Kotlin for Apache Spark
summary
Introduces a new Kotlin API called continuity for Apache Spark that reimplements core Spark primitives, shows concrete code translating DataFrame/SQL and RDD patterns into idiomatic Kotlin, demonstrates interoperability with existing Java/Scala Spark code, and runs a small end-to-end ETL example built with Maven/Gradle to prove the API executes on Spark and is usable in real jobs.
AI-written summary · about
related talks
47mScala: The Unpredicted Lingua Franca for Data Science
35mExploratory Data Analysis with Spark and IntelliJ IDEA
33mTo Spark or Not to Spark
47mThe future of data: Apache Spark 3.1, Delta Lake and Koalas
01h 12mBig Data in Java World: Apache Spark and Scala. Arch and live coding
51mDataFrame: Kotlin's Innovative Approach to Data Structures
43mKotlin 4 vs. Scala 3
46mScala and the JVM as a Big Data Platform
