Kotlin is a cross-platform, statically typed, general-purpose JVM language. In the last year more than 5 million developers have used Kotlin in mobile, backend, frontend and scientific development. The number of Kotlin developers grows rapidly every year.
- According to redmonk: "Kotlin, the second fastest growing language we’ve seen outside of Swift, made a big splash a year ago at this time when it vaulted eight full spots up the list."
- According to snyk.io, Kotlin is the second most popular language on the JVM
- According to StackOverflow Kotlin’s share increased by 7.8% in 2020.
We notice the increasing usage of Kotlin in data analysis (6% of users in 2020, as opposed to 2% in 2019) and machine learning (3% of users in 2020, as opposed to 0% in 2019), and we expect these numbers to continue to grow.
We, authors of this SPIP, strongly believe that making Kotlin API officially available to developers can bring new users to Apache Spark and help some of the existing users.
The goal of this project is to bring first-class support for Kotlin language into the Apache Spark project. We’re going to achieve this by adding one more module to the current Apache Spark distribution.
There is no goal to replace any existing language support or to change any existing Apache Spark API.
At this time, there is no goal to support non-core APIs of Apache Spark like Spark ML and Spark structured streaming. This may change in the future based on community feedback.
There is no goal to provide CLI for Kotlin for Apache Spark, this will be a separate SPIP.
There is no goal to provide support for Apache Spark < 3.0.0.
A working prototype is available at https://github.com/JetBrains/kotlin-spark-api. It has been tested inside JetBrains and by early adopters.
There is always a risk that this product won’t get enough popularity and will bring more costs than benefits. It can be mitigated by the fact that we don't need to change any existing API and support can be potentially dropped at any time.
We also believe that existing API is rather low maintenance. It does not bring anything more complex than already exists in the Spark codebase. Furthermore, the implementation is compact - less than 2000 lines of code.
We are committed to maintaining, improving and evolving the API based on feedback from both Spark and Kotlin communities. As the Kotlin data community continues to grow, we see Kotlin API for Apache Spark as an important part in the evolving Kotlin ecosystem, and intend to fully support it.
A working implementation is already available, and if the community will have any proposal of changes for this implementation to be improved, these can be implemented quickly — in weeks if not days.