a look how MySQL handles transactions physically, let’s have a look at what is going on from a logical point of view.

We are using a test table called demo with an id and a counter field, both integer. In it we have 10 counters, all set to 0.

CREATE TABLE `demo` (
  `id` bigint unsigned NOT NULL AUTO_INCREMENT,
  `counter` int NOT NULL DEFAULT '0',
  UNIQUE KEY `id` (`id`)
)
INSERT INTO `demo` VALUES (1,0);
INSERT INTO `demo` VALUES (2,0);
...
INSERT INTO `demo` VALUES (10,0);

In one session, we start a transaction and modify a counter value. We do not commit anything.

Session1> start transaction read write;
Session1> update demo set counter = 10 where id = 3;

Isolation

In a second session, we check the data and notice a few things:

Session2> …