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In order to stay current in a technology you have to immerse yourself in community content.

Documentation is good for knowing the specification of a language or tool and books or training courses are great for when you want to dive deep on a particular topic. However in many technology fields, including SQL Server, one of the best ways to stay up to date is by following blogs.

Not only are blogs posts typically showing newer features and techniques that haven't been able to make their way into books and training courses yet, they often will cover more specialized scenarios and edge cases than you'll encounter in the traditional learning sources. Following a broad user base of SQL Server professionals who blog solutions to problems they encounter and will often open your eyes to features of the tools you use everyday that you weren't even aware of.

This is especially nice for times when I'm not actively learning a specific topic. Reading a variety of blogs on various SQL Server subjects often reminds me how much I don't know and how many features I don't use during my day-to-day work. These blogs also serve as inspiration to investigate ideas further.

RSS Feeds

My favorite way to follow other SQL Server blogs is by subscribing to RSS feeds. I use Feedly as my RSS feed reader of choice (RIP Google Reader) and browse through all of my feeds whenever I have downtime. Inspired by Brent Ozar's post last year, I'm sharing all of the RSS feeds I follow in this OPML file.

You can download the OPML file and import it into your RSS reader as a starting point, or go through the list of websites and see if you find something new. I decided to also include my non-SQL feeds in the above link too (they are categorized in appropriate sections) in case you are curious about what sites I follow for other programming and career topics.

It's impossible to stay up to date with all the information that I want to, but staying up to date on RSS feeds gets me close.

I'm always looking for more sources - RSS is so easy to consume - so if you have any suggestions please let me know!

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Today I want to share with you an interesting observation I made about SELECT expression execution order.

I was working on writing a dynamic SQL query that would transform the following piece of JSON:

{"data":[["a","b","c"],["d","e","f"]]}

Into a query that looked like this:

SELECT 'a' AS Row0Column0, 'b' AS Row0Column1, 'c' AS Row0Column2 
UNION ALL
SELECT 'd' AS Row1Column0, 'e' AS Row1Column1, 'f' AS Row1Column2 

Normally I would use something like OPENJSON and PIVOT to transform the original data into a table result set, but in this instance I my requirements dictated that I needed to build the code as a series of SELECT and UNION ALL statements.

The first step in building this query was using OPENJSON to parse the JSON data into rows and value arrays:

SELECT
    *
FROM
(
SELECT
    rows.[key] AS RowNumber,
    rows.[Value] AS RowArray
FROM 
    OPENJSON(N'{"data":[["a","b","c"],["d","e","f"]]}','$.data') rows
) r
CROSS APPLY OPENJSON(r.RowArray) v
ORDER BY
    r.RowNumber,
    v.[key]

This first query was a good start. I then added a variable @RowQuery and started building my dynamic SQL code to generate my SELECT and UNION ALL statements:

DECLARE 
    @RowQuery varchar(max)

/* TOP is here to get the ORDER BY to work as expected */
SELECT TOP 134960239460263
    @RowQuery =  COALESCE (@RowQuery + ' ','') + '''' + v.[value] + ''' as [Row'+r.RowNumber+'Column'+v.[key]+']'
FROM
(
SELECT
    rows.[key] AS RowNumber,
    rows.[Value] AS RowArray
FROM 
    OPENJSON(N'{"data":[["a","b","c"],["d","e","f"]]}','$.data') rows
) r
CROSS APPLY OPENJSON(r.RowArray) v
ORDER BY
    r.RowNumber,
    v.[key]

PRINT 'SELECT ' + @RowQuery;

At this point I had the row/column numbering correct, but I still needed to add a UNION ALL SELECT before the start of each row.

