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Month: August 2021

Explanation Anti-Patterns

Published 2021-08-31 by Kevin Feasel

Julia Evans catalogs things to avoid when providing explanations:

This list isn’t meant to make you feel bad about your writing. I’ve probably done all of these things! I’m certainly going to do them again! I even did at least one of them while writing this post!

But knowing that I’m likely to accidentally do these things makes it easier for me to avoid them, and it makes me more receptive to critique when people point out issues with my writing (“Julia, this is assuming a lot of knowledge that I don’t have!“).

Being aware of these patterns also helps me when reading a confusing explanation: “oh, I’m not confused by this explanation because I’m stupid, I’m confused because it’s introduced 6 new-to-me concepts and it hasn’t explained what any of them is yet!“.

Read on for the list and some excellent explanations of what to do and what to avoid when trying to explain things clearly to people.

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A Primer on Apache Cassandra Reads and Writes

Published 2021-08-31 by Kevin Feasel

Utkarsh Upadhyay explains some of the internals of reading and writing with Apache Cassandra:

Apache Cassandra is a type of No-SQL database. It handles large amounts of data across many commodity servers. Being a highly scalable and high-performance distributed database, it provides high availability with no single point of failure. Here in this blog, mainly I focused on Reads and writes in Cassandra. And For Cassandra architecture, you can refer to this blog Apache Casandra: Back to Basics. So let’s get started with this blog on Apache Cassandra: Reads and Writes.

Click through for a comparison between Cassandra and MySQL, followed by a high-level architectural explanation of read and write operations in Cassandra. Though one thing which raises my eyebrow is the statement that reads in Cassandra are O(1). I don’t know that not to be the case, but I’m inclined to say it doesn’t sound right.

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Databricks Autologging

Published 2021-08-31 by Kevin Feasel

Corey Zumar and Kasey Uhlenhuth announce a new product:

Machine learning teams require the ability to reproduce and explain their results–whether for regulatory, debugging or other purposes. This means every production model must have a record of its lineage and performance characteristics. While some ML practitioners diligently version their source code, hyperparameters and performance metrics, others find it cumbersome or distracting from their rapid prototyping. As a result, data teams encounter three primary challenges when recording this information: (1) standardizing machine learning artifacts tracked across ML teams, (2) ensuring reproducibility and auditability across a diverse set of ML problems and (3) maintaining readable code across many logging calls.

Read on to see how Databricks Autologging can satisfy these issues.

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Receiving Notifications on Cosmos DB 429 Errors

Published 2021-08-31 by Kevin Feasel

Hasan Savran wants to remain in the loop:

Developers like to know when things go wrong in applications. It is an easy and simple solution to send an email when a bad error occurs. Things can go wrong easily in Cosmos Db, one of the most common error you will get from Cosmos DB is “Request rate too large (429)” exception. This error says that you do not have enough request units to run a query. This error usually occurs in peak times. Usually cause of getting 429 errors is the configuration of Request Units settings. You need to scale up your application or optimize your queries.
     It takes more time to retrieve data from Cosmos DB when error 429 occurs. You should get notification when this occurs, but you do not want to get an email each time it occurs either. 1- 5% of requests with 429 is acceptable. You can always open the Cosmos DB Monitoring tools and keep eye on it, or you can create Cosmos DB Alerts to get emails.

Click through for a demonstration of how to use Cosmos DB Alerts.

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Fun with Powershell Functions

Published 2021-08-31 by Kevin Feasel

Robert Cain shows us the basics of functions in Powershell:

Like most languages, PowerShell supports the use of functions. Functions are reusable bits of code with a name wrapped around them. This lets you make multiple calls to your function name allowing you code reuse.

PowerShell actually has two types of functions, Basic and Advanced. Basic functions are a lot like the 1974 VW SuperBeetle I owned back in college. No frills but useful, gets you where you are going. Did 0 to 60 mph in under 5 minutes. Most of the time.

