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Category: T-SQL

Making Near-Zero Downtime Deployments Easier

I continue my series on developing for near-zero downtime deployments:

By default, SQL Server uses pessimistic locking, meaning that readers can block writers, writers can block readers, and writers can block writers. In most circumstances, you can switch from Read Committed to Read Committed Snapshot Isolation and gain several benefits. RCSI has certainly been in the product long enough to vet the code and Oracle has defaulted to an optimistic concurrency level for as long as I can remember.

The downtime-reducing benefit to using RCSI is that if you have big operations which write to tables, your inserts, updates, and deletes won’t affect end users. End users will see the old data until your transactions commit, so your updates will not block readers. You can still block writers, so you will want to batch your operations—that is, open a transaction, perform a relatively small operation, and commit that transaction. I will go into batching in some detail in a later post in the series, so my intent here is just to prime you for it and emphasize that Read Committed Snapshot Isolation is great.

Now that I have the core concepts taken care of, the next posts in the series move into practical implementation examples with a lot of code.

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UNCOMPRESS Isn’t DECOMPRESS

Solomon Rutzky strives to solve the question, “What is the UNCOMPRESS function anyhow?”:

With no clear indications of what the UNCOMPRESS function does, we can at least pass in some simple values to see what comes back, and see if we can make sense of the output. For the following tests, please keep in mind that “8-bit” refers to the VARCHARCHAR, and TEXT (deprecated) datatypes. And, “16-bit” refers to the NVARCHARNCHARNTEXT (deprecated),and XML datatypes.

Read on as Solomon figures out what it does and how non-useful it is for anybody nowadays.

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Generating Reference Numbers With Sequences

Matthew McGiffen shares one technique to generate reference numbers using a sequence and the FORMAT function:

One thing to note is that, while the sequence will generally produce unique number, it is still worth enforcing that in your table definition with a unique constraint i.e.

ALTER TABLE dbo.Orders ADD CONSTRAINT UQ_Orders_OrderReference UNIQUE(OrderReference);

This prevents someone from issuing an UPDATE command that might create a duplicate reference. 

As long as you can live with the occasional gap in your reference number, sequences are a good solution to the problem.

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ISNUMERIC And Unexpected Results

Jen Stirrup explains why ISNUMERIC isn’t all that great:

I noted that one of the columns failed to convert VARCHAR to DECIMAL.

The error message is below, and it’s usually fairly easy to sort:
Error converting data type varchar to numeric

Normally, I’d use ISNUMERIC to identify the rows that fail to have a value in that column that could be converted to a number. Then, I could identify the value, and then I could replace or exclude it, as required.

However, on this occasion, using ISNUMERIC failed to identify any columns as being non-numeric. 

Click through to see why Jen got this result.

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sp_executesql WITH RECOMPILE

Erik Darling points out that running sp_executesql with the WITH RECOMPILE setting doesn’t really change anything:

This’ll give us the key lookup plan you see above. If I re-run the query and use the 2010-12-30 date, we’ll re-use the key lookup plan.

That’s an example of how parameters are sniffed.

Sometimes, that’s not a good thing. Like, if I passed in 2008-12-30, we probably wouldn’t like a lookup too much.

One common “solution” to parameter sniffing is to tack a recompile hint somewhere.

Click through for Erik’s demonstration.

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Using Calendar Tables

I have a post up on using calendar tables:

There’s one problem with picking a SQL Saturday in April: Easter and Passover tend to run right around that time, and nobody wants a SQL Saturday on Passover or the day before Easter. Unfortunately, our calendar table doesn’t include holiday information. So let’s add it!

Working with holidays and working with fiscal years versus calendar years are just two of the uses of calendar tables. But they’re the only two that I show.

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A Rant About ORMs

Ned Otter is not a fan of ORMs:

I’ve seen a lot of tech come and go in my time, but nothing I’ve seen vexes me more than “framework generated SQL”.  No doubt I’m ignorant about some aspects of it, but its usage continues to confound many a DBA.

To troubleshoot one of these bad boys, you might consider Google Glass, but it will fail you. The first issue is that these crappy frameworks generate a code tsunami that’s almost (or actually) unreadable by humans. The tables you know and love are aliased with names such as “Extent1” and the like. Multiple nestings of that, and it’s all gobbledygook aka spaghetti code.

These work great as long as you have more hardware to throw at the problem.

I would differentiate here a micro-ORM like Dapper from a Hibernate or Entity Framework like Ned has in mind, where the difference is that Dapper acts as a way of automating the data access layer but you still write the SQL queries or stored procedures.

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Building A Calendar Table

I have a post up on building a calendar table:

Another thing to keep in mind here is that you’re only going to load your calendar table once, so if it takes two minutes to do, who really cares? The version I have should run reasonably fast–I calculated 726 years on slow hardware in 19 seconds and fast hardware in 11 seconds. I’m sure you can play code golf and get it done faster, but that’s probably not a good use of your time.

What you want to sweat instead is query time: how long is it taking to access this data?

Click through for a script.

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