spark-fast-tests VS leapp

I was a Databricks user for 5 years and spent 95% of my time developing Spark code in IDEs. See the spark-daria and spark-fast-tests projects as Scala examples. I developed internal libraries with all the business logic. The Databricks notebooks would consist of a few lines of code that would invoke a function in the proprietary Spark codebase. The proprietary Spark codebase would depend on the OSS libraries I developed in parallel.

https://github.com/MrPowers/spark-fast-tests https://github.com/97arushisharma/Scala_Practice/tree/master/BigData_Analysis_with_Scala_and_Spark/wikipedia

If the majority of your stuff is not UDF-based there is an OS solution to run assertion tests against full data frames called spark-fast-tests. The idea here is similar in that you have a it notebook that calls your actual notebook against a staged input reads the output and compares it to a prefabed expected output. This does take a bit of setup and trial and error but it’s the closest I’ve been able to get to proper automated regression testing in databricks

I am the author of spark-fast-tests and chispa, libraries for unit testing Scala Spark / PySpark code.

I built daria (https://github.com/MrPowers/spark-daria) to make it easier to write Spark and spark-fast-tests (https://github.com/MrPowers/spark-fast-tests) to provide a good testing workflow.

quinn (https://github.com/MrPowers/quinn) and chispa (https://github.com/MrPowers/chispa) are the PySpark equivalents.

Built bebe (https://github.com/MrPowers/bebe) to expose the Spark Catalyst expressions that aren't exposed to the Scala / Python APIs.

Also build spark-sbt.g8 to create a Spark project with a single command: https://github.com/MrPowers/spark-sbt.g8

I've built popular PySpark (quinn, chispa) and Scala Spark (spark-daria, spark-fast-tests) libraries.

Summary:

Do you find yourself overwhelmed with work, requests, or complaints and in need of assistance to alleviate the pressure, enhance communication, facilitate organization, prioritize tasks, and foster greater trust and transparency?

Alternatively, I can work as a full stack developer.

AWS Community builder, AWS User group Leader, public speaker (https://www.youtube.com/watch?v=qdu58NAQfU0&t=271s)

Or perhaps you need both? =)

I have 4+ years of experience as a product manager and 8 in product development (before pm: agile coach, UX designer, and developer).

I've been the co-founder of the open-core company behind the OSS project Leapp (https://github.com/Noovolari/leapp)

Please feel free to reach out.

You can switch to saml2aws using the browser method instead of the Okta method and it will continue to work after the upgrade. There is also a really neat GUI tool to manage your session tokens that also works. https://www.leapp.cloud

Take a try to Leapp: https://github.com/Noovolari/leapp

Hello everyone, I'm the maintainer of an open-source DeveloperTool (https://github.com/Noovolari/leapp)

With a heuristic of 7000 users daily, I started feeling the need to have more information on how Users are using the project to improve it.

Is it the right thing to do to create a better Developer Experience and gain feedback for the end users?

On a side:

- For all your employees I can advice you Leapp as open-source project (https://github.com/Noovolari/leapp). It solve mayor of the problem listed here:

I am looking to manage Leapp (https://www.leapp.cloud/) from the StreamDeck. Leapp allows you to manage and switch between different Cloud Accounts (AWS, Azure, etc). Leapp has a command line interface which I could automate with a StreamDeck plugin. Unfortunately it looks like the only official SDK is the sandboxed JavaScript one. This means I cannot automate command line tools with it.

If you’re wondering if there is a tool that allows you to stop thinking about AWS credentials and where to store them in the right way, give a look at Leapp! It takes the responsibility of storing long-term credentials in the system vault, generating/refreshing short-term credentials, and placing them in the right place for the clients to use them.

Still, there is an elementary problem that we need to address, and it’s more on the operational side of things. Once we secured and implemented a tremendous multi-account strategy, how do people access AWS accounts? It turns out there is a fantastic open-source tool that lets you handle that with no effort, and its name is Leapp.

When you have to configure access to multiple AWS accounts using the Assume Role access pattern, it becomes difficult to get rid of all the Named Profiles configuration data and relationships. When you’ve to deal with a complex access scenario, tools like Leapp (https://www.leapp.cloud) come to the rescue! Leapp avoids you to specify relationships between Named Profiles in the config file, as the access methods are stored in the tool-specific configuration file.

Leapp Github repository