Advanced functions have a lot more capabilities, and are more akin to a Tesla. Lots of fancy design, can do cool things, and depending on your need might be worth the extra investment.

Robert’s post is all about those basic functions, so check it out.

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Contrasting In-Place and Side-By-Side Updates for SQL Server

Published 2021-08-31 by Kevin Feasel

Chad Callihan is not the biggest fan of in-place upgrades:

How many SQL Server upgrades have you been a part of? Was there much discussion about whether or not to do an in-place upgrade versus a side-by-side upgrade? I’ve been part of both and to me there is only one safe way to perform upgrades. Let’s go over some pros and cons of each and see if you come to the same conclusion.

I did kind of spoil the answer, but click through to understand why one is so much riskier than the other.

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Enabling Modern Styles on Old Power BI Reports

Published 2021-08-31 by Kevin Feasel

Soheil Bakhshi saves us some time:

I see some developers really hate the old style of the visuals when they have to work on an old report and it makes them crazy to see that the visuals style remains the same even if they create a new report page and add new visuals to the page. So some developers go through a lot of pain to get the visuals to work in the modern style. I even know some developers copied all queries from Power Query from the old report and pasted them to a new Power BI file. Then they used Tabular Editor to copy the tabular objects from the old report to the new one. And some even started to build everything from scratch. If you are one of those developers, be aware that there is a simple setting that can help to quickly switch all the old visuals to their new modern style.

Read on to learn which setting that is.

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Github Autopilot and Insecure Code Suggestions

Published 2021-08-30 by Kevin Feasel

Mayank Sharma reviews an article:

Academic researchers discover that nearly 40% of the code suggestions by GitHub’s Copilot tool are erroneous, from a security point of view.

Developed by GitHub in collaboration with OpenAI, and currently in private beta testing, Copilot leverages artificial intelligence (AI) to make relevant coding suggestions to programmers as they write code.

To help quantify the value-add of the system, the academic researchers created 89 different scenarios for Copilot to suggest code for, which produced over 1600 programs. Reviewing them, the researchers discovered that almost 40% were vulnerable in one way or another. 

Click through to learn more, as well as a link to the article itself. I would be interested in reading GitHub’s thoughts on this.

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Using Index Column Order and Dynamic SQL to Fix Non-SARGable Queries

Published 2021-08-30 by Kevin Feasel

Erik Darling wraps up season 1 of Saving Sarge with a cliffhanger. First up, how setting up indexes to lead with SARGable columns makes sense:

Quite a bit, I find myself working with people who are able to change indexes, but unable to change queries.

Even making small, sane changes would nix their support, should they ask for it. I do sometimes have to laugh at the situation: if support were that great, they wouldn’t need me, and if we made the change, they probably wouldn’t need support.

Oh well, though. Keep me employed, ISVs.

Then, Erik takes a look at using dynamic SQL to solve one class of non-SARGable predicates:

The non-SARGABLE pattern that dynamic SQL helps you deal with is the the catch all query pattern, which can look like:

– col = @parameter or @parameter is null
– col = isnull(@parameter, col)
– col = coalesce(@parameter, col)

Or any similar variation of null/not null checking of a parameter (or variable) in the where/join clause at runtime.

Dynamic SQL allows you to build up the specific where clause that you need for the non-NULL set of search filters.

Stay tuned for the next thrilling episode of Saving Sarge. Same SARG-time, same SARG-channel.

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E-Mailing a DBA upon Object Creation in System Databases

Published 2021-08-30 by Kevin Feasel

Thomas Williams has another script for us:

Next on the list to commission a SQL Server, is to create a trigger in the master system database to send an e-mail to the DBA when objects are created in the database.

In general I’d expect this never to happen – but if it did, I’d want to follow up. It’s possible to go even further and prevent creating objects in the master system database completely.

My experience is that about 5% of the time, people intentionally put objects into the master database, and 95% of the time, I…err, they…forgot to switch databases before running the script.

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