Dec 15 - 16, 2017
Oct 13, 2017
Apache Spark is one of the most popular Big Data frameworks today. It is fast becoming the de facto technology choice for stream processing, real-time analytics, data science and machine learning applications at scale. It has moved well beyond the early-adopter phase, is supported by a vibrant open source community and is enjoying accelerated adoption in enterprises.
Aug 23, 2017
The adoption of Apache Spark to analyze data in real-time is increasing with its ability to handle sophisticated analytical requirements and a common framework for streaming and batch. However, most organizations are also looking for "true streaming" features like lower latency and the ability to process out-of-order data.
Structured Streaming, a new