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Category: T-SQL

Querying Database and Log File Sizes with T-SQL

Published 2020-04-17 by Kevin Feasel

Allen White takes us through an easy technique to check database and log file sizes:

As a consultant, I have to be able to quickly spot problems, and one of the problems I frequently find is transaction log files that are incorrectly sized.

There are two catalog views in the master database which make this easy to do – sys.master_files and sys.databases. The sys.master_files view contains the database and individual file names, and the data_space_id column always has a value of 0 for the log file. The size column returns the value in 8KB pages, so we have to multiply the column by 8, then divide by 1024 to get the size in megabytes (MB).

Click through for the demo.

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MERGE in Many Languages

Published 2020-04-10 by Kevin Feasel

Lukas Eder takes a look at the MERGE statement in SQL:

A few dialects support MERGE. Among the ones that jOOQ 3.13 supports, there are at least:

– Db2
– Derby
– Firebird
– H2
– HSQLDB
– Oracle
– SQL Server
– Sybase SQL Anywhere
– Teradata
– Vertica

For once, regrettably, this list does not include PostgreSQL. But even the dialects in this list do not all agree on what MERGE really is. The SQL standard specifies 3 features, each one optional:

– F312 MERGE statement
– F313 Enhanced MERGE statement
– F314 MERGE statement with DELETE branch

But instead of looking at the standards and what they require, let’s look at what the dialects offer, and how it can be emulated if something is not available.

This is a really cool overview of an area where several vendors can claim support, but that support can mean quite different things. The one caveat is, I don’t know if any of the other platforms’ MERGE operators are as busted as SQL Server’s in terms of bugs.

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All About Table Expressions

Published 2020-04-09 by Kevin Feasel

Itzik Ben-Gan has started a series on table expressions:

Perhaps this will come as a surprise to some, but I actually do find the use of the term table in common table expression as very appropriate. In fact, I find the use of the term table expression as appropriate. To me, the best way to describe what a CTE is in T-SQL, it’s a named table expression. The same applies to what T-SQL calls derived tables (the specific language construct as opposed to the general idea), views and inline TVFs. They are all named table expressions.

If you can bear with me a bit, I’ll provide the reasoning for my view of things in this article. It occurred to me that both the naming confusion, and the confusion around whether there’s a persistency aspect to table expressions, can be cleared with a better understanding of the fundamentals of our field of relational database management systems. Those fundamentals being, relational theory, how SQL (the standard language) relates to it, and how the T-SQL dialect used in the SQL Server and Azure SQL Database implementations relates to both.

There’s a lot of depth in this post, so I recommend a careful reading.

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VARCHAR Columns and Bytecode Version Mismatch in R

Published 2020-04-06 by Kevin Feasel

Dave Mason runs through a tricky problem with SQL Server Machine Learning Services:

During my testing, I’ve found R handles CHAR and VARCHAR data within the input data set as long as the ASCII codes comprising the data is in the range from 0 to 127. This much is not surprising–those are the character codes for the ASCII table. Starting with character code 128, R begins having some trouble. 

Read on to see the problem. Dave’s advice at the end is sound (and frankly, my advice for any string data in SQL Server).

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Combining User-Defined Types and Temp Tables

Published 2020-04-03 by Kevin Feasel

Andy Levy tries to make cats and dogs live together:


This tripped me up a few weeks ago, but once I stopped and thought about for a moment it made total sense. I was trying to copy some data into a temp table and got an error I’d never encountered before.

Column, parameter, or variable #1: Cannot find data type MyStringType.

What’s that all about? Let’s find out.

I don’t think it spoils things to say that Andy’s story is a tragedy and not a comedy. But in fairness, the number of shops using user-defined types (as opposed to user-defined table types) is probably not enormous.

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The Peril of Local Variables

Published 2020-04-01 by Kevin Feasel

Erik Darling dives into the tradeoffs you make when using local variables in stored procedures to avoid parameter sniffing:

In a stored procedure (and even in ad hoc queries or within dynamic SQL, like in the examples linked above), if you declare a variable within that code block and use it as a predicate later, you will get either a fixed guess for cardinality, or a less-confidence-inspiring guess than when the histogram is used.

The local variable effect discussed in the rest of this post produces the same behavior as the OPTIMIZE FOR UNKNOWN hint, or executing queries with sp_prepare. I have that emphasized here because I don’t want to keep qualifying it throughout the post.

This deserves a careful read-through.

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Tracking Object Changes and Views

Published 2020-04-01 by Kevin Feasel

Ed Pollack has a solution for tracking when the underlying objects which make up a view change:

When a view’s underlying objects change, the view itself will not change. This can result in a view where the data types of columns, as well as nullability, precision, and scale can be reported inaccurately. When this happens, it is possible for queries against these columns to return errors, truncate data, perform poorly, or otherwise behave in unexpected ways.

This article will delve into views, how they are defined, and how T-SQL can be used to programmatically test the validity of views and ensure they never become stale.

Click through for an interesting article with plenty of code demos.

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Using T-SQL to Generate a Login Migration Script

Published 2020-03-30 by Kevin Feasel

Thomas Rushton shows us how to migrate logins from one server to another using just T-SQL:

There are three things to look at:

1. Creating Logins from Windows accounts
2. Creating logins that are authenticated by SQL Server
3. Assigning membership of the appropriate server roles

Note that we’re just creating a snapshot of what’s there – we’re not aiming to keep these things in true synchronisation between servers. Note also that this script will only create accounts that don’t exist. If there’s an account already there with the same name, the script generated will not recreate it with new options.

We get the final script as well as a nice walkthrough of each component.

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Avoid Default String Lengths

Published 2020-03-30 by Kevin Feasel

Kenneth Fisher warns us against creating strings without specifying a length:

Every now and again I see someone get lazy and declare a string (CHAR, NCHAR, VARCHAR and NVARCHAR) without specifically declaring what the length is going to be. This can lead to some interesting problems. First of all it’s usually going to be a length of one.

I’d take this one step further and say avoid creating strings without specifying a length in products like ADO.NET as well—there, you won’t get the single-character length Kenneth mentions here, but you do get one plan per character length passed in, which does a great job of bloating the plan cache.

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Trimming Strings with T-SQL

Published 2020-03-18 by Kevin Feasel

Andy Levy saves us all several characters at a time:

Every now and then, we encounter data that needs to be cleaned up because it’s got leading and/or trailing spaces. Or maybe you’re storing short data in a CHAR(N) field, so when you query it, you’re getting trailing spaces. For time immemorial, we’ve had to wrap these fields in rtrim(ltrim(fieldname)) to do the deed.

Effective with SQL Server 2017, that’s no longer the case. 

The eight keystrokes add up over time. In all seriousness, I am happy that TRIM() is a thing in SQL Server 2017. And Andy gives us a little bonus to make it worth your refactoring while.

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