I thought, "Oh, this is easy. Since the dynamic SQL I'm building is basically a loop, I need to check for a change in the RowNumber column's value to identify I'm on a new row. If I am, I can insert the UNION ALL SELECT text and I'll be all set":

DECLARE 
    @RowQuery varchar(max),
    @CurrentRow int = 0;

/* TOP is here to get the ORDER BY to work as expected */
SELECT TOP 134960239460263
    @RowQuery =  COALESCE (@RowQuery + '','') + IIF(r.RowNumber > @CurrentRow, CHAR(10)+'UNION ALL'+CHAR(10)+'SELECT ', ', ')+'''' + v.[value] + ''' as [Row'+r.RowNumber+'Column'+v.[key]+']',
    @CurrentRow = IIF(r.RowNumber > @CurrentRow, r.RowNumber, @CurrentRow)
FROM
(
SELECT
    rows.[key] AS RowNumber,
    rows.[Value] AS RowArray
FROM 
    OPENJSON(N'{"data":[["a","b","c"],["d","e","f"]]}','$.data') rows
) r
CROSS APPLY OPENJSON(r.RowArray) v
ORDER BY
    r.RowNumber,
    v.[key]

/*remove the first comma and add an initial SELECT */
PRINT STUFF(@RowQuery,1,1,'SELECT'); 

Success! But as I was celebrating my dynamic SQL victory, I realized I was making an assumption about SQL Server that I had never thought about before:

The above query only works because SQL Server is executing the variables in the SELECT list sequentially. I'm incrementing @CurrentRow only after processing my @RowQuery variable, and this logic only works correctly if SQL Server executes the variable expressions in the order they appear in the SELECT list. If SQL Server was executing items in the SELECT list in reverse or random order, @CurrentRow could potentially get set BEFORE @RowQuery was evaluated, causing the logic of adding "UNION ALL SELECT" in the right location to fail.

This surprised me because I don't usually think about the column execution order of a query. Normally column expressions in the SELECT statement are independent of each other so the order that the columns are executed in doesn't really matter. But in this example, the column execution order does matter and it's reassuring to see SQL Server do what I assumed it was doing.

Now, I can't guarantee this always works. I tried but failed to think of a scenario where SQL Server wouldn't execute the columns in sequential order. While the query seemed to work as expected in all of the tests I ran, I'll leave this observation open ended in case anyone has ever encountered a scenario or has any ideas of when SQL Server doesn't process SELECT statement expressions in the order they are listed.

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This week I want to share something that surprised me about using SQL Server's SET IDENTITY_INSERT statement.

I started with two tables with identity columns defined:

CREATE TABLE dbo.[User]
(
    Id int identity,
    UserName varchar(40)
);
CREATE TABLE dbo.StupidQuestions
(
    Id bigint identity,
    UserId int,
    Question varchar(400)
);


INSERT INTO dbo.[User] (UserName) VALUES ('Jim');
INSERT INTO dbo.[User] (UserName) VALUES ('Jane');
INSERT INTO dbo.[User] (UserName) VALUES ('Jin');
INSERT INTO dbo.[User] (UserName) VALUES ('Joyce');

INSERT INTO dbo.StupidQuestions (UserId,Question) VALUES (1,'Is smooth peanut butter better than chunky?');
INSERT INTO dbo.StupidQuestions (UserId,Question) VALUES (1,'Do I really need to backup my production databases?');
INSERT INTO dbo.StupidQuestions (UserId,Question) VALUES (2,'How to grant developers SA access?');
INSERT INTO dbo.StupidQuestions (UserId,Question) VALUES (3,'I''m getting an error about not being able to add any more indexes to my table - how do I increase the limit?');
INSERT INTO dbo.StupidQuestions (UserId,Question) VALUES (4,'How can I include more than 32 columns in my index key?');
GO

I wanted to copy the data from these two tables into two other tables:

CREATE TABLE dbo.User_DEV
(
    Id int identity,
    UserName varchar(40)
);

CREATE TABLE dbo.StupidQuestions_DEV
(
    Id bigint identity,
    UserId int,
    Question varchar(400)
);

This would allow me to safely test some changes on these _DEV table copies without breaking my original tables.

The next step was to write a couple of INSERT INTO SELECT statements:

INSERT INTO dbo.User_DEV
SELECT Id,UserName FROM dbo.[User]

INSERT INTO dbo.StupidQuestions_DEV
SELECT Id,UserId,Question FROM dbo.StupidQuestions

And of course as soon as I executed them SQL Server threw an error stating that I can't INSERT data into tables containing identity columns without first enabling identity inserts:

An explicit value for the identity column in table 'dbo.User_DEV' can only be specified when a column list is used and IDENTITY_INSERT is ON.

