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sbt, a widely used build tool for Scala projects; Spark Framework is designed to handle, and process big-data and it solely supports Scala; Neo4j is a java spring framework supported by Scala with domain-specific functionality, analytical capabilities, graph algorithms, and many more; Play!, an open-source Web application framework that ...
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 ...
Other functional programming languages that have seen use in industry include Scala, [120] F#, [18] [19] Wolfram Language, [7] Lisp, [121] Standard ML [122] [123] and Clojure. [124] Scala has been widely used in Data science, [125] while ClojureScript, [126] Elm [127] or PureScript [128] are some of the functional frontend programming languages ...
Apache Kafka is a distributed event store and stream-processing platform. It is an open-source system developed by the Apache Software Foundation written in Java and Scala.The project aims to provide a unified, high-throughput, low-latency platform for handling real-time data feeds.
The platform consists of a workspace that includes multiple collaboration and open-source tools for use in data science. [1] In Watson Studio, a data scientist can create a project with a group of collaborators, all having access to various analytics models and using various languages (R/Python/Scala).
The DataStream API includes more than 20 different types of transformations and is available in Java and Scala. [22] A simple example of a stateful stream processing program is an application that emits a word count from a continuous input stream and groups the data in 5-second windows:
DataLab: platform for creating self-service, exploratory data science environments in the cloud using best-of-breed data science tools; DevLake: development data platform, providing the data infrastructure for developer teams to analyze and improve their engineering productivity; HugeGraph: a large-scale and easy-to-use graph database
An actor implementation, written by Philipp Haller, was released in July 2006 as part of Scala 2.1.7. [4] By 2008 Scala was attracting attention for use in complex server applications, but concurrency was still typically achieved by creating threads that shared memory and synchronized when necessary using locks.