Press "Enter" to skip to content

Author: Kevin Feasel

What Prevents Plan Reuse?

Published 2018-08-31 by Kevin Feasel

Eric Blinn walks us through what might cause a query plan not to be used:

There are several reasons that a query plan would need to be compiled again, but they can be boiled down to a few popular reasons.

The first one is simple.  The plan cache is stored exclusively in memory.  If there is memory pressure on the instance SQL Server will eject plans from cache that aren’t being used to make room for newer, more popular plans or even to expand the buffer pool.  If a command associated to a plan that has been ejected from the plan cache is issued, it will need to be compiled again before it can execute.

Since SQL Server 2008 a system stored procedure, sp_recompile, has been available to clear a single stored procedure plan from the cache.  When executed with a valid stored procedure name as the only parameter any plans for that procedure will be marked for recompilation so that a future execution of that procedure will need to be compiled.  Running sp_recompile does not actually compile the procedure.  It simply invalidates any existing plans so that some future execution, which in theory may never come, will need to compile before executing.

Read on for additional causes.

Comments closed

When Query Store Alterations Are Blocked

Published 2018-08-31 by Kevin Feasel

Erin Stellato gives us some helpful tips on Query Store:

If you are trying to execute an ALTER DATABASE command to change a Query Store option (e.g. turn it off, change a setting) and it is blocked, take note of the blocking session_id and what that session_id is executing.  If you are trying to execute this ALTER command right after a failover or restart, you are probably blocked by the Query Store data loading.

As a reminder, when a database with Query Store enabled starts up, it loads data from the Query Store internal tables into memory (this is an optimization to make specific capabilities of Query Store complete quickly).  In some cases this is a small amount of data, in other cases, it’s larger (potentially a few GB), and as such, it can take seconds or minutes to load.  I have seen this take over 30 minutes to load for a very large Query Store (over 50GB in size).

Erin has a story which ties this together, so check that out.

Comments closed

Unraveling Rolling Totals With Power Query

Published 2018-08-31 by Kevin Feasel

Imke Feldmann shows us how to get from rolling totals back to the original values using Power Query:

To retrieve this value, one would have to start with the first value in the year. This is also the value of the first quarter, but for the 2nd quarter, one would have to deduct the value of the first quarter from the cumulative value of the 2nd quarter. So basically retrieving the previous cumulative row and deduct it from the current cumulative row. Do this for every row, unless it’s the start of the year or belongs to a different account code in this example:

(Although for the data given in the sample, it would be sufficient to just take the year as a discriminator, but to be on the save side, I would suggest to include the different accounts as well)

That’s a pretty interesting approach.

Comments closed

Explaining Data Flows (And Dataflows)

Published 2018-08-31 by Kevin Feasel

Melissa Coates disambiguates “data flows” from “dataflows” because those are two totally different things:

It’s another terminology post! Earlier this week I was having a delightful lunch with Angela Henry, Kevin Feasel, Javier Guillen, and Jason Thomas. We were chatting about various new things. Partway thru our conversation Jason stops me because he thought I was talking about Power BI Dataflows when I was really talking about Azure Data Factory Data Flows. It was kind of a funny moment actually but it did illustrate that we have some overlapping terminology coming into our world.

So, with that inspiration, let’s have a chat about some of the new data flow capabilities in the Microsoft world, shall we?

Melissa clarifies the term “data flow” (or “dataflow” as the case may be) across several products in Microsoft’s BI stack.  Worth the read.

Comments closed

Time-Series Analysis With Box-Jenkins

Published 2018-08-30 by Kevin Feasel

The folks at Knoyd walk us through time series analysis using the Box-Jenkins method:

However, this approach is not generally recommended so we have to find something more appropriate. One option could be forecasting with the Box-Jenkins methodology. In this case, we will use the SARIMA (Seasonal Auto Regressive Integrated Moving Average) model. In this model, we have to find optimal values for seven parameters:

  • Auto Regressive Component (p)
  • Integration Component (d)
  • Moving Average Component (q)
  • Seasonal Auto Regressive Component (P)
  • Seasonal Integration Component (D)
  • Seasonal Moving Average Component (Q)
  • Length of Season (s)

To set these parameters properly you need to have knowledge of auto-correlation functions and partial auto-correlation functions.

Read on for a nice overview of this method, as well as the importance of making sure your time series data set is stationary.

