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Category: T-SQL Tuesday

Heaps Of Fun

Rob Farley talks about an issue with heaps:

What I found was that the list of IDs was being stored in a table without a clustered index. A heap. Now – I’m not opposed to heaps at all. Heaps are often very good, and shouldn’t be derided. But you need to understand something about heaps – which is that they’re not suited to tables that have a large amount of deletes. Every time you insert a row into a heap, it goes into the first available slot on the last page of the heap. If there aren’t any slots available, it creates a new page, and the story continues. It doesn’t keep track of what’s happened earlier. They can be excellent for getting data in – and Lookups are very quick because every row is addressed by the actual Row ID, rather than some key values which then require a Seek operation to find them (that said, it’s often cheap to avoid Lookups, by adding extra columns to the Include list of a non-clustered index). But because they don’t think about what kind of state the earlier pages might be in, you can end up with heaps that are completely empty, a bunch of pointers from page to page, with header information, but no actual rows therein. If you’re deleting rows from a heap, this is what you’ll get.

This guy’s heap had only a few rows in it. 8 in fact, when I looked – although I think a few moments later those 8 had disappeared, and were replaced by 13 others.

But the table was more than 400MB in size. For 8 small rows.

Read the whole thing, including Rob’s reluctance to post on this topic.

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Test Accounts

Andy Yun had the task of cleaning up test accounts:

Monday morning came along and as scheduled, our Production DBAs executed my script before start of business. 30 minutes later, the frantic calls started to reach us. Seems some of our clients could no longer “make widgets!” Accounts that they needed to route data were gone! My manager and I looked at one another in horror – we were only deleting internal accounts!!! We didn’t hesitate and immediately had our Prod DBAs back out the change with my backout script, before the rest of the United Stated started business. The backout was executed immediately and all was back to normal, but business folks were pissed and wanted to know what happened.

It was good foresight to have a backout script.

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Rolling The CHECKDB Dice

Arun Sirpal tells a harrowing story of a Recovery Pending situation:

Looks like I had open transactions while my transaction log got lost during an outage. I tried switching the database online but that failed.

Msg 5181, Level 16, State 5, Line 4 Could not restart database “FAT”. Reverting to the previous status. Msg 5069, Level 16, State 1, Line 4 ALTER DATABASE statement failed.

Accessing the database is the real challenge now.

Moral of the story:  have backups and have good luck.

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T-SQL Tuesday 87 Roundup

Matt Gordon has the roundup for T-SQL Tuesday 87:

Finally, as a first time host, I was obviously hoping that this topic would garner some responses, but you never know until you hit that post button whether you’ve selected something of interest to the community or not. Thankfully, this month’s topic picked up views from over 20 countries and over 20 blog responses. The list (with a brief post-by-post commentary from me) is below. Happy reading and thanks again for reading/writing/participating!

Read on for the full list of respondents.

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String Splitting And Concatenation

Aaron Bertrand and Steve Hughes talk about string splitting, and Aaron also discusses string concatenation.  First Aaron:

That may not look like a massive simplification, but don’t forget about all the logic buried behind the table-valued function in the first example. And if you’re like several shops I know, if you look across your codebase and see all the messy uses you have for either of these methods, the benefits should be even more clear – and testing should bear that the performance savings compared to traditional, expensive methods are the sweetest part of the deal.

And Steve:

The STRING_SPLIT function will return a single column result set. The column name is “value”. The datatype will be NVARCHAR for strings that are NCHAR or NVARCHAR. VARCHAR is used for strings that are CHAR or VARCHAR types.

These two functions are small, but come in handy quite frequently.

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AT TIME ZONE And Reports

Rob Farley shows how to use AT TIME ZONE without sacrificing performance:

Because how am I supposed to know whether a particular date was before daylight saving started or after? I might know that an incident occurred at 6:30am in UTC, but is that 4:30pm in Melbourne or 5:30pm? Obviously I can consider which month it’s in, because I know that Melbourne observes daylight saving time from the first Sunday in October to the first Sunday in April, but then if there are customers in Brisbane, and Auckland, and Los Angeles, and Phoenix, and various places within Indiana, things get a lot more complicated.

To get around this, there were very few time zones in which SLAs could be defined for that company. It was just considered too hard to cater for more than that. A report could then be customised to say “Consider that on a particular date the time zone changed from X to Y”. It felt messy, but it worked. There was no need for anything to look up the Windows registry, and it basically just worked.

But these days, I would’ve done it differently.

Now, I would’ve used AT TIME ZONE.

Read on for the scenario.

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Instant File Initialization In DMVs

Rodney Landrum shows off a couple new columns in SQL Server 2016 SP1 DMVs:

Microsoft announced many new features in SQL Server 2016 SP1 and the fanfare was mostly centered around the Enterprise features now available in SQL Server 2016 Standard Edition.  Many may have missed some hidden gems in the announcement.  Two of these are columns added to the existing DMVs, sys.dm_server_services and sys.dm_os_sys_info. The columns provide information for two specific features that previously had to be gathered by opening gpedit.msc and/or scrolling through SQL error logs. I am referring to Lock Pages in Memory and Instant File Initialization (enabled via Perform Volume Maintenance Tasks privilege).

It is now possible to simply query the DMVs to determine if these are being used for the running SQL Server instance.

Click through for the details.

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Session Context

Ewald Cress looks at SESSION_CONTEXT() as a replacement for CONTEXT_INFO():

SESSION_CONTEXT() brings two major innovations. Firstly, it replaces a 128-byte scalar payload with a key-value structure that can accommodate 256kB of data. You can really go to town filling this thing up.

The second change is less glamorous, but possibly more significant: it is possible to set an entry to read-only, meaning that it can safely be used for the kind of contextual payload you don’t want tampered with. This makes me happy, not because I currently have a great need for it, but because it neatly ties in with things I have been thinking about a lot lately.

Read on for more.

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Calculated Dimensions

Ginger Grant shows how calculated dimensions can solve the classic role-playing dimension problem in Analysis Services Tabular:

Working with role playing dimensions, which are found when you have say multiple dates in a table and you want to relate them back to a single date table, have always been problematic in SQL Server Analysis Services Tabular. Tabular models only allow one active relationship to a single column at a time. The picture on the left shows how tabular models represent a role playing dimension, and the model on the right is the recommended method for how to model the relationships in Analysis Services Tabular as then users can filter the data on a number of different date tables.

The big downside to this is one has to import the date table into the model multiple times, meaning the same data is imported again and again. At least that was the case until SQL Server 2016 was released. This weeks TSQL topic Fixing Old Problems with Shiny New Toys is really good reason to describe a better way of handling this problem.

Read on for how to implement calculated dimensions.

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Not All Shiny Toys Are Good

Wayne Sheffield rains on our parade:

There are other issues with the MERGE statement. It has bugs… some of which can cause database corruption.

Here we have a Shiny New Toy (feature), supposed to make life easier, yet it causes problems. Until it can perform better (and the bugs are eliminated), I just don’t use it.

Beware the Shiny New Toys.

Wayne makes a great point.  Not all new things are good, even when they’re potentially quite useful.  I love shiny new toys a lot, but part of being a database administrator is protecting data, and part of that means being able to trust your tools.  Sometimes the tools work really well right out of the gate, and sometimes (like in the case of MERGE) they don’t.

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