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A special type of class known as a case class is provided, which includes automatic support for pattern matching and can be used to model the algebraic data types used in many functional programming languages. (From the perspective of Scala, a case class is simply a normal class for which the compiler automatically adds certain behaviors that ...
The core of Apache Flink is a distributed streaming data-flow engine written in Java and Scala. [3] [4] Flink executes arbitrary dataflow programs in a data-parallel and pipelined (hence task parallel) manner. [5] Flink's pipelined runtime system enables the execution of bulk/batch and stream processing programs.
It provides a platform for building reactive applications for the JVM, consisting of the Play Framework, Akka middleware and Scala programming language, with additional supporting products and development tools such as the Slick database library for Scala and the sbt build tool. Lightbend also provides training, consulting and commercial ...
Lift is also designed to be a high-performance, scalable web framework by leveraging Scala actors to support more concurrent requests than is possible with a thread-per-request server. As Scala program code executes within the Java virtual machine (JVM), any existing Java library and web container can be used in running Lift applications.
sbt is the de facto build tool in the Scala community, [6] used, for example, by the Scala 2 and Scala 3 compilers themselves, [7] [8] Play Framework, and Lichess, a popular chess server. The sbt project is "bootstrapped" — it uses sbt to build itself and considers dogfooding a positive feature.
Spark Core is the foundation of the overall project. It provides distributed task dispatching, scheduling, and basic I/O functionalities, exposed through an application programming interface (for Java, Python, Scala, .NET [16] and R) centered on the RDD abstraction (the Java API is available for other JVM languages, but is also usable for some other non-JVM languages that can connect to the ...
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It was initially used by Twitter and emerged from a wide variety of data storage problems. Gizzard operated as a middleware networking service that ran on the Java Virtual Machine. It managed partitioning data across arbitrary backend datastores, which allowed it to be accessed efficiently.