Ok, simple enough to fix: we just need to do what the error message says and SET IDENTITY_INSERT ON for both tables:

SET IDENTITY_INSERT dbo.User_DEV ON;  
SET IDENTITY_INSERT dbo.StupidQuestions_DEV ON;  

And... it still didn't work:

IDENTITY_INSERT is already ON for table 'IdentityTest.dbo.User_DEV'. Cannot perform SET operation for table 'dbo.StupidQuestions_DEV'.

One at a time

Although I've probably moved data around like this hundreds (thousands?) of times before, I've never encountered this particular error.

Apparently SQL Server only allows one table to have the IDENTITY_INSERT property enabled at a time within each session. The solution therefore is straightforward: enable identity inserts and copy each table's data one at a time:

SET IDENTITY_INSERT dbo.User_DEV ON; 
INSERT INTO dbo.User_DEV (Id,UserName)
SELECT Id,UserName FROM dbo.[User];
SET IDENTITY_INSERT dbo.User_DEV OFF; 

SET IDENTITY_INSERT dbo.StupidQuestions_DEV ON;
INSERT INTO dbo.StupidQuestions_DEV (Id,UserId,Question)
SELECT Id,UserId,Question FROM dbo.StupidQuestions
SET IDENTITY_INSERT dbo.StupidQuestions_DEV OFF;

20/20

In hindsight, I think I've never encountered this error before because I normally use the the Export Data Wizard in SSMS or a dedicated SSIS package to move data around. Either of those options are typically easier than writing T-SQL to move data across servers or for repeatability for when I need to regularly refresh tables with test data.

However, when using either of those options I've never paid attention to the implementation details, causing me to assume I knew how SQL Server handles identity inserts.

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A long time ago I built an application that captured user input. One feature of the application was to compare the user's input against a database of values.

The app performed this text comparison as part of a SQL Server stored procedure, allowing me to easily update the business logic in the future if necessary.

One day, I received an email from a user saying that the value they were typing in was matching with a database value that they knew shouldn't match. That is the day I discovered SQL Server's counter intuitive equality comparison when dealing with trailing space characters.

Padded white space

You are probably aware that the CHAR data type pads the value with spaces until the defined length is reached:

DECLARE @Value CHAR(10) = 'a'
SELECT
    @Value AS OriginalValue,
    LEN(@Value) AS StringLength,
    DATALENGTH(@Value) AS DataLength,
    CAST(@Value AS BINARY) AS StringToHex;

The LEN() function shows the number of characters in our string, while the DATALENGTH() function shows us the number of bytes used by that string.

In this case, DATALENGTH is equal to 10. This result is due to the padded spaces occurring after the character "a" in order to fill the defined CHAR length of 10. We can confirm this by converting the value to hexadecimal. We see the value 61 ("a" in hex) followed by nine "20" values (spaces).

If we change our variable's data type to VARCHAR, we'll see the value is no longer padded with spaces:

DECLARE @Value VARCHAR(10) = 'a'
SELECT
    @Value AS OriginalValue,
    LEN(@Value) AS StringLength,
    DATALENGTH(@Value) AS DataLength,
    CAST(@Value AS BINARY) AS StringToHex;

Given that one of these data types pads values with space characters while the other doesn't, what happens if we compare the two?

DECLARE 
    @CharValue CHAR(10) = '',
    @VarcharValue VARCHAR(10) = ''
SELECT
    IIF(@CharValue=@VarcharValue,1,0) AS ValuesAreEqual,
    DATALENGTH(@CharValue) AS CharBytes,
    DATALENGTH(@VarcharValue) AS VarcharBytes

In this case SQL Server considers both values equal, even though we can confirm that the DATALENGTHs are different.

