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Category: T-SQL

VARCHAR Columns and Bytecode Version Mismatch in R

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

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

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

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

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

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

Every now and again I see someone get lazy and declare a string (CHARNCHARVARCHAR 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

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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Quickly Finding Distinct Values with T-SQL

Paul White does some amazing things with T-SQL, news at 11:

I will be looking for distinct values in the BountyAmount column of the dbo.Votes table, presented in bounty amount order ascending. The Votes table has just under 53 million rows (52,928,720 to be exact). There are just 19 different bounty amounts, including NULL.

The Stack Overflow 2013 database comes without nonclustered indexes to minimize download time. There is a clustered primary key index on the Id column of the dbo.Votes table. It comes set to SQL Server 2008 compatibility (level 100), but we will start with a more modern setting of SQL Server 2017 (level 140):

Getting the query down from 10.5 seconds to 1ms is crazy.

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Supporting Multiple NULL Values with a Unique Constraint

Itzik Ben-Gan walks us through a workaround in T-SQL:

Suppose that you have a database in a platform that supports the standard unique constraint and you need to migrate that database to SQL Server. You may face issues with the enforcement of unique constraints in SQL Server if the unique columns support NULLs. Data that was considered valid in the source system may be considered invalid in SQL Server. In the following sections I’ll explore a number of possible workarounds in SQL Server.

I use a simplified version of this as an interview question, so it’s nice to see an entire article from Itzik on the topic, including a couple solutions way outside the box.

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Selecting From a Stored Procedure

Madhivanan shows us how to query the results of a stored procedure:

One of my friends asked me “Is it possible to query Stored Procedure resultset like a table. ie select * from (EXEC Stored_procedure)?”

Well. Querying the resultset from the Stored Procedure like Table can be done using OPENROWSET function

This is a fairly novel approach to the problem. In the past, I’ve inserted the results of a stored procedure into a temp table, but you can only do that if the procedure itself doesn’t call INSERT INTO ... EXEC ....

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