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Category: T-SQL

Finding Foreign Key Relationships in SQL Server

Published 2020-02-04 by Kevin Feasel

John Morehouse shows how you can piece together foreign key relationships in SQL Server:

Recently, I had to purge some parent records from a table.  In this case, the parent table had foreign keys, which itself isn’t an issue.  The fact that there were more than 30 of them was.   While SQL Server will happily tell you that you are violating a foreign key if a child record is present when deleting the parent record, finding all of them can be cumbersome.  This is even more true when you have a larger number of foreign keys.

Thankfully, SQL Server can tell us a lot of information about foreign keys including both the parent and child tables as well as the column used.  From this information, we can dynamically create a SELECT statement that would tell us the number of child records that are tied to the parent ID.

Click through for the solution.

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Splitting Strings with T-SQL

Published 2020-02-04 by Kevin Feasel

Andy Levy recommends using STRING_SPLIT():

Last year, you finally retired the last of your SQL Server 2008R2 instances. Congratulations! But are you taking advantage of everything that your new instances have to offer? Unless you did a review of all of the T-SQL in your applications, I’m guessing not.

At one time or another, we all find ourselves having to do some string parsing, especially splitting strings on a delimiter. Nearly all of us have one (or two or a dozen) functions for doing this somewhere on every instance of SQL Server. But since SQL Server 2016, we’ve had an official way to do it – the STRING_SPLIT() function.

Andy’s example involves splitting strings, but there are plenty of functions which come into the T-SQL lexicon. It might be worth doing a quick review of the available system functions just to see if there’s something useful which slipped with a newer version of SQL Server.

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Solving the Gaps and Islands Set of Problems

Published 2020-01-23 by Kevin Feasel

Ed Pollack continues a series on gap and island analysis:

Gaps and islands analysis supplies a mechanism to group data organically in ways that a standard GROUP BY cannot provide. Once we know how to perform an analysis and group data into islands, we can extend this into the realm of real data.

For all code examples in this article, we will use a set of baseball data that I’ve created and maintained over the years. This data is ideal for analytics as it is large and contains data quality that varies between very accurate and very sloppy. As a result, we are forced to consider data quality in our work, as well as scrutinize boundary conditions for correctness. This data will be used without much introduction as we will only reference two tables, and each is relatively straightforward.

The code in this article gets a bit complex, but Ed shows off some powerful techniques.

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Contrasting TVPs and Memory-Optimized TVPs

Published 2020-01-22 by Kevin Feasel

Denis Gobo wants to see what memory-optimized table-valued parameters are good for:

The other day I was thinking about the blog post Faster temp table and table variable by using memory optimization I read a while back. Since you can’t believe anything on the internets (no disrespect to whoever wrote that post) , I decided to take this for a test

In this post I will be creating 2 databases, one is a plain vanilla database and the other, a database that also has a file group that contains memory optimized data

I will also be creating a table type in each database, a plain one and a memory optimized one in the memory optimized database

Read on for Denis’s findings.

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Fun with SET Options

Published 2020-01-21 by Kevin Feasel

Dan Guzman takes us through different SET options in T-SQL and where you can go wrong:

ANSI_PADDING OFF has also been deprecated for quite some time and the SQL Server documentation specifically calls out “ANSI_PADDING should always be set to on.” In summary, a column-level ANSI_PADDING OFF setting causes nullable fixed-length char(n) and binary(n) columns to behave like variable-length varchar(n) and varbinary(n) columns. Furthermore, SQL Server automatically trims trailing blank characters from character data and leading binary zeros from binary data and stores the values as variable length instead of storing the provided value as-is during inserts and updates. Varchar(n)/varbinary(n) columns with ANSI_PADDING OFF are similarly trimmed. Note that it is the persisted ANSI_NULLS column meta-data setting that determines the storage and trimming behavior, not the current session ANSI_PADDING setting. The session ANSI_PADDING must still be ON when using features that require proper settings.

Some of these will pop up in occasional errors, like if you’re using filtered indexes or indexed views.

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Qutoed Data and OPENROWSET

Published 2020-01-20 by Kevin Feasel

Dave Mason wants to remove quoted identifiers from a flat file:

I haven’t shown all the columns, but you get the idea–every column in the result set has data enclosed in double quotes. That’s exactly how it appears in the source data file.

Dave has a method which works for plenty of versions of SQL Server. If you’re using 2017 or later, the FIELDQUOTE parameter was added to solve this problem, though to be fair, I haven’t actually tried it to see if it works as expected.

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Not All Cursors are Bad

Published 2020-01-10 by Kevin Feasel

Erik Darling doesn’t want to mess with your cursors (that much):

Read the code. Understand the requirements.

I tune queries all day long. The number of times someone has said THIS CURSOR IS A REAL BIG PROBLEM and been right is pretty small.

Often, there was a tweak to the cursor options, or a tweak to the query the cursor was calling (or the indexes available to it) that made things run in a more immediate fashion. I want to tune queries, not wrestle with logic that no one understands. Old code is full of that.

I’ll grant the premise (and add my own case where a cursor was necessary to solve the problem), though I did work at one company where the entire product logic was driven by nested cursors 5 or 6 levels deep. Those were really big problems. I think you’ll find the problem most frequently in shops with a heavy dose of Oracle, as Oracle cursors do perform well.

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Using the OUTPUT Clause

Published 2020-01-06 by Kevin Feasel

Eduardo Pivaral takes us through the OUTPUT clause:

Even when the code is easy to read, but if you use this pattern over all your codebase, maintain it can become difficult if you have to change object names or implement it on another system.

T-SQL language provides the OUTPUT clause, that allows you to retrieve information from a DML statement in the same batch.

This is pretty useful for performance tuning in some scenarios, but also for simplifying multi-step processes.

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Gap and Island Analysis

Published 2020-01-03 by Kevin Feasel

Ed Pollack covers a topic of importance for database developers:

Within a data set, an island of data is any ordered sequence where each row is in close proximity to the rows around it. For some data types and analysis, “close proximity” will mean consecutive. Dates, integers, and letters of the alphabet can be ordered sequentially where two adjacent values will not be able to have additional values in between them.

For example, there are no dates between October 23rd and October 24th. Similarly, there are no integers between 17 and 18 and no English letters between E and F. For these examples, an island of data could be defined as a sequence of consecutive values. A gap can be defined as a sequence of missing values.

There are a lot of difficult problems which gap & island analysis makes much easier by pivoting the way you think about the problem.

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