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Day: January 25, 2024

Calculating Date Differences in Month with R

Published 2024-01-25 by Kevin Feasel

Steven Sanderson has ways to track months:

Greetings fellow R enthusiasts! Today, let’s dive into the fascinating world of date calculations. Whether you’re a data scientist, analyst, or just someone who loves coding in R, understanding how to calculate the number of months between dates is a valuable skill. In this blog post, we’ll explore two approaches using both base R and the lubridate package, ensuring you have the tools to tackle any date-related challenge that comes your way.

Read on to see how to do this in base R as well as the lubridate package.

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DBCC SHRINKFILE and tempdb

Published 2024-01-25 by Kevin Feasel

Tom Collins answers a question:

Question: I’m trying to delete a TempDB ndf file from the TempDB file definitions. It is no longer required ,but getting an error message :

DBCC SHRINKFILE: Page xxxxxxxx could not be moved because it is a work table page.

How can I get around this problem? There is no activity on the server

Read on for the answer.

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The Impact of Auto-Close on Performance

Published 2024-01-25 by Kevin Feasel

Steve Stedman explains why Auto-Close should almost never be on for your database:

When the AutoClose setting is enabled, SQL Server will shut down the database after the last user disconnects. This means that every time a new connection is made, SQL Server must go through the entire process of starting the database again. This includes reading the database file, allocating memory, and performing any necessary recovery processes. This overhead can cause a noticeable delay for users as they connect, especially if the database is large or complex.

Read on for several other factors affecting performance. I will say that the best use case for Auto-Close is when you have a dev instance—especially on a local machine—with a large number of databases and a very limited amount of RAM available. Otherwise, if this is a server, I’m turning Auto-Close off. Even today, I’d rather just buy enough RAM for my developers than flip this switch.

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Notebooks versus Dataflow Gen2 in Microsoft Fabric

Published 2024-01-25 by Kevin Feasel

Gilbert Quevauvilliers takes us through a comparison:

In this blog post I am going to compare Dataflow Gen2 vs Notebook in terms of how much it costs for the workload. I will also compare usability as currently the dataflow gen2 has got a lot of built in features which makes it easier to use.

The goal of this blog post is to understand which in my opinion is cheaper and easier to use, which will then be the focus for future blog posts with regards to what I’ve learned along the way, which will hopefully assist you too.

To compare between the two workloads, I am going to be using the same source file as well as do the same transformations which will result in the same result.

Read on for a surprising difference in cost.

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Reviewing the Data Activator in Microsoft Fabric

Published 2024-01-25 by Kevin Feasel

Ginger Grant takes us through the Data Activator:

With the GA release of Fabric in November, 2023, I am dedicating several posts to new features which you will not find in Power BI or Azure Synapse, and the latest one I want to talk about is Data Activator. Data Activator is an interesting tool to include inside of Fabric because it is not reporting or ETL, rather it is a way to manage actions when the data hits defined targets.  It is a management system for data stored in Fabric or streamed in Azure using IOT or Event Hubs. You can use Data Activator to monitor the current state or to define actions to occur when certain conditions occur in the data.  Data Activator is still in preview, but you can evaluate it now.

Read on to see how to enable it and what you can currently do with it.

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Fixing Eager Spooling

Published 2024-01-25 by Kevin Feasel

Erik Darling sends it to the moon:

Probably the most fascinating thing about Eager Index Spools to me is how often the optimizer will insert them into execution plans, often to a query’s detriment.

In a sane world, a non-loop join plan would be chosen, a missing index request would be registered that matches whatever would have been spooled into an index, and we’d all have an easier time.

Read on for a few examples of the problem and two separate ways you can fix it. Remember, kids: friends don’t let friends eagerly spool.

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