From the article:
With hundreds of developers and millions of lines of code, Databricks is one of the largest Scala shops around. This post will be a broad tour of Scala at Databricks, from its inception to usage, style, tooling and challenges. We will cover topics ranging from cloud infrastructure and bespoke language tooling to the human processes around managing our large Scala codebase. From this post, you’ll learn about everything big and small that goes into making Scala at Databricks work, a useful case study for anyone supporting the use of Scala in a growing organization.
Databricks was built by the original creators of Apache Spark™, and began as distributed Scala collections. Scala was picked because it is one of the few languages that had serializable lambda functions, and because its JVM runtime allows easy interop with the Hadoop-based big-data ecosystem. Since then, both Spark and Databricks have grown far beyond anyone’s initial imagination. The details of that growth are beyond the scope of this post, but the initial Scala foundation remained.
