Apache Spark 4.0 Everything You Must Know
Spark Connect is a protocol that specifies how a client application can communicate with a remote Spark Server. Clients that implement the Spark Connect protocol can connect and make requests to remote Spark Servers, very similar to how client applications can connect to databases using a JDBC driver — a query spark.table("some_table").limit(5) should simply return the result. This architecture gives end users a great developer experience
Apache Spark 4.0 introduces enhanced support for ANSI SQL, including features such as collation, which significantly improve the platform’s SQL capabilities and align it more closely with SQL standards used in traditional databases.
Simple API in Python for Data Sources. The idea is to enable Python developers to create data sources without having to learn Scala or deal with the complexities of the current data source APIs. The goal is to make a Python-based API that is simple and easy to use, thus making Spark more accessible to the wider Python developer community. This proposed approach is based on the recently introduced Python user-defined table functions (SPARK-43797) with extensions to support data sources.
