Validating MySQL version numbers

As part of a MySQL 5.5 to MySQL 5.6 upgrade across several Ubuntu servers of varying distros an audit highlighted a trivial but interesting versioning identification error in Ubuntu’s packaging of MySQL.

Ubuntu 12.04 LTS

$ sudo dpkg -l | grep mysql-server-5.5
ii  mysql-server-5.5   5.5.41-0ubuntu0.12.04.1  ...

$ mysql -uroot -p -e "SELECT VERSION()"
+-------------------------+
| VERSION()               |
+-------------------------+
| 5.5.41-0ubuntu0.12.04.1 |
+-------------------------+

But when you look at the mysql --version it does NOT say 5.5.41.

$ mysql --version
mysql  Ver 14.14 Distrib 5.5.34, for debian-linux-gnu (x86_64) using readline 6.2

Ubuntu 14.04 LTS

On 14.04 I get expected results.

$ sudo dpkg -l | grep mysql-server-5.5
ii  mysql-server-5.5       5.5.41-0ubuntu0.14.04.1   ...

rbradfor@rubble:~$ mysql -uroot -p -e "SELECT VERSION()"
+-------------------------+
| VERSION()               |
+-------------------------+
| 5.5.41-0ubuntu0.14.04.1 |
+-------------------------+

$ mysql --version
mysql  Ver 14.14 Distrib 5.5.41, for debian-linux-gnu (x86_64) using readline 6.3
Tagged with: Databases MySQL

Producing Alternative Means statistics with SQL

Producing Alternative Means statistics with SQL

MySQL’s built-in AVG() computes the arithmetic mean — the sum divided by the count. That is the right default for many questions, but it is not always the right measure of central tendency.

Extending MySQL Capabilities with UDFs, Plugins and Components

Extending MySQL Capabilities with UDFs, Plugins and Components

MySQL offers three different approaches to extending the SQL capabilities with the default product you download and install. These are: User Defined Function (UDF) MySQL Manual MySQL Plugin MySQL Manual MySQL Component MySQL Manual For the purposes of this post I will be using the current LTS version MySQL 8.

Producing One-Sample Z-Test statistics with SQL

Producing One-Sample Z-Test statistics with SQL

The one-sample Z-test determines whether a sample mean differs significantly from a known population mean when the population standard deviation is also known. It is the appropriate test when the population parameters are established — quality control benchmarks, national averages, long-run process measurements — and you want to evaluate whether a new sample is consistent with them.