A Fine Slice Of SQL Server
Christian Lorentzen takes a well-deserved victory lap:
Yes! After more than 10 years, scikit-learn released its 1.0 version on 24 September 2021. In this post, I’d like to point out some personal highlights apart from the release highlights.
Read on for four such highlights. H/T R-Bloggers.
Comments closedJoe Obbish busts out the slide rule:
Lately I’ve been doing some exploratory performance testing on Azure SQL Managed Instances in preparation for a migration to that platform. This blog post documents some storage testing results and may even have practical advice near the end. All testing was done on a gen5 general purpose instance with 8 vCores.
Read on for Joe’s findings. Spoiler alert: there is practical advice at the end.
Comments closedNithin Sankar tracks deviations with cumulative sums:
With the advent of Internet of Things (IOT) and the proliferation of connected devices, comes the challenge of monitoring parts for maintenance before they break down. A common approach revolves around getting data from connected devices and performing a statistical test to determine the likelihood of the device failing. While this common approach is robust, it typically involves a significant time investment in exploratory data analysis, feature engineering, training, and testing to build a predictive model. It, therefore, often lacks the agility required to keep up with the monitoring demands of increasingly time-sensitive initiatives.
In this context, the question becomes: how can we ensure a similar degree of rigor, but also improve the timeliness and responsiveness of being able to perform predictive maintenance?
Click through for the process, as well as an example using Azure Stream Analytics and Power BI.
Comments closedRonen Ariely finds the real creator:
Question: I have seen new database in my server. that was created nearly 45 days back. I have tried to check using standard report but no luck. SQL version: SQL server 2017 enterprise. Is it possible to find who created database…
Read on for a bit of transaction log spelunking.
Comments closedDennes Torres compares several strategies for querying data stored in Azure Blob Storage:
In the third part of the series Querying Blob Storage with SQL, I will focus on the performance behaviour of queries: What makes them faster, slower, and some syntax beyond the basics.
The performance tests in this article are repeated, and the best time of the queries is recorded. This doesn’t mean you will always achieve the same timing. Many architectural details will affect the timing, such as cache, first execution, and so on. The timing exposed on each query is only a reference pointing to the differences of the query methods that can affect the time and the usual result for better or worse performance.
Click through to see which patterns perform well and which don’t.
Comments closedDave Ruijter backs that thing up:
Out of the box, Azure Data Lake Storage Gen2 provides redundant storage. Therefore, the data in your Data Lake(house) is resilient to transient hardware failures within a datacenter through automated replicas. This ensures durability and high availability. In this blog post, I provide a backup strategy on how to further protect your data from accidental deletions, data corruption, or any other data failures. This strategy works for Data Lake as well as Data Lakehouse implementations. It uses native Azure services, no additional tools, software, or licenses are required.
Read on for a detailed strategy.
Comments closed