Running R Jobs using Prefect

Prefect

Prefect is an open-source workflow management system that allows you to build, schedule, and monitor data workflows. It enables you to transform any Python function into a unit of work that can be observed and orchestrated. Prefect can be used for various use cases such as ETL pipelines, machine learning workflows, data warehousing, and more. It has a dynamic engine and ephemeral API that makes it easy to run workflows interactively during the building phase. Prefect also offers the ability to cache and persist inputs and outputs for large files and expensive operations, improving development time when debugging.

R

R is a programming language that was created for statistical computing and graphics. It has become increasingly popular over the years because of its flexibility, ease of use, and powerful data analysis capabilities. R has a rich ecosystem with complex data models and elegant tools for data reporting. It offers a wide variety of statistics-related libraries and provides a favorable environment for statistical computing and design. R is especially popular among data scientists, statisticians, and researchers who work with large datasets. It is used for data analysis, statistical inference, machine learning algorithms, and data visualization. R can also be used for creating reproducible, high-quality research reports.

Open source orchestrators like Prefect are one of the primary means by which companies leverage R in production. Prefect offers a mechanism to schedule and monitor these jobs as part of more complex workflow graphs. Kaspian has a native operator for Prefect; this operator makes it easy to either swap to or get started with running R jobs that utilize Kaspian's flexible compute layer.

Learn more about Kaspian and see how our flexible compute layer for the modern data cloud is already reshaping the way companies in industries like retail, manufacturing and logistics are thinking about data engineering and analytics.