This behavior doesn't only occur with mixed data type comparisons however. If we compare two values of the same data type, with one value containing several space characters, we experience something...unexpected:

DECLARE 
    @NoSpaceValue VARCHAR(10) = '',
    @MultiSpaceValue VARCHAR(10) = '    '
SELECT
    IIF(@NoSpaceValue=@MultiSpaceValue,1,0) AS ValuesAreEqual,
    DATALENGTH(@NoSpaceValue) AS NoSpaceBytes,
    DATALENGTH(@MultiSpaceValue) AS MultiSpaceBytes

Even though our two variables have different values (a blank compared to four space characters), SQL Server considers these values equal.

If we add a character with some trailing whitespace we'll see the same behavior:

DECLARE 
    @NoSpaceValue VARCHAR(10) = 'a',
    @MultiSpaceValue VARCHAR(10) = 'a     '
SELECT
    IIF(@NoSpaceValue=@MultiSpaceValue,1,0) AS ValuesAreEqual,
    DATALENGTH(@NoSpaceValue) AS NoSpaceBytes,
    DATALENGTH(@MultiSpaceValue) AS MultiSpaceBytes

Both values are clearly different, but SQL Server considers them to be equal to each other. Switching our equal sign to a LIKE operator changes things slightly:

DECLARE 
   @NoSpaceValue VARCHAR(10) = 'a',
   @MultiSpaceValue VARCHAR(10) = 'a     '
SELECT
   IIF(@NoSpaceValue LIKE @MultiSpaceValue,1,0) AS ValuesAreEqual,
   DATALENGTH(@NoSpaceValue) AS NoSpaceBytes,
   DATALENGTH(@MultiSpaceValue) AS MultiSpaceBytes

Even though I would think that a LIKE without any wildcard characters would behave just like an equal sign, SQL Server doesn't perform these comparisons the same way.

If we switch back to our equal sign comparison and prefix our character value with spaces we'll also notice a different result:

DECLARE 
    @NoSpaceValue VARCHAR(10) = 'a',
    @MultiSpaceValue VARCHAR(10) = '    a'
SELECT
    IIF(@NoSpaceValue=@MultiSpaceValue,1,0) AS ValuesAreEqual,
    DATALENGTH(@NoSpaceValue) AS NoSpaceBytes,
    DATALENGTH(@MultiSpaceValue) AS MultiSpaceBytes

SQL Server considers two values equal regardless of spaces occurring at the end of a string. Spaces preceding a string however, no longer considered a match.

What is going on?

ANSI

While counter intuitive, SQL Server's functionality is justified. SQL Server follows the ANSI specification for comparing strings, adding white space to strings so that they are the same length before comparing them. This explains the phenomena we are seeing.

It does not do this with the LIKE operator however, which explains the difference in behavior.

Comparisons when extra spaces matter

Let's say we want to do a comparison where the difference in trailing spaces matters.

One option is to use the LIKE operator as we saw a few examples back. This is not the typical use of the LIKE operator however, so be sure to comment and explain what your query is attempting to do by using it. The last thing you want is some future maintainer of your code to switch it back to an equal sign because they don't see any wild card characters.

Another option that I've seen is to perform a DATALENGTH comparison in addition to the value comparison:

DECLARE 
    @NoSpaceValue VARCHAR(10) = 'a',
    @MultiSpaceValue VARCHAR(10) = 'a    '
SELECT
    IIF(@NoSpaceValue = @MultiSpaceValue AND DATALENGTH(@NoSpaceValue) = DATALENGTH(@MultiSpaceValue),1,0) AS ValuesAreEqual,
    DATALENGTH(@NoSpaceValue) AS NoSpaceBytes,
    DATALENGTH(@MultiSpaceValue) AS MultiSpaceBytes

This solution isn't right for every scenario however. For starters, you have no way of knowing if SQL Server will execute your value comparison or DATALENGTH predicate first. This could wreck havoc on index usage and cause poor performance.