Comments closed

Databricks Runtime 4.3 Released

Published 2018-08-30 by Kevin Feasel

Todd Greenstein announces Databricks Runtime 4.3:

In addition to the performance improvements, we’ve also added new functionality to Databricks Delta:

  • Truncate Table: with Delta you can delete all rows in a table using truncate.  It’s important to note we do not support deleting specific partitions.  Refer to the documentation for more information: Truncate Table

  • Alter Table Replace columns: Replace columns in a Databricks Delta table, including changing the comment of a column, and we support reordering of multiple columns.   Refer to the documentation for more information: Alter Table

  • FSCK Repair Table: This command allows you to Remove the file entries from the transaction log of a Databricks Delta table that can no longer be found in the underlying file system. This can happen when these files have been manually deleted.  Refer to the documentation for more information: Repair Table

  • Scaling “Merge” Operations: This release comes with experimental support for larger source tables with “Merge” operations. Please contact support if you would like to try out this feature.

Looks like a nice set of reasons to upgrade.

Comments closed

Getting Started With Linux

Published 2018-08-30 by Kevin Feasel

Kellyn Pot’vin-Gorman has a new series on learning Linux for SQL Server DBAs:

As this series of articles are published, it will be important that you have a way to do some hands on with Linux, not just read about this powerful operating system. To accomplish this, my recommendation is to download Docker for Windows.

Choosing to use Docker over a VM or a cloud deployment might seem odd at first, but I’ve found that Docker is the perfect option from the testing and classes I’ve led. The Docker image is light–using a minute number of resources on any laptop. Access to the docker image isn’t dependent upon Wi-Fi or the user having a cloud account. The image, for the most part, offers an experience that is incredibly similar to a full Linux server in functionality for no additional cost.

Once you’ve downloaded Docker and have it installed, create a Linux container with SQL Server on your workstation, (thanks to Microsoft) to work with and build your knowledge. Start by opening a Command Prompt, cmd from the search option in Windows.

This post is mostly setup and updating packages.  I also want to pitch We Speak Linux if you’re in this boat.  Kellyn did our inaugural webinar, too.

Comments closed

Running Powershell Files From SQL Operations Studio

Published 2018-08-30 by Kevin Feasel

Jay Robinson shows how you can configure SQL Operations Studio to run Powershell with the click of two buttons:

As I’ve used SQL Operations Studio more and more, I’ve also been finally using PowerShell in more situations. Given that I like the editor and that there’s a built-in terminal, I’ve been running those in my Ops Studio instance. But for a while I didn’t have a slick way of running an entire PowerShell file in the terminal. Usually, I’d just Ctrl+A/Ctrl+C/Ctrl+V, which is a bit awkward.

But among all the other ways you can customize Ops Studio, you have a lot of control over the key mappings. One way to edit these mappings is to pull up the Command Pallette (Ctrl+Shift+P) and start typing “key”, and you’ll see “Preferences: Open Keyboard Shortcuts”. You’ll also see it mentions the Ctrl+K/Ctrl+S shortcut. This will bring you to the basic Keyboard Shortcuts window, where you’ll need to click “keybindings.json”. Either way, just like Ops Studio’s overall settings (and VSCode’s, for that matter), you get a JSON file you can now tweak. Actually, two of them, with the defaults on the left and your own settings on the right.

Read on to see Jay’s mapping and an explanation of what he’s doing.

Comments closed

Normalization Code Smells

Published 2018-08-30 by Kevin Feasel

Erik Darling has a few tips to see if you’re not properly normalizing your tables:

First Sign Of Problems: Prefixed Columns

Do you have columns with similar prefixes?

If you have naming patterns like this, it’s time to look at splitting those columns out.

I took the Users and Posts tables from Stack Overflow and mangled them a bit to look like this.

You may not have tables with this explicit arrangement, but it could be implied all over the place.

One great way to tell is to look at your indexes. If certain groups of columns are always indexed together, or if there are lots of missing index requests for certain groups of columns, it may be time to look at splitting them out into different tables.

These things tend to happen, but they can have serious negative consequences for database performance, not to mention the risk of bad data sneaking in.

Comments closed

HA/DR With Azure SQL Database

Published 2018-08-30 by Kevin Feasel

James Serra explains the High Availability and Disaster Recovery options available when using Azure SQL Database:

High Availability (HA) – Keeping your database up 100% of the time with no data loss during common problems.  Redundancy at system level, focus on failover, addresses single predictable failure, focus is on technology.  SQL Server IaaS would handle this with:

  • Always On Failover cluster instances
  • Always On Availability Groups (in same Azure region)
  • SQL Server data files in Azure

Disaster Recovery (DR) – Protection if major disaster or unusual failure wipes out your database.  Use of alternate site, focus on re-establishing services, addresses multiple failures, includes people and processes to execute recovery.  Usually includes HA also.  SQL Server IaaS would handle this with:

  • Log Shipping

  • Database Mirroring

  • Always On Availability Groups (different Azure regions)

  • Backup to Azure

Click through for more details.

Comments closed