For better or worse I spend some time each day at Stack Overflow [r], reading and answering questions. If you do the same, you probably notice certain features in questions that recur frequently. It’s as though everyone is copying from one source – perhaps the one at the top of the search results. And it seems highest-ranked is not always best.
Nowhere is this more apparent to me than in the way many users create data frames. So here is my introductory guide “how not to create data frames”, aimed at beginners writing their first questions.
Read on for a few tips. These are aimed at people asking questions but they’re sound advice in general.
This bootcamp is a free online course for everyone who wants to learn hands-on machine learning and AI techniques, from basic algorithms to deep learning, computer vision and NLP. However, the course language is German only, but for every chapter I did, you will find an English R-version here on my blog (see below for links).
Right now, the course is in beta phase, so we are happy about everyone who tests our content and leaves feedback. Also, not the entire curriculum is finished yet, we will update and extend the course during the next months. If there are specific topics you’d like to have us cover, just let us know!
If you understand German and want to learn about data science, check this out and leave feedback.
Another thing to keep in mind here is that you’re only going to load your calendar table once, so if it takes two minutes to do, who really cares? The version I have should run reasonably fast–I calculated 726 years on slow hardware in 19 seconds and fast hardware in 11 seconds. I’m sure you can play code golf and get it done faster, but that’s probably not a good use of your time
. Whatyou want to sweat instead is query time: how long is it taking to access this data?
Click through for a script.
I think Dynamic Data Masking is pretty cool. The idea is basically to provide a mask for certain users when they might see protected data. The documentation on this feature is actually pretty deep, it’s worth a look.
I just want to show you how you can see the masking in an execution plan. Let’s mask some data in StackOverflow2010! (Also, there’s an interesting side note at the end)
Click through for those notes.
I am telling you personally that I hate the use of DISTINCT.
DISTINCT used by those people, who are not sure about their data set or SELECT statement or JOINS.
Whenever I get any query with DISTINCT, immediately I suggest to remove it.
I agree with this sentiment about 85% of the time. There are cases where I know l am working with data at a finer grain than I need and the counts aren’t important. But just tossing a
DISTINCT on a query to stop it from repeating rows is the wrong approach: figure out why that repetition happens and fix it.
Let’s start with what services may require you to use a data gateway.
You will need a data gateway when you are using Power BI, Azure Analysis Services, PowerApps, Microsoft Flow, Azure Logic Apps, Azure Data Factory, or Azure ML with a data source/destination that is in a private network that isn’t connected to your Azure subscription with a VPN gateway. Note that a private network includes on-premises data sources and Azure Virtual Machines as well as Azure SQL Databases and Azure SQL Data Warehouses that require use of VNet service endpoints rather than public endpoints.
There are a few of them so check out Meagan’s post and take notes.
The next blade will show you an active console of the virtual machine. From here you are able to determine what the current status of the virtual machine might be. You will also noticed that you can gain access to the serial log (shown below), which will give you more detailed information about the boot process.
Once we click on Boot Diagnostics, we will then see the initial startup screens of the server:
This is useful if you have some huge misconfiguration and the server’s failing for some reason.
Querying the data of an Extended Events session has never been easy. My XEvent sessions typically store event data in a target file, which means using sys.fn_xe_file_target_read_file. To get something of value, you need to shred the event data XML.
Doing this in T-SQL isn’t great. It’s probably better to shred in another language—F# would probably be my choice due to its type provider—and dump the results back into SQL. But if you want to stick to one language, Dave shows you how.