A more serious problem can occur if you are comparing fields with different data types. For example, when comparing a VARCHAR to NVARCHAR data type, it's pretty easy to create a scenario where your comparison query using DATALENGTH will trigger a false positive:

DECLARE 
    @NoSpaceValue VARCHAR(10) = 'a ',
    @MultiSpaceValue NVARCHAR(10) = 'a'
SELECT
    IIF(@NoSpaceValue = @MultiSpaceValue AND DATALENGTH(@NoSpaceValue) = DATALENGTH(@MultiSpaceValue),1,0) AS ValuesAreEqual,
    DATALENGTH(@NoSpaceValue) AS NoSpaceBytes,
    DATALENGTH(@MultiSpaceValue) AS MultiSpaceBytes

Here the NVARCHAR stores 2 bytes for every character, causing the DATALENGTHs of a single character NVARCHAR to be equal to a character + a space VARCHAR value.

The best thing to do in these scenarios is understand your data and pick a solution that will work for your particular situation.

And maybe trim your data before insertion (if it makes sense to do so)!

This past weekend I had a blast presenting Joker's Wild with Erin Stellato (blog|twitter), Andy Mallon (blog|twitter), and Drew Furgiuele (blog|twitter).

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Table of contents:

• What is Joker's Wild? Watch this to witness Andy's amazing PowerPoint animation skills (0:00)
• Bert demos SQL injection (2:25)
• Erin recollects desserts (9:55)
• Andy shares an automation tip (18:55)
• Andy explains an ANSI standard (23:10)
• Drew describes containers (27:02)

While a video doesn't quite give you the same experience as being in the room with dozens of other data professionals laughing and shouting along, hopefully it gives you an idea.

Here's a behind-the-scenes peek at how it all came together.

A Different Kind Of Presentation

I've wanted to do a "fun" SQL Server presentation for a while; something that would be lighthearted while still delivering (some) educational value.

I ran some ideas past Erin after SQL Saturday Cleveland earlier this year. We came up with several concepts ideas we could incorporate into the presentation (thanks to Paul Popovich and Luis Gonzalez for also helping us generate a lot of these ideas) and at that point I think Erin came up with the name "Joker's Wild."

Blind Commitment

Fast forward a few months: occasionally I'd talk about the presentation idea with people but still wasn't any closer to actually making it real.

Then a few days before the SQL Saturday Columbus submission deadline, Erin reached out to ask if we were going to submit. We recruited Andy and Drew to help present and submitted an abstract:

Come one, come all to the greatest (and only) SQL Server variety show at SQL Saturday Columbus.

This session features a smattering of lightning talks covering a range of DBA- and developer-focused SQL Server topics, interspersed with interactive games to keep the speakers and audience on their toes.

Plan for plenty of sarcasm, laughs, and eye rolls in this thoughtfully structured yet highly improvised session.

We can't guarantee what you'll learn, but we do promise a great time!

*Slot machine will not generate real money for "winners"

Structure

If that abstract reads a little vague, it's because at that point we didn't know exactly what we wanted to do yet. Once our session was selected though it was time to come up with a concrete plan (big thank you to David Maxwell and Peter Shore for giving us the opportunity to try something like this).

After some discussion, Erin, Andy, Drew, and I came up with the following structure:

1. The audience will choose the lightning talk topic
2. We will spin the "Wheel of Misfortune" to determine the presentation style, including:
   • Slides I didn't write
   • Random slide timing
   • Who has the clicker?
3. We will play some SQL Server themed Jeopardy and Pictionary with the audience

After our first meeting Andy created the world's most versatile PowerPoint presentation that would run the show. Seriously, if you haven't watched the video above yet, go watch it - that introduction is all PowerPoint goodness created by him.

The Session and Final Thoughts

I'm incredibly happy with how it all went. The session was planned but a lot of it was still left up to a highly improvised performance. I had a lot of fun preparing and presenting, and I think the session was well received by the audience. Jeopardy and Pictionary were a lot of fun too, even though I ran out of video recording space so I couldn't include them in the video.

I hope we have another opportunity to present this session again in the future.

Thank you again David and Peter for letting us do this session as part of SQL Saturday Columbus.

Thank you to our audience for taking a risk on attending a session you didn't know much about. Also for your great participation.

And thank you Erin, Andy, and Drew for helping do something fun and different.