The term Scala originated from “Scalable language” and it means that Scala grows with you. In recent times, Scala has attracted developers because it has enabled them to deliver things faster with fewer codes. Developers are now much more interested in having Scala training to excel in the big data field. The Scala community has grown over the years and it has now become a standard for enterprise, start-ups and universities alike. Scala is now being used by many companies and individuals to build their own new ideas. Play Framework, Akka, Apache Spark, etc are some of the tools and projects created using Scala.
Scala is now the next wave of computation engines and more importance has been given to the speed processing rather than the size of the batch, and the ability to process event streaming in real-time.
Apache Spark can be considered as the replacement of MapReduce. In late 2013, Cloudera, the largest Hadoop vendor supported the idea of replacing MapReduce with Apache Spark.
Spark is developed by AMPLab and it is a fast and general purpose engine for large-scale data processing. Spark effectively provides an alternative for Hadoop’s two stage MapReduce model. It has improved the performance of certain applications to 100 times with its fine grain operators, in-memory caching of intermediate data, and data flow optimization.
Scalding has been introduced and maintained by Twitter. It provides full benefits of Scala syntax and functional operations. Scala is a powerful language for solving functional problems. Scalding makes comprehensive use of Scala and it is an extension to cascading that enables application development with Scala.
If we focus on the benefits of Scalding, data applications can be built with Scala. With simple and concise syntax code becomes easier to interpret. Scalding has filled the benefits of cascading application framework.
3. Apache Kafka
Built and maintained by LinkedIn, Apache Kafka is a distributed streaming platform. Apache Kafka allows the user to publish and subscribe streams of data, just like a messaging system. Kafka is responsible for handling hundred of megabytes of read-write traffic per second from thousand of clients. It is also empowered by Scala and we can see the influence of the language. Real-time data pipelines and streaming apps can be built by using Apache Kafka.
Yahoo Kafka Manager is also written in Scala and the web console is built using Play Framework. The Kafka Manager is being used by many teams including the Media Analytics team. It interacts with an actor-based, in-memory model built with Akka and Apache Curator.
Built by the people at twitter, Finagle can be considered as one of the best case using Scala. It is used to build high-concurrency servers and is an extensible RPC system for JVM. Finagle was intended to provide high performance, concurrency along with Scala and Java idiomatic APIs.
Finagle is known for the optimal use of available system resources and high scalability through concurrency. It uses safe, simple and clean concurrent programming model which is based on Futures. All these results in safe and modular programs.