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Category: Syntax

CAST() and CONVERT() for Dates

Chad Callihan converts a date:

CAST and CONVERT can both be used to switch a value to a new data type. They are similar, but certainly not identical. While CAST is considered ANSI SQL and will get you across the finish line, CONVERT can give you more flexibility when it comes to formatting date values. Let’s look at an example comparing the usage of CAST and CONVERT with dates.

Most of the time, I’ll use CAST() over CONVERT(), not so much because the former is ANSI compliant, but rather because I think it’s more intuitive to remember. Date formatting is one of the few occasions in which I usually prefer CONVERT() and that’s precisely because of the format options. Of course, if you want more custom formatting options, you can use FORMAT(), though that function uses .NET in the background and is remarkably slow. It’s fine if you’re formatting a few dates, but if you’re outputting millions of rows, you will certainly see a marked difference.

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Substrings in MySQL

Rahul Mehta describes how substrings work in MySQL:

MySQL is an open-source relational database management system. It is a widely used relational database management system in the entire world. MySQL like any other database can store different types of data. One of the most used data types is “String”. Developers widely use it in storing data as well as in different formatting operations. One of the key requirements we will always come across is to derive a part of the string. MySQL provides a “SUBSTRING” function to extract a substring from a string. My SQL has below options for extracting the string:

  1. SUBSTRING
  2. SUBSTR (A SYNONYM FOR SUBSTRING)
  3. SUBSTRING_INDEX

Read on to see how these two functions work. They differ a bit from SQL Server in terms of functionality, though there’s a lot of overlap between the two.

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MERGE is (Kinda) Okay

Hugo Kornelis performs a survey:

The MERGE statement compares source and target data, and then inserts into, updates, and deletes from the target table, all in a single statement. This statement was introduced in SQL Server 2008. I liked it, because it allows you to replace a set of multiple queries with just one single query. And while a statement with that many options necessarily has a more complex syntax, I still believe that, in most cases, a single MERGE statement is easier to read, write, and maintain, than a combination of at least an INSERT and an UPDATE, often a DELETE, and sometimes first a SELECT into a temporary table if the source is complex.

Click through for a review of a variety of problems people have had in the past. It surprised me a bit when I learned how few of these issues were still active problems caused by MERGE.

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SparkSQL CONCAT vs T-SQL CONCAT

Bill Fellows has a public service announcement:

The concat function is super handy in the database world but be aware that the SQL Server one is way better because it solves two problems. It combines everything into a string and it does not require NULL checking. In the before times, one had to down cast to a n/var/char type as well as check for NULL before appending strings via the plus sign.

The point of difference is so important that Bill busted out the marquee HTML tag. Which now leads me to wonder, was marquee or blink the bigger evil in the mid-to-late ’90s web?

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WITHIN GROUP in STRING_AGG()

Chad Callihan messes with groups:

When was the last time you wrote a SQL query and knew something was possible but just couldn’t remember how? I had one of those moments this week with STRING_AGG and ordering data, and although it was frustrating, I knew it would make a worthwhile blog post. Let’s look at some examples using STRING_AGG and WITHIN GROUP (aka the clause that slipped my mind).

There’s a perfectly good reason why WITHIN GROUP might slip your mind: STRING_AGG() is known as an ordered set function (versus a window function which uses an OVER() clause). It’s also the only ordered set function SQL Server supports, so you don’t get too many opportunities to use the key phrase.

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Dueling Sequences for Positive and Negative Numbers

Jose Manuel Jurado Diaz hears banjo music:

SQL Server’s INT data type, by design, provides a range from -2,147,483,648 to 2,147,483,647. But often, developers only utilize the positive range for primary keys and other identifier fields, effectively wasting half of its potential. What if we could harness this full range to temporarily extend the capacity of an INT column? In this article, we explore this idea in-depth.

I’m of two minds here. On the one hand, surrogate keys don’t have a meaning (by definition!), so it doesn’t really matter if that number is positive or negative. Also, including negative numbers makes sense when you expect the steady state table size to be above 2 billion but below 4 billion rows (assuming that you’re using an INT datatype), or you’ve found out that the steady state size is that big after the fact.

On the other hand, I don’t like having a caller define whether they want positive or negative values, as that now imbues meaning to the surrogate key, where positive keys mean one thing and negative keys mean another.

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Alternatives to GREATEST and LEAST in SQL Server 2022

Drupal Grupal gives us alternatives:

If you haven’t already heard, SQL 2022 has introduced a new built-in system function called GREATEST. Simply put, it is to a set of columns, variables, expressions etc. what the MAX function is to a set of values (i.e., rows) of a single column or expression. The opposite of GREATEST function is LEAST function which returns the smallest value from the supplied list of columns, variables, constants etc. GREATEST & LEAST can be considered a pair, just as MIN/MAX functions are.

In other situations, GREATEST() and LEAST() are known as ARGMAX() and ARGMIN(), respectively.

Drupal shows us two alternatives to the built-in function and includes a performance comparison.

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Creating a Function in Snowflake

Kevin Wilkie creates a function:

Sometimes, you’ll need to create functions that do a particular thing. They’re not always pretty. Some of them look like they should have been thrown out with the bathwater.

Unlike SQL Server, user-defined functions in Snowflake can be done in several different languages. They can be done in Java, JavaScript, Python, Scala, or plain-old SQL.

Which means that Postgres users will be a bit more comfortable here than SQL Server users.

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A Primer on Database Constraints in MySQL

Robert Sheldon creates some keys:

MySQL supports six basic types of constraints for ensuring data integrity: PRIMARY KEYNOT NULLDEFAULTCHECKUNIQUE, and FOREIGN KEY. In this article, I introduce you to each constraint type and provide examples for how they work. The examples include a series of CREATE TABLE statements that demonstrate different ways to incorporate constraints into your table definitions. If you’re not familiar with the CREATE TABLE statement or how to create tables in a MySQL database, refer to an earlier article in this series that introduces you to the statement.

In short, they support the same set that SQL Server users are used to. But do read on to see the nuances behind each of these.

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