Visual Spark Studio IDE For Spark Apps
Visual Spark Studio IDE For Spark Apps
Written by Kay Ewbank   
Thursday, 01 March 2018

A new free IDE has been released that lets you build, test and run Apache Spark apps on your desktop. Visual Spark Studio is a free cut-down version of the Impetus StreamAnalytix platform. It provides a lightweight development tool for data processing and analytics on Spark data.

Apache Spark is a general-purpose cluster computing framework, with native support for distributed SQL, streaming, graph processing, and machine learning.


The new IDE can be used to build Spark apps for for both batch and streaming mode. It is a free, quick-start lightweight product that is a A Spark-only version of StreamAnalytix (an open-source enabled, enterprise-grade, stream processing and machine learning platform). Visual Spark Studio keeps the StreamAnalytix interface and has ready-to-use operators to select, drag-and-drop, connect, and configure connectors to create a fully functional Spark pipeline.


The IDE can be used to receive data from a range of local data sources and data targets, and includes all the analytics and machine learning capabilities of StreamAnalytix on a single instance. There's also an option to export and scale out pipelines to a multi-node Spark cluster using the enterprise version of StreamAnalytix. 

Visual Spark Studio has drag-and-drop operators for data source, sink, transformation, and analytics, or you can use custom logic with Java and Scala operators. There's a pipeline designer for application development and built-in dashboards for real-time visualization of data. The data sources that you can write into include HDFS, Kafka, RDBMS, and Solr, and there are built in
operators for predictive models, Spark MLlib, ML and PMML for model-porting.

Visual Spark Studio is available for Windows, Linux and Mac, and while the aim of the developers is obviously to encourage you to move to StreamAnalytix, Spark Studio offers a useful way to get to grips with Spark and the concepts behind it.



More Information

Visual Spark Studio Website

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