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Author: Kevin Feasel

SQL Order Of Operations

Published 2016-12-12 by Kevin Feasel

Lukas Eder explains order of operations in a SQL query:

If you’re not a frequent SQL writer, the syntax can indeed be confusing. Especially GROUP BY and aggregations “infect” the rest of the entire SELECT clause, and things get really weird. When confronted with this weirdness, we have two options:

  • Get mad and scream at the SQL language designers
  • Accept our fate, close our eyes, forget about the snytax and remember the logicaloperations order

I generally recommend the latter, because then things start making a lot more sense, including the beautiful cumulative daily revenue calculation below, which nests the daily revenue (SUM(amount) aggregate function) inside of the cumulative revenue (SUM(...) OVER (...)window function):

Lukas explains things from an Oracle perspective, so not all of this matches T-SQL, but it’s close enough for comparison.

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NOLOCK, No Problem?

Published 2016-12-12 by Kevin Feasel

Arun Sirpal explains that NOLOCK not only takes locks, but also lets you read invalid data:

A Sch-S (schema stability) lock is taken.  This is a lightweight lock; the only lock that can conflict with this is a Sch-m (schema modification) lock. (C = Conflict). This means that a NOLOCK can actually block for example against an ALTER TABLE command.

I would lean heavily toward turning on Read Committed Snapshot Isolation instead of using NOLOCK in most environments.  It’s something you’d need to test, but it does come with fewer bad ramifications.

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Parameterized Visibility In SSRS Reports

Published 2016-12-12 by Kevin Feasel

Monica Rathbun shows how to show or hide clusters of columns in Reporting Services reports:

Ever had users come to you and request another version of a report just to add another field and group data differently? Today, was such the day for me. I really don’t like have multiple versions of the same report out there. So, I got a little fancy with the current version of the report and added a parameter then used expressions to group the data differently and hide columns. For those new to SSRS I’ve embedded some links to MSDN to help you along the way.

This is an easy-to-follow, step-by-step guide.

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Synchronous Or Asynchronous Stats Updates

Published 2016-12-12 by Kevin Feasel

SQL Scotsman explains synchronous versus asynchronous stats updates:

With that said, it would seem that asynchronous statistics are better suited to OLTP environments and synchronous statistics are better suited to OLAP environments.  As synchronous statistics are the default though, people are reluctant to change this setting without good reason to.  I’ve worked exclusively in OLTP environments over the last few years and have never seen asynchronous statistics rolled out as the default.  I have personally been bitten by synchronous statistic updates on large tables causing query timeouts which I resolved by switching to asynchronous statistic updates.

This is an interesting, nuanced take on the issue.  My bias is toward asynchronous stats updates because I have been burned, but it’s interesting to read someone thinking through the implications of this seemingly simple choice.

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Passing Parameters To SQL Queries Via Power BI

Published 2016-12-12 by Kevin Feasel

Chris Webb shows how to use the Value.NativeQuery() function to pass parameters to SQL Server queries:

It looks like, eventually, this will be the way that any type of ‘native’ query (ie a query that you write and give to Power Query, rather than a query that is generated for you) is run against any kind of data source – instead of the situation we have today where different M functions are needed to run queries against different types of data source. I guess at some point the UI will be updated to use this function. I don’t think it’s ‘finished’ yet either, because it doesn’t work on Analysis Services data sources, although it may work with other relational data sources – I haven’t tested it on anything other than SQL Server and SSAS. There’s also a fourth parameter for Value.NativeQuery() that can be used to pass data source specific options, but I have no idea what these could be and I don’t think there are any supported for SQL Server. It will be interesting to see how it develops over the next few releases.

It’s good to know that you can parameterize queries now.

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The Limits Of SP1

Published 2016-12-12 by Kevin Feasel

Parikshit Savjani explains limitations in SQL Server 2016 SP1:

With the recent announcement of SQL Server 2016 SP1, we announced the consistent programmability experience for developers and ISVs, who can now maintain a single code base and build intelligent database applications which scale across all the editions of SQL Server. The processor, memory and database size limits does not change and remain as–in all editions as documented in the SQL Server editions page. We have made the following changes in our documentation to accurately reflect the memory limits on lower editions of SQL Server. This blog post is intended to clarify and provide more information on the memory limits starting with SQL Server 2016 SP1 on Standard, Web and Express Editions of SQL Server.

The development space has been expanded, but there’s still good reason for enterprises to use Enterprise Edition.

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ETL With Spark

Published 2016-12-09 by Kevin Feasel

Eric Maynard demonstrates that moving data across Hadoop clusters can be sped up by using Spark:

By leveraging Spark for distribution, we can achieve the same results much more quickly and with the same amount of code. By keeping data in HDFS throughout the process, we were able to ingest the same data as before in about 36 seconds. Let’s take a look at Spark code which produced equivalent results as the bash script shown above — note that a more parameterized version of this code code and of all code referenced in this article can be found down below in the Resources section.

Read the whole thing.

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SSAS Tabluar RAM Requirements

Published 2016-12-09 by Kevin Feasel

Bill Anton looks at ensuring your Tabular server has enough RAM:

In addition to being an “in-memory” technology, Analysis Services Tabular is also a “column-store” technology which means all the values in a table for a single column are stored together. As a result – and this is especially true for dimensional models – we are able to achieve very high compression ratios. On average, you can expect to see compression ratios anywhere from 10x-100x depending on the model, data types, and value distribution.

What this ultimately means is that your 2 TB data mart will likely only requrie between 20 GB of memory (low-end) and 200 GB (high-end) of memory. That’s pretty amazing – but still leaves us with a fairly wide margin of uncertainty. In order to further reduce the level of uncertainty, you will want to take a representative sample from your source database, load it into a model on a server in your DEV environment, and calculate the compression factor.

Read the whole thing; Bill has several factors he considers when sizing a machine.

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SQL Server Port Changes

Published 2016-12-09 by Kevin Feasel

Steve Jones shows how to change the port of your SQL Server instance:

Notice that I have multiple instances here, so I need to choose one. Once I do, I see the protocols on the right. In this case, I want to look at the properties of TCP/IP, which is where I’ll get the port.

If I look at properties, I’ll start with the Protocol tab, but I want to switch to the IP Addresses tab. In here, you can see I’ll see an entry for each of the IPs my instance is listening on. I can see which ones are Active as well as the port. In my case, I have these set to dynamic ports.

My rules of thumb, which might differ from your rules of thumb:  disable the Browser, don’t change off of 1433 for a single instance, and hard-code ports if you happen to be using named instances.  There’s a small argument in favor of “hiding” your instance by putting it onto a higher port (i.e., 50000+), but that’s not a great way of protecting a system, as an attacker can run nmap (or any other port scanner) and find your instance.  The major exception to this is if you also have something like honeyports set up.  In that case, changing the port number can increase security, and will almost definitely increase the number of developers who accidentally get blackholed from the server.

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