A Fine Slice Of SQL Server
Unmesha Sreeveni shows how you can create a widget in a Databricks notebook:
In order to get some inputs from user we will require widgets in our Azure Databricks notebook.
This blog helps you to create a text based widget in your python notebook.
The syntax is rather similar for Scala as well.
Comments closedMark Kromer clears up some issues around debugging in Azure Data Factory:
One of the important features built into ADF is the ability to quickly preview your data while designing your data flows and to execute the finished product against a sampling of data prior to finalizing and operationalizing your pipelines.
However, there are a few fundamentals relative to working with Joins that you should keep in mind and a few details below are important to understand at design time and while debugging / testing.
The answer makes sense but it would not have been the first thing to come to mind for me.
Comments closedMark Lelijveld walks us through something new in Power BI Desktop’s August 2020 update:
If you work or used to work with Analysis Services, you might know the perspectives functionality. It is a feature inside tabular modelling that allows you to define viewable subsets of a data model.
Each tabular model can include multiple perspectives, where each perspective can include a subset of tables, columns a measures. Especially with large enterprise models, perspectives can be very useful.
With perspectives, you can define specific perspectives to be defines for a specific target audience. For example, the author can create logical subsets of the model for each audience of the dataset. (e.g. Sales, Finance, Marketing, etc.) One thing must clear, perspectives are not object level security or any other kind of security! It is just a better way to view it.
Read on to see how you can create and work with these in Power BI Desktop.
Comments closedAaron Bertrand walks us through a painful scenario:
We recently performed a DDL operation against a SQL Server table – simply increasing the size of a varchar column – which should have been instantaneous. Instead, we killed the SQL Server process after observing 20 minutes of HARD_SYNC_COMMIT waits and a blocked replication log reader. Could this issue have been avoided? What went wrong?
I spotted the issue pretty quickly, but it’s easy to miss in a code review. Read the whole thing.
Comments closedEitan Blumin uses Extended Events to track activity:
Extended events provides a solution similar to client side trace. It basically can capture all events that a trace can capture (and more), and it also supports a wider choice of target types. And that, is where its true power lies.
It just so happens that Extended Events has a target type called “ring buffer“, and it gives us exactly what we need.
The ring buffer is easy to set up and if you don’t need permanence, works great.
Comments closed