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Author: Kevin Feasel

AzureTableStor: Table Storage in R

Published 2020-11-19 by Kevin Feasel

Hong Ooi announces a new package on CRAN:

I’m pleased to announce that the AzureTableStor package, providing a simple yet powerful interface to the Azure table storage service, is now on CRAN. This is something that many people have requested since the initial release of the AzureR packages nearly two years ago.

Azure table storage is a service that stores structured NoSQL data in the cloud, providing a key/attribute store with a schemaless design. Because table storage is schemaless, it’s easy to adapt your data as the needs of your application evolve. Access to table storage data is fast and cost-effective for many types of applications, and is typically lower in cost than traditional SQL for similar volumes of data.

If that sounds like a fit for you, check out the package.

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Improving Performance Counters with Powershell

Published 2020-11-19 by Kevin Feasel

Jeffrey Hicks has an improvement to Get-Counter in Powershell:

I wanted to tell you about another addition to the latest release of the PSScriptTools module. This is something I’ve written about before but I decided to add the function to the module. I hope you find it a much easier way to work with performance counters. And it works in Windows PowerShell and PowerShell 7.x.

Click through to see what has changed.

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The Default Cardinality Estimator and Ascending Keys

Published 2020-11-19 by Kevin Feasel

Erik Darling compares cardinality estimators:

Look, I’m not saying there’s only one thing that the “Default” cardinality estimator does better than the “Legacy” cardinality estimator. All I’m saying is that this is one thing that I think it does better.

What’s that one thing? Ascending keys. In particular, when queries search for values that haven’t quite made it to the histogram yet because a stats update hasn’t occurred since they landed in the mix.

Read the whole thing.

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Database DevOps and Availability Groups

Published 2020-11-19 by Kevin Feasel

Kendra Little has some considerations for us:

One question which comes up periodically from our Microsoft Data Platform customers is whether there is anything special that they need to do when implementing version control, continuous integration, and automated deployments for a production database which is a member of a SQL Server Availability Group. 

The good news is that deployments are quite straightforward. You’ve most likely already configured a listener for your applications to connect to the Availability Group and automatically find the writeable database. To do a deployment, you simply need to connect to the listener as well.

There are a few other considerations which are helpful to think about when building your approach to database DevOps, however.

Check out the article for the details.

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Refreshing Power Query on Protected Excel Sheets

Published 2020-11-19 by Kevin Feasel

Imke Feldmann shows how to refresh Power Query results on protected sheets in Excel:

When working with Power Query in Excel you might want to refresh Power Queries on protected sheets. But this will not work by default. Using a macro to temporarily unprotect the sheet and protect it again will do the trick. But this requires the password being displayed in the VBA code. So please have in mind that this technique only works for scenarios where you want to prevent accidental changes with the password protection.

Read on for the process.

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Finding Function Names with Overlap in R

Published 2020-11-18 by Kevin Feasel

Tomaz Kastrun has a script for us:

So the following function does just that; if goes through the list of functions for all the installed packages in particular environment and finds duplicates. Giving the R programmer the insights where to be cautious and refer to scope and namespace.

This is a cautionary tale to use full object naming, like coin::show() rather than just show().

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An Intro to Time Series Databases

Published 2020-11-18 by Kevin Feasel

Kyle Buzzell looks at time series databases:

As the name implies, a time series database (TSDB) makes it possible to efficiently and continuously add, process, and track massive quantities of real-time data with lightning speed and precision. While other database models have been used for these kinds of workloads in the past, TSDBs utilize specific algorithms and architecture to deal with their unique needs.

In this piece, we’ll take a deeper look at time series databases, including the unique needs of the workloads they’re built for, their benefits, common use cases, and the TSDBs out there.

Click through for an overview. Time series databases are definitely a niche product, but they are really good inside that niche.

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Tracking Cosmos DB Re-Indexing Progress

Published 2020-11-18 by Kevin Feasel

Hasan Savran wants information:

Indexes let your queries run faster. When you need to adjust your indexing policies, database engines re-indexes your data respecting to your changes. In Cosmos DB, when you change your indexing policies, database engine truncates all your indexes and starts to reindex all your indexes from scratch. You do not want to change your indexing policies when your application is busy. Because your queries can not use the dropped indexes, queries will take longer, and they will cost more Request Units. Also, your queries might not return all the data they supposed to. You can read me my older post about indexes in Cosmos DB.

     You may want to monitor re-indexing progress; you may want to disable your application until indexing is completed or warn your team about the re-indexing progress. You can check the re-indexing progress only from SDK, that means you need to write your own code to accomplish this. I have the following code which checks the progress every second. If progress is at %100 then it quits, otherwise it continues to check progress every second until it receives 100 as result.

Hasan has provided us with a script, so check that out.

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