Databricks Contributes Spark Declarative Pipelines to Apache Spark
Databricks is contributing the technology behind Delta Live Tables (DLT) to the Apache Spark project as Spark Declarative Pipelines, simplifying the development of streaming pipelines.
RDD vs DataFrame vs Dataset in Apache Spark: Which One Should You Use and Why
Spark offers three main APIs—RDD, DataFrame, and Dataset—each with unique advantages: RDD provides low-level control, DataFrames optimize performance, and Datasets bring type safety.
Both cache() and persist() store an RDD/DataFrame/Dataset in memory (or disk) to avoid recomputation. cache() is shorthand for persist(StorageLevel.MEMORY_ONLY), while persist() offers more control.