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Day: August 18, 2022

Useful Design Patterns for Apache Spark Projects

Published 2022-08-18 by Kevin Feasel

Alexander Eleseev applies some design patterns:

When I participated in a big data project, I needed to program Spark applications to move and transform data from/to relational and distributed databases, like Apache Hive. I found such applications to have a number of pitfalls, so all “hard to read code,” “method is too large to fit into a single screen,” etc. problems need to be avoided for us to focus on deeper issues. Also, Spark jobs are similar: data is loaded from a single or multiple databases, gets transformed, then saved to a single or multiple databases. So it seems reasonable to try to use GoF patterns to program Spark applications. 

Specifically, this covers Spark code written in Java (or Python). I’d argue that Scala-based code would profit by following a different set of functional patterns rather than Gang of Four object-oriented design patterns.

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A Primer on Azure Arc-Enabled Data Services

Published 2022-08-18 by Kevin Feasel

Warwick Rudd has a four-parter on Azure Arc-Enabled Data Services. Part 1 sets the stage:

Utilising Azure Arc-enabled data services provides you the ability to take advantage of the Azure data services (SQL Server, Azure SQL Managed Instance, PostgreSQL) in a hybrid environment. This offering provides you with reduced administrative efforts in managing and maintaining your data services while giving you the same look and feel as if you were running in the Azure Cloud.

Part 2 looks at the Data Controller:

The Azure Arc Data Controller is a Kubernetes operator that performs all of the orchestration to ensure you achieve your desired state. This is the main component in the Azure Arc infrastructure that links the data services with the Arc-enabled hardware located either in your On-premises, Azure, or any other public cloud data center and your azure subscription.

The Arc data controller allows you to deploy, manage, secure, and monitor your deployed data services estate using Azure Data Studio or the Azure Portal (only for directly connected mode deployments) but giving you the same experience as if you were managing your data services from inside of the Azure Portal.

Part 3 deploys a Data Controller:

As previously mentioned there are 2 types of deployment available for your Arc Data Controller. In this post, we are going to have a look at deploying in the Arc Data Controller using the directly connected mode.

For a directly connected Arc Data Controller, we have direct connectivity to our Azure subscription. With this in mind, there are several options as we previously discussed on how to deploy the data controller. For this post, we are using the portal deployment method.

Finally, Part 4 covers management options:

With ADS open and running you can create connections to Arc Data Controllers the same as you can with Instances of SQL Server. In ADS we have under the connections area a section specific for Arc Data Controllers.

Check out all four posts.

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Optimizing Azure Pricing for Storage and VMs

Published 2022-08-18 by Kevin Feasel

Shane Baldacchino continues a series on cost optimization in the cloud:

Cost. I have been fortunate to work for and help migrate one of Australia’s leading websites (seek.com.au) in to the cloud and have worked for both large public cloud vendors. I have seen the really good, and the not so good when it comes to architecture.

Cloud and cost. It can be quite a polarising topic. Do it right, and you can run super lean, drive down the cost to serve and ride the cloud innovation train. But inversely do it wrong, treat public cloud like a datacentre then your costs could be significantly larger than on-premises.

Click through for some good advice, including an appreciation of spot instances.

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Power BI Field Parameters and None Options

Published 2022-08-18 by Kevin Feasel

Barney Lawrence votes None of the Above:


Field Parameters are one of my favourite recent additions to Power BI. The ability to turn a single chart into potentially dozens changes the way we think about putting variations of visuals on the page. It was a real wow moment for a client recently when I showed how field parameters for 5 fields and 5 measures could produce a single report page that replaced 25 of their existing reports.

While they theoretically don’t allow you to do much that you couldn’t previously with a disconnected slicer and a lot of DAX they build it faster and without the need to get heavily in to coding DAX. Anything that lowers the difficulty bar for users trying to make the most out of Power BI is a good thing in my book.

There are a couple of issues Barney has with them as they stand now but there are workarounds.

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