Top n Window Function queries over a specific subset of data are common in analysis and reporting requirements. Luckily, in MySQL, there are Window functions we can use for this type of query. To be quite honest, you don’t necessarily need Window Functions. You can retrieve those top 3 (or whatever) types of results with a regular SQL query. But, since we have those powerful Window Functions, why not use them? My thoughts exactly! Besides, no one wants a spaghetti code mess of SQL to try and understand. Not to mention, Window functions are often better optimized for querying larger data sets. Continue reading and see example queries for more understanding…

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These days, I mostly program in PHP with MySQL as the database, which is just fine by me. I have had a long-time interest in MySQL (SQL in general), and after several steady months of programming in PHP, I must say I have really come into the language and developed a fondness for it. All that being said, I still enjoy using and learning the MySQL Shell in Python mode. As Database Developers, we often need the LAST INSERT ID value from a previous INSERT statement on a column that has the AUTO_INCREMENT attribute. MySQL Shell has a get_auto_increment_value() method we can call against a Shell object result and retrieve that value. Continue reading and see examples of the MySQL Shell get_auto_increment_value() method used in Python mode…

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I recently watched a fantastic Python Pandas library tutorial series on YouTube. Without a doubt, Pandas is great for all sorts of data stuff. On the same token, MySQL Shell in Python mode is quite powerful in the sense that Python and the MySQL Shell (version >= 8.0) are somewhat united in the same environment. Although Pandas is in a league all its own when it comes to data analysis, between the power of MySQL and Python, we can also perform some basic analysis easily in MySQL Shell Python mode. In this blog post, I will cover some basic data analysis using Python mode in the MySQL Shell. Continue reading to see examples…

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Over the last few months, I have written numerous blog posts on different features of the MySQL Shell ranging from basic CRUD to aggregate functions and DDL. As a part of the MySQL version 8 release, MySQL Shell is a powerful and alternative environment that you can manage and work with your data in using a choice of 3 languages: Python, Javascript, or SQL. So this blog post is a simple compilation of all the Python mode related posts, in one easy-to-access location…

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We all know as SQL professionals that a common use of the ALTER TABLE command is that we can change a tables’ structure in a myriad number of ways. And, that’s a good thing too because chances are, you won’t always nail down the initial structure. Due to changing business or application requirements, you may even have to add additional columns that were not considered during the schema design phase. Suppose you have many tables that are structured similarly and they all need a specific column added to their already-existing design. Under certain circumstances, using the MySQL Shell in Python mode (\py), can reduce the number of manual ALTER TABLE statements you have to type. Continue reading to see examples in the MySQL Shell…

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There may come a time you need to rename one or more columns in an existing MySQL table for a variety of reasons. Using ALTER TABLE, to rename a column is an easy enough command. But, suppose there are multiple tables in the same database/schema that have the same-named column and all of those columns need to be renamed. That could be a lot of ALTER TABLE statements to type out. Save your energy and time, avoiding all of those ALTER TABLE commands all-together. If you are lucky enough to be working with a MySQL version > 8.0 then the Shell is your salvation. With just a few lines of Python code in \py mode, all of your trouble(s) and headache(s) are no more…

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Date and time values are some of the most important datatypes in an RDBMS. From tracking order dates to payroll hours, DATE and DATETIME datatypes are used in all types of applications. At times as a Developer, you may need only certain portions of a DATE or DATETIME value. In MySQL, the EXTRACT() function can provide you with a specific component of a DATE or DATETIME value depending on which INTERVAL is given as a parameter. Continue reading to see example EXTRACT() queries for understanding…

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Have you ever had to type out a massive CREATE TABLE statement by hand? One with dozens of columns? Maybe several dozens of columns? There are likely some GUI tools to help with large CREATE TABLE commands. Or, other drag-n-drop types of software that I am not familiar with. What if you could write a few lines of Python code and take care of a huge CREATE TABLE statement with way less effort than typed manually? Interested? Continue reading and see how using pandas, pyodbc, and MySQL…

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If you are a developer working in a MySQL environment, this blog post is for you. I share 3 MySQL commands or statements that you should know. That is a bold statement, I know. Turns out, once you do know (of) these commands, you will use them all the time. They minimize guesswork which leads to better productivity in other facets of your programming and querying workflow. I use them myself almost daily and am sure you will too once you see how simple they are to use. So why should you know them? Continue reading and find out…

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• OpenSuse Leap 15.1
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In this post, I’ll cover examples of the MySQL TRIM() function. TRIM() removes specific characters – or spaces – from a given string, at either: the beginning, ending, or potentially in both locations depending on several factors. With an optional keyword argument that controls which character(s) – if any – are removed, TRIM() can be tricky so let’s gain understanding with several easy-to-digest examples…

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OS, Software, and DB used:

• OpenSuse Leap 15.1
• MySQL 8.0.20

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