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Author: Kevin Feasel

Max And Min Decimal Values

Published 2016-06-01 by Kevin Feasel

Robert Davis gives us the formula for the max and min decimal values given a scale and precision:

Unfortunately, the mathematical approach has flaws. First of all, Power(10, 38) exceeds the range of any numerical data type in SQL Server. There is no way to store or work with this value in calculations. Secondly, once you try to raise 10 to a power greater than 30, you start seeing floating point calculations (the values are approximate). For example, select Power(Cast(10 as decimal(38, 0)), 31) — casting as decimal(38, 0) because it exceeds int or bigint — yields 9999999999999999600000000000000. That’s clearly an approximated value and is not going to work for calculations where we’re expecting a precise value. So, that leaves the hacky version I didn’t want to do because I just cannot count on the mathematical approach working. Here is the base query using the hacky calculation

Read on for the hacky version.

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Bidirectional Cross-Filtering And M

Published 2016-05-31 by Kevin Feasel

Chris Webb shows how to create a report with with a single slicer that allows the ability to show data for the current day, week, month, and year:

The way to achieve this is not all that different from the calculated column approach, but it requires a separate table to model the many-to-many relationship between all the required relative period selections and the dates in them, as well as the use of bidirectional cross-filtering between tables (which I blogged about here). The data model I used for this report looks like this

Be sure to read the comments to make sure you don’t get into a scenario in which a user can select multiple periods and get duplicated data.

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Undocked Query Windows

Published 2016-05-31 by Kevin Feasel

Michael Swart notes that undocked query windows now feel all grown up:

The March 2016 Refresh (13.0.13000.55 Changelog) updates SSMS to use the new Visual Studio 2015 shell. Part of that change means that undocked windows are now top-level windows.

Top level windows are windows without parents so the undocked window is not a child window of the main SSMS window (but it is part of the same process). And so it gets its own space in the task bar, and participates in alt+tab when you switch between windows.

Also these undocked windows can be a collection of query windows.

One reason I rarely used child windows is that I’d undock something, switch to a browser tab underneath, and then switch back and watch the undocked window pop over my browser tab.  This sounds like a good improvement.

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Columnstore Replication

Published 2016-05-31 by Kevin Feasel

Niko Neugebauer notes that certain columnstore index types are now supported for replication in SQL Server 2016:

At this point you can notice, that from our 3 tables there are only 2 are available for the transactional replication, with the disk-based table with a Clustered Columnstore Index is not being available for the replication.
This means that there are no improvements since SQL Server 2014 for the DWH/BI scenarios in this direction and this is definitely sad.
Well, we can always go a different direction, like in the case of Availability Groups in SQL Server 2014, where readable secondaries are supported only for the Nonclustered Columnstore Indexes. In SQL Server 2016 we can use Nonclustered Columnstore Index even on all columns if needed and get the principle improvements for the Batch Execution Mode.

Notice here that even though we can select the InMemory tables with Clustered Columnstore, there are a couple of additional important settings that needs to be configured to make things function. So clicking through the GUI Wizard will not set things correctly up by default.

The short answer, Niko states, is that you can only replicate non-clustered columnstore indexes at this time.  I can see some use for replicating clustered columnstore tables (warehouse scale-out scenarios, perhaps), but it  wasn’t at the top of my columnstore improvement list.

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Parallel Maintenance Tasks

Published 2016-05-31 by Kevin Feasel

Jonathan Kehayias shows how to parallelize Ola’s maintenance tasks using Service Broker:

With that setup, now we need to build an activation stored procedure to process the messages from the queue and perform the operations generated by Ola’s scripts.  At first I thought that this would be pretty straightforward, but it actually required a fair amount of additional logic to prevent poison messages and queue deactivation from occurring when multiple online index rebuilds were attempted on the same table.  When this occurs the engine raises Error 1912:

Could not proceed with index DDL operation on %S_MSG ‘%.*ls’ because it conflicts with another concurrent operation that is already in progress on the object. The concurrent operation could be an online index operation on the same object or another concurrent operation that moves index pages like DBCC SHRINKFILE.

which causes the XACT_STATE() of the operation to become –1, which only allows the transaction processing the command to be rolled back, leading to a poison message within Service Broker.  So to mitigate against that I had to add in a check against sys.dm_tran_locks for any ALTER_INDEX command to identify if a conflicting lock is currently being held and if it is then we just requeue the message and increment the retry count held within the message so that we can incrementally back-off attempting to run the command each time it encounters a conflicting lock using a WAITFOR.  Since Ola’s scripts log the command type, database name, object name, and command to be executed to the CommandLog table in the master database, all we need to queue in our message is the ID of the command to be processed by Service Broker, and we can get the rest of the pertinent information from the CommandLog table directly.  As a part of each tasks execution in our activation stored procedure we will also update the StartTime and EndTime of the operation for historical trending of execution durations.

This is a clever use of Service Broker, and I’m glad Jonathan shared his code.  Also check out his Pluralsight course for another good use of Service Broker.

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Project Parameters In Biml

Published 2016-05-31 by Kevin Feasel

Catherine Wilhelmsen explains why you cannot create project parameters using Biml:

SSIS project parameters do not work the same way as SSIS packages. All project parameters are stored as XML elements in a single XML document for the entire project called Project.params. This is the core reason why packages have a good overwrite story while parameters have a poor overwrite story.

It should be obvious that BimlExpress can’t just overwrite your Project.params file. Of course, BimlExpress would be creating the parameters you specified in your BimlScripts, but it would also be overwriting any parameters you might have created manually. If you are a Biml purist, you might not care about this, because you would be fine with creating all of your project parameters through Biml. Unfortunately, most Biml users are not Biml purists – and even fewer development teams are Biml purists.

It’s a bit of a tricky situation for those cases in which you do want a pure Biml solution, and I’m glad Catherine got down to the bottom of it.

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SQL Licenses On Azure

Published 2016-05-31 by Kevin Feasel

Kenneth Nielsen notes that you can now bring your own SQL Server licenses to Azure marketplace images:

A few days ago, we announced that Microsoft Enterprise customers is now allowed to bring their own SQL Licenses to Azure VMs. This means that if a customer already have a SQL License, this license can be used on SQL Server VM images from Marketplace.

This means that they do no longer need to build their own VM, but instead can just provision a server from the marketplace and use the existing license.

I like this, but I do wonder what percentage of people will use marketplace-created VMs instead of customizing their own builds.

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Codd’s Twelve Rules

Published 2016-05-30 by Kevin Feasel

E.F. Codd’s 12 rules (well, thirteen):

Twelve rules are cited below as part of a test to determine whether a product that is claimed to be fully relational is actually so. Use of the term “fully relational” in this report is slightly more stringent than in my Turing paper (written in 1981). This is partly because vendors in their ads and manuals have translated the term “minimally relational” to “fully relational” and partly because in this report, we are dealing with relational DBMS and not relational systems in general, which would include mere query-reporting systems.

However, the 12 rules tend to explain why full support of the relational model is in the users’ interest. No new requirements are added to the relational model. A grading scheme is later defined and used to measure the degree of fidelity to the relational model.

This particular article seems less important thirty years later, but it was vital in the early days of relational systems to understanding what, precisely, a relational database management system ought to do and—just as importantly—what it ought not do.  It wasn’t enough to slap SQL on top of a hierarchical database platform and call it relational.

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