A Fine Slice Of SQL Server
Gilbert Quevauvilliers needs a refresh:
I have been answering some questions on the Power BI (Or is it now Fabric?) community forum, and I have found recently that there are some people asking how to get data from Excel that is stored in SharePoint Online.
In this blog post I will show you how to connect to a single Excel file using Power BI desktop, and then configure it in the Power BI Service where it does not require a gateway.
Read on to see how.
Comments closedI have found almost every day of my career at Microsoft, I learn something new about Microsoft SQL. It is one of the reasons I enjoy my job. In April of 2023, I was speaking at the MVP Summit in Redmond, Washington. One day I was spending time in a side conversation with MVP Rob Farley discussing some of his “wish list” items for SQL. One of these wish list items was delayed transaction durability for tempdb.
Good news for Rob on that front.
Comments closedTsz Sze provides some recommendations:
The snapshots feature of the Apache Hadoop Distributed Filesystem (HDFS) enables you to capture point-in-time copies of the file system and protect your important data against corruption, user-, or application errors. This feature is available in all versions of Cloudera Data Platform (CDP), Cloudera Distribution for Hadoop (CDH) and Hortonworks Data Platform (HDP). Regardless of whether you’ve been using snapshots for a while or contemplating their use, this blog gives you the insights and techniques to make them look their best.
Read on for those tips and tricks.
Comments closedPaul Brebner tracks some measurements:
Like a steam locomotive, Apache Kafka also has lots of “moving parts”. A Kafka cluster is actually a distributed system, a cluster, which consists of multiple brokers (servers)—messages are sent to Kafka with producers, and consumers receive messages. Topics are used to direct messages between producers and consumers—producers write to selected topics, and consumers subscribe and read from selected topics. Topics are divided up into partitions, and the partitions are distributed over the available brokers for high availability and concurrency. Partitions are replicated to other partitions (followers) from the leader partition (3 is common for production clusters).
Click through for the description of metrics on brokers, topics, consumer groups, and more, as well as an extended analogy to steam locomotives which works surprisingly well.
Comments closedRobert Cain continues a series on KQL:
In this post we’ll cover the next in our series on KQL Windowing Functions,
row_rank_min. Therow_rank_minfunction will assign rank numbers to an incoming dataset, with the rank of 1 being assigned to the minimal value in the dataset and increasing as the values increase.First though, if you’ve not read the introductory post on Windowing Functions, Fun With KQL Windowing Functions – Serialize and Row_Number, you should do so now as it introduced several important concepts needed to understand how these Windowing Functions work.
Read on for Robert’s explanation.
Comments closedBrian Bønk does some data shuffling:
The Fabric servive Eventstream can read data from an Event Hub service to help collect data from IoT devices and other streaming services. But how do you configure the Event Hub and Eventstream to work together?
I’ll try to help with that in this blogpost.
Click through for the article, which provides a how-to guide on the topic.
Comments closedErin Stellato gives us an update:
In this release we updated to VS Code version 1.79.2, from version 1.70, bringing ADS nearly current with VS Code. Keeping up with VS Code is an artifact of Azure Data Studio being a fork of VS Code, and the team accomplished a major feat with this latest merge. Many of the changes are not immediately obvious to users, but there are improvements across security, performance, and the application interface.
Read on for the highlights.
Comments closedHenrietta Dombrovskaya shows us an execution plan in Postgres:
In the last blog (When PostgreSQL Parameter Tuning is not the Answer), we compared several execution plans for a SQL statement as we made changes to parameters and indexes. Still, there was no mention of what an execution plan is, how one can obtain an execution plan for a query, and how to interpret the result. In this blog, we will take a deep dive into this topic.
Read on for the full article.
Comments closedStephane Laurent writes some code:
I implemented the framed closed curves exposed in this blog post, in Julia and R. In fact it is useless with R, because the rgl function
cylinder3dis faster and better.Here is the Julia implementation:
Click through for that code, as well as equivalent R code. H/T R-Bloggers
Comments closedSteven Sanderson explains the value of the str() function:
In a nutshell,
str()stands for “structure” and offers a concise summary of the structure of an R object. It presents essential details about the object, including its data type, dimensions, and the first few values. By providing an overview of your data,str()allows you to grasp the fundamentals at a glance and proceed with a clearer understanding of what you’re working with.
str() is a really useful function and people who develop objects in R thoughtfully can pack a lot of useful data into the one call.