6 Techniques For Troubleshooting Your Code

Published on: 2018-08-14

This post is a response to this month’s T-SQL Tuesday #105 prompt by Wayne Sheffield.  T-SQL Tuesday is a way for the SQL Server community to share ideas about different database and professional topics every month.

This month’s topic asks to share a time you ran into a metaphorical brick wall and how you worked it out.


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The Problem: Trimmed JSON Values

Recently I was using FOR JSON PATH to generate a JSON string from a query to use in a web app:

The resulting JSON string is 5,580 characters long.

The goal was to read this query result into my .NET app like so:

Is this the best way to design every app/database interaction?  Probably not, but it was right for this scenario because I didn’t want to create models for all of the dynamic data I’d be returning.

Design decisions aside, my “brick wall” issue was that my “jsonResult” value was getting truncated around 2,000 characters instead of displaying the full 5,580.  The JSON string looked great in SSMS, but for the life of me I couldn’t figure out why the data was getting chopped off when read into .NET.

Time to Debug

What follows are the usual steps I take when debugging a problem that has me stumped.  I’ve turned these into a 1950s style educational film so you can laugh at my bad jokes while your learn.

1. Rubber Duck Debugging

The first thing I usually do when I hit a wall like this is talk myself through the problem again.

This technique usually works well for me and is equivalent to those times when you ask  someone for help but realize the solution while explaining the problem to them.

To save yourself embarrassment (and to let your coworkers keep working uninterrupted), people often substitute an inanimate object, like a rubber duck, instead of a coworker to try and work out the problem on their own.

Alas, in this case explaining the problem to myself didn’t help, so I moved on to the next technique.

2. Simplify the Problem

Breaking a problem down into smaller solvable parts can help sometimes.  I changed my query to return less data by switching to SELECT TOP 5 and seeing if .NET was still truncating the data.  It wasn’t! Mildly successful!

In this case though, I couldn’t really build off my simplified example.  As soon as my result passed ~2,000 characters, the JSON string was getting chopped off.

In this step I also figured out if I put my query into a derived table, my .NET code worked beautifully and returned the complete JSON string:

This was an ugly solution though and I didn’t like doing it.  I especially didn’t like it because I didn’t know why a derived table fixed the output.

3. Check the Internet

As great as the internet is, I try to limit myself to how much searching I do on it when troubleshooting.  Searching for an online solution can quickly devolve into wasting two hours with nothing to show.

I performed some cursory searches on Google, StackOverflow, various forums, blogs, etc… but didn’t find anything helpful (fun/sad fact: I searched for solutions again while typing up this post and now find plenty of solutions…who knows what I was doing wrong that day).

4. Ask a Friend

I love working through problems with others because I’m often amazed at how differently others approach a problem.  Often times this leads to a solution I would not have thought of on my own.  I especially enjoy hearing from people new to the subject area because they often have the most creative solutions due to not yet having become cynical and jaded from previous experience :).

I try to hold off on this option until at least trying all of the above techniques because 1) I hate breaking another person’s concentration 2) I feel like I learn better if I struggle through a problem myself.

And in this case shopping the problem around didn’t help – no one I talked to had a great solution.

5. Take a Break

After trying all of the above, I was out of ideas.  I took a break from the problem for the rest of the day, resolved to give it another try in the morning the morning.

6. RTFM

And the next morning, I had the idea to check the documentation to see what it said about the return type of FOR JSON PATH.

Embarrassingly, this one should be way higher on the list, and I’d like to say that it usually is, but for one reason or another I didn’t bother checking until this late in the game.

And wouldn’t you know it?  The last paragraph, of the last section, tells me exactly what I needed to know.

The documentation tells me that the JSON string will be broken up across multiple rows and my client app needs to concatenate them all together.  What I ended up doing is a simple String.Join():

There’s no explanation for why SSMS is able to concatenate these values together but other client apps have to manually do so, but at least I found my documented solution.

Conclusion

Even though I found a somewhat-satisfactory solution in the documentation, my fall back was going to be to use the ugly derived table solution discovered in step 2.  It was ugly, but at some point I would have to call it quits and settle with an ugly workaround rather than spend more time on troubleshooting.

Next time I’ll be sure to check the documentation earlier in the process and hopefully that will save me from some of the frustration I encountered in this particular scenario.

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Displaying Long Values in SSMS

Published on: 2018-08-07

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I write a lot of dynamic SQL and frequently encounter variables that contain many characters:

This variable is 4059 characters long, and when I execute it it runs great.

A homage to one of my favorite Uncyclopedia entries.

If my programmatically built query had an error in it, the first thing I’d want to do when debugging it would be to see the the text of the entire @LongValue variable.

