Press "Enter" to skip to content

Curated SQL Posts

Fixing Windows Power Settings

Published 2019-08-30 by Kevin Feasel

Jeff Iannucci takes us through power settings within T-SQL:

Well, not exactly, but it’s definitely like that. The default Power Setting is “Balanced” which means during periods of lower activity the clock speeds of your CPUs are reduced to conserve power and save your battery.

Apparently all Windows installations think they are on laptops. SPOILER ALERT: your database servers are probably not laptops.

Jeff has a T-SQL script to fix this. Unfortunately, it won’t fix the other power-based performance killer: power settings in BIOS.

Comments closed

Understanding Power BI Data Virtualization Queries

Published 2019-08-30 by Kevin Feasel

Gerhard Brueckl walks us through a few examples of queries Power BI makes when virtualizing data:

Even though this query only touches two different data sources, it is a good way to analyze the queries sent to the data sources. To track these queries I used the built-in Performance Analyzer of Power BI desktop which can be enabled on the “View”-tab. It gives you detailed information about the performance of the report including the actual SQL queries (under “Direct query”) which were executed on the data sources. The plain text queries can also be copied using the “Copy queries” link at the bottom.

Read on for the queries and for Gerhard’s analysis.

Comments closed

AzCopy, Batch Files, and the Task Scheduler

Published 2019-08-30 by Kevin Feasel

Randolph West shares the results of persistent, relentless experimentation:

This coincidentally has caused an issue if we are using Windows Task Scheduler to schedule the synchronization process, especially if we use a SAS (Shared Access Signature) token which can be quite long. What then happens is we have a command that is longer than Windows Task Scheduler allows, and the task will fail with a very unhelpful error message:

Task Scheduler failed to execute task "\AzureBlobStorageSync". Attempting to restart. Additional Data: Error Value: 2147942487.

Click through to see how Randolph fixed this problem, which created a new problem necessitating Randolph solve it as well.

Comments closed

Estimates outside the Histogram Range

Published 2019-08-30 by Kevin Feasel

Josh Darnell shows us how SQL Server calculates estimates for input values outside of the range of your relevant statistic’s histogram:

I have the impression that CSelCalcColumnInInterval “fails” if the predicate doesn’t fall within any of the histogram intervals. The estimation logic then chooses to try the CSelCalcAscendingKeyFiltercalculator (a reference to the “ascending key problem”) if the predicate is specifically higher than the last histogram interval.

Josh includes a couple of demos as well, so check them out.

Comments closed

Checking Spark Config on Windows

Published 2019-08-29 by Kevin Feasel

Ed Elliott has a Powershell script to tell you if your Spark configuration on Windows is incorrect:

There are some pretty common mistakes people make (myself included!), most common I have seen recently have been having a semi-colon in JAVA_HOME/SPARK_HOME/HADOOP_HOME or having HADOOP_HOME not point to a directory with a bin folder which contains winutils.

To help, I have written a small powershell script that a) validates that the setup is correct and then b) runs one of the spark examples to prove that everything is setup correctly.

Click through for the script.

Comments closed

Eliminating Tail Calls in Python

Published 2019-08-29 by Kevin Feasel

John Mount shows how you can eliminate tail calls in Python:

I was working through Kyle Miller‘s excellent note: “Tail call recursion in Python”, and decided to experiment with variations of the techniques.

The idea is: one may want to eliminate use of the Python language call-stack in the case of a “tail calls” (a function call where the result is not used by the calling function, but instead immediately returned). Tail call elimination can both speed up programs, and cut down on the overhead of maintaining intermediate stack frames and environments that will never be used again.

Click through for John’s riff on the topic.

Comments closed

Local Database Builds with Jenkins

Published 2019-08-29 by Kevin Feasel

Steve Jones continues a series on continuous integration, containers, and all that is good in life:

The only way to build a database project in SQL Server is with an actual SQL Server. In this case, I don’t have any code that would error on LocalDB, so I’ll just use that. I coudl specify my local SQL Server development database if I had the need.

This is a test build, so I also don’t need any SQL Compare options or other switches.

Getting code into source control and building continuous integration around it has become a lot easier over the past several years. Easy enough that you can work a simple system out in a day or two of experimentation.

Comments closed

Finding Unused Indexes in SQL Server

Published 2019-08-29 by Kevin Feasel

Monica Rathbun shows us how we can find and remove unused indexes in SQL Server:

Indexes can be incredibly beneficial to your database performance; however, they do come with a cost—indexes both consume storage space and affect insert performance. Therefore, it is important as part of your index maintenance procedures that you periodically check to see if your indexes are being used. Many times, indexes are created in the belief they are needed but in fact they are never used. You can reduce that IO overhead on inserts when you remove unnecessary indexes.

I’ll use the same script. Typically, I won’t drop unless total reads is 0 or at least two or three orders of magnitude smaller than writes. Sometimes you have indexes which don’t get used frequently but support very expensive or time-sensitive reports, and you don’t want those getting caught up in your dragnet.

Comments closed

Why ALTER Implies DROP

Published 2019-08-29 by Kevin Feasel

Andy Mallon explains why granting ALTER operations to a user means that you’ve granted DROP permissions:

Dropping stuff is destructive. Anyone who’s ever dropped a plate or a car knows that. But dropping a table, procedure, or database makes it go away completely. The only way to un-drop something is to recover it from backup, or to re-deploy from source control (you do have all your code & schema in source control, right?). Getting back to the original question’s premise (it’s OK to change the object but not to completely make it disappear), I ask…does it even matter? What are you preventing? Is dropping an object worse than altering it?

Read on for Andy’s reasoning.

Comments closed

Dropping a Column as a Metadata Operation

Published 2019-08-29 by Kevin Feasel

Max Vernon takes us through column dropping:

Dropping a column that is not referenced by any other object lets the storage engine simply mark the column definition as no longer present. Deleting the meta-data invalidates the procedure cache. Any query that subsequently references the affected table will result in the plan for that query be recompiled. The recompile operation can only return columns that currently exist in the table. As a result, the storage engine skips the bytes stored in each page for the dropped column, as if the column no longer exists.

This has some nice benefits in practice around minimizing deployment-releated downtime.

Comments closed