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Curated SQL Posts

Updating Microsoft Fabric Warehouses via Power Apps

Shabnam Watson troubleshoots an issue:

One of my recent explorations with Microsoft Fabric was integrating Power Apps with a Fabric Warehouse—both in a standalone Power Apps app and as an embedded visual within a Power BI report to enable writeback. My goal was simple: to enable Power Apps to display and update records from a table in the Fabric Warehouse. Initially, I turned to the three-screen template apps to get started, however; while it displayed the records, it failed to update them. This led me to dive deeper into how Fabric Warehouse differs from other SQL data sources when it comes to Power Apps and to find a workaround.

Read on to see how it all works.

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Don’t Trust TRUSTWORTHY

Chad Callihan talks about an untrustworthy setting:

TRUSTWORTHY is a database property change that can have far-reaching security consequences when turned ON. Let’s take a brief look at what the TRUSTWORTHY property is and if it’s worth turning on, even when it is a potential fix to your problems.

Chad links to a DBA Stack Exchange post from Solomon Rutzky concerning module signing, which is a good opportunity for me to plug Solomon’s modulesigning.info. This is the correct answer, not TRUSTWORTHY or any of its ilk (EXECUTE AS, cross-database ownership chaining, etc.).

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Glyphs and Character Encodings in PostgreSQL

Cristophe Pettis has a two-parter (so far). First up is an explanation of several linguistic terms:

This is part one of a series on PostgreSQL and collations, and how to use them without tears. This is an introduction to the general concepts of glyphs, character encodings, collations, and locales.

Part two covers character encodings in PostgreSQL:

From the point of view of the computer, a character string is just a sequence of bytes (maybe terminated by a zero byte, maybe with a length). If the only thing PostgreSQL had to do with character strings was store them and return them to the client, it could just ignore that character encodings even exist.

However, databases don’t just store character strings: they also compare them, build indexes on them, change them to upper case, do regex searches on them, and other things that mean they need know what the characters are and how to manipulate them. So, PostgreSQL needs to know what character encoding applies to the text it is storing.

Read on for a detailed explanation for PostgreSQL. A lot of this also applies to SQL Server, though there are some inevitable differences that pop up.

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Finding a Good Cost Threshold for Parallelism

Jared Westover goes on a quest:

Given modern hardware, you might hear that the default setting of 5 for the Cost Threshold for Parallelism (CTFP) is far too low. However, people are left with a decision: Should they change it or leave it alone? If I change it and the performance gets worse, I’ll be left with egg on my face. What exactly is the benefit of increasing it, especially for smaller-cost queries?

Read on to learn more about what Cost Threshold for Parallelism is, how you can set it, and a simple example of how the setting can affect you. Jared also has some links to great resources that I highly recommend you check out.

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Moving items from “My Workspace” in Microsoft Fabric

Matt Collins is on the move:

A common issue I’ve seen recently when working with Microsoft Fabric is managing items in the “My Workspace” Workspace. This is often the playground for many users who sign up for a free trial but can result in some administrative overhead when resources developed here are now ready for wider use and need to be moved to a shared location.

In this article we will discuss how to move workspace items in Microsoft Fabric from “My Workspace” to other workspaces, using our understanding of item dependencies and some metadata to speed up the process.

Read on to learn how, as well as some of the issues you can run into along the way.

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Map and FlatMap in PySpark

Vipul Kumar does a bit of work with resilient distributed datasets:

PySpark, the Python API for Apache Spark, is widely used for big data processing and distributed computing. It enables data engineers and data scientists to efficiently process large datasets using resilient distributed datasets (RDDs) and DataFrames. Two commonly used transformations in PySpark are map() and flatMap(). These functions allow users to perform operations on RDDs and are pivotal in distributed data processing.

In this blog, we’ll explore the key differences between map() and flatMap(), their use cases, and how they can be applied in PySpark.

The DataFrame approach has all but obviated having developers use the original Hadoop-like map-reduce approach to writing code in Spark. Even so, I do think it’s useful to know how it all works.

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A Survey of Predictive Analytics Techniques

Akmal Chaudhri tries a bunch of things:

In this short article, we’ll explore loan approvals using a variety of tools and techniques. We’ll begin by analyzing loan data and applying Logistic Regression to predict loan outcomes. Building on this, we’ll integrate BERT for Natural Language Processing to enhance prediction accuracy. To interpret the predictions, we’ll use SHAP and LIME explanation frameworks, providing insights into feature importance and model behavior. Finally, we’ll explore the potential of Natural Language Processing through LangChain to automate loan predictions, using the power of conversational AI.

Click through for the notebook, as well as an overview of what the notebook includes. I don’t particularly like word clouds as the “solution” in the BERT example, though without real data to perform any sort of NLP, there’s not much you can meaningfully do.

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Source Control Tips

Aamir Khan shares some tips on source control:

In software development, version control is an essential practice that helps manage changes to code and collaborates effectively with team members. A well-organized repository not only streamlines the development process but also enhances productivity and minimizes errors. In this blog post, we’ll explore best practices for maintaining a clean and organized repository, including branch naming conventions and crafting effective commit messages.

The primary audience for this is software developers, but if you create and modify SQL assets (tables, stored procedures, views, functions, etc.), source control is a great thing for many reasons, and this still applies to you. And if you write Powershell scripts because you’re “not a coder,” well, I have some shocking news for you.

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Fixing Timeout Issues with Azure SQL Database

Reitse Eskens shares some knowledge:

The customer can connect to the Azure Sql database with Sql Server Management Studio (SSMS) but not with a specific client application.
When digging into the logs (all logs were activated for this database), nothing shows up for the specific login used by the client application. The application itself returns a connection error caused by a time-out.

The application resides outside of Azure and can’t use a VPN connection, the Azure Sql Server has a specific firewall rule to allow incoming traffic from this specific IP address. Not a situation I’m really happy with, but it happens.

Read on for the solution. It was not one I had anticipated. But it did land in my “When in doubt, blame the network” policy.

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The Importance of Monitoring in Microsoft Fabric

Marc Lelijveld flips a switch but also watches it:

A long time ago, I blogged about Power BI governance with topics like feature implementation in a phased approach and why you should consider to disable export to Excel. In this blog, I want to continue the governance topic with another blog about why monitoring your tenant is important! This blog will also provide you an overview of the various monitoring options you have out of the box, no matter what your role is. No matter if you are the workspace-, capacity-, domain- or tenant administrator.

I encourage everyone, no matter if you are the service administrator or not, to go through this blog and look from various angles how monitoring can help. I think it can be relevant for any Fabric / Power BI user to see all capabilities it has to offer from a different angle and better understand possible restrictions that are set by your service administrator.

Read on for Marc’s argument, as well as plenty of examples of what you can do as far as monitoring goes.

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