Category: Syntax

Chad Callihan shows off a good use of aggregate functions and the CASE statement:

Have you have been tasked with pulling multiple counts from the same table? Maybe you need to find how many records have a value for a column and how many are NULL. Or maybe you need to see how many records are true and how many are false.

It’s simple enough to run a query to count one set of criteria, run another query for the second set of criteria, and combine them when sending your results. Did you know you can get multiple counts with one query?

Here’s an example of how using COUNT and CASE can speed up your day.

Click through for an example. I mildly disagree with Chad’s conclusion that this is something you’ll rarely do—the more you work with reporting and analytical queries, the more you’ll appreciate this.

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Daniel Hutmacher mixes separators with regular characters:

Suppose you have a delimited string input that you want to split into its parts. That’s what STRING_SPLIT() does:

DECLARE @source nvarchar(max)='Canada, Cape Verde, '+    'Central African Republic, Chad, Chile, China, Colombia, Comoros';

SELECT TRIM([value]) AS[Country]
FROM STRING_SPLIT(@source, ',');

Simple enough. But delimited lists are tricky, because the delimiter could exist in the name itself. Look for yourself what happens when we add the two Congos to the list:

Daniel has a clever solution to the problem.

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Steve Jones shows off a good use case for window functions:

Recently I was looking at some data and wanted to analyze it by month. I have a goal that is set for each day and then an actual value. I wanted to know how I was tracking against the goal, as a running total. If my goal is 10 a day, then I ought to actually get to 10 the first day, 20 for the second day (10 + 10), etc.

Read on to see how Steve solved the problem.

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Reitse Eskens looks at a couple of useful window operators:

I was teaching a class today on more advanced SQL queries and we were discussing if you could use preceding and following in a single windowing function.

Windowing Functions

If you’re not familiar with windowing functions, they’re really cool. You can perform all kinds of trickery and magic with them. Let’s start with a simple example.
The dataset I’m using has flight data from the early 2000’s.

Read on for the example and for the answer to Reitse’s question.

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Chad Callihan looks at synonyms in SQL Server:

Are you familiar with synonyms as they relate to SQL Server? I haven’t seen them used too much out in the wild but understand they can have benefits. Let’s take a look at what synonyms are in SQL Server and some common reasons for implementing them.

My recollection is that synonyms have some limitations which make them not as useful as they’d first appear. But the bigger reason I think we don’t see synonyms used very often is that they obscure information and make it tougher to understand what’s really happening. In that respect, it’s a bit similar to a trigger: useful but sometimes painful to debug because it obscures relevant information.

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Ronen Ariely provides a solution:

However, the answer in this specific case was not optimal. Unfortunately in most cases in the forums, most people that come to ask a question, do not care about learning but only about the solution, even so in my opinion the road is just as important as the end point. The road (the learning) is what will help the person to solve the next issue and not just the current one – teach a man to fish and you feed him for a lifetime…

The op marked the answer he got and I assume that from his point of view the discussion ended, but I wanted to present the solution which might be tens time better in some cases, which is what I will do in this post…. so let’s start

I won’t dive too deeply into Ronen’s philosophical argument—you can definitely read about that in the post. I will say I am sympathetic to the argument at the margin and believe it’s worthwhile to know the superior solution.

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