I could do this by just saying SELECT @LongValue, and while recent versions of SSMS will display the whole value for me, it completely loses my formatting which stinks (and is especially bad if there are any comments prefixed with --  in the query):

Need a ultra HD wide display to fit this all on one screen.

I can say PRINT @LongValue, which will keep the formatting, but it will get trimmed at 4,000 characters (notice the missing ORDER BY):

Some Better Ways

Erik Darling posts one solution to this problem in his T-SQL Tuesday #104 entry (as well as some other problems/solutions for lengthy SQL variables). Specifically he links to a SQL string printing script that will loop through the lengthy variable and print everything while maintaining formatting:

Not perfectly formatted, but good enough.

And while I like using that stored procedure on my primary server, I’m too lazy to install it every where I need it.

Instead, I have a couple of go-to solutions that work on all SQL Server instances 2008 forward.

Solution 1: CAST to XML

Casting the long variable to XML allows SSMS to generate a clickable, single-row result that preserves formatting:

IntelliSense complains but I’m OK with it

The only downside to this approach is that certain charaters, like “<” and “>”, can’t be converted to XML:

Solution 2: FOR XML PATH

A slight variation on solution 1, we can get similar results using FOR XML PATH:

FOR XML PATH is one of the most abused SQL Server functions.

In this solution, the “<” is escaped to “&lt;”, which isn’t perfect but at least my variable can be displayed with formatting intact.  A quick find and replace for any escaped characters and I’m good to go.

Good Enough

These techniques aren’t perfect, but for purposes of debugging dynamically generated code they are good enough.

Maybe one day SSMS will print longer strings or include a syntax formatter and I won’t care nearly as much.

And if not, I’ll happily continue to abuse FOR XML to do things other than generate XML documents.

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Should You Use Index Hints?

Published on: 2018-07-31

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One of the things that the SQL Server query optimizer does is determine how to retrieve the data requested by your query.

Usually it does a pretty good job, which is a great because if it didn’t then we’d be spending most of our days programming sorting and joining algorithms instead of having fun actually working with our data.

Sometimes the query optimizer has a lapse in judgement and createds a less-than-efficient plan, requiring us to step in and save the day.

Index Hints Give You Control

One way to “fix” a poor performing plan is to use an index hint.  While we normally have no control over how SQL Server retrieves the data we requested, an index hint forces the  query optimizer to use the index specified in the hint to retrieve the data (hence, it’s really more of a “command” than a “hint”).

Sometimes when I feel like I’m losing control I like using an index hint to show SQL Server who’s boss.  I occasionally will also use index hints when debugging poor performing queries because it allows me to confirm whether using an alternate index would improve performance without having to overhaul my code or change any other settings.

…But Sometimes That’s Too Much Power

While I like using index hints for short-term debugging scenarios, that’s about the only time they should be used because they can create some pretty undesirable outcomes.

For example, let’s say I have this nice simple query and index here:

This index was specifically created for a different query running on the Posts table, but it will also get used by the simple query above.

Executing this query without any hints causes SQL Server to use it anyway (since it’s a pretty good index for the query), and we get decent performance: only 1002 logical reads.

I wish all of my execution plans were this simple.

Let’s pretend we don’t trust the SQL Server optimizer to always choose this index, so instead we force it to use it by adding a hint:

With this hint, the index will perform exactly the same: 1002 logical reads, a good index seek, etc…

But what happens if in the future a better index gets added to the table?

If we run the query WITHOUT the index hint, we’ll see that SQL Server actually chooses this new index because it’s smaller and we can get the data we need in only 522 logical reads:

This execution plan looks the same, but you’ll notice the smaller, more data dense index is being used.

If we had let SQL Server do it’s job, it would have given us a great performing query!  Instead, we decided to intervene and hint (ie. force) it to use a sub-optimal index.

Things Can Get Worse

The above example is pretty benign – sure, without the hint SQL Server would have read about half as many pages, but this isn’t a drastic difference in this scenario.

What could be disastrous is if because of the hint, the query optimizer decides to make a totally different plan that isn’t nearly as efficient.  Or if one day someone drops the hinted index, causing the query with the hint to down right fail:

Index hints  can be nice to use in the short-term for investigating, testing, and debugging.  However, they are almost never the correct long-term solution for fixing query performance.

Instead, it’s better to look for the root-cause of a poor performing query: maybe you need to rebuild stats on an index or determine if the cardinality estimator being used is not ideal.  You might also benefit from rewriting a terribly written query.

Any of these options will likely help you create a better, long-term, flexible solutions rather than forcing SQL Server to use the same hard-coded, potentially sub-optimal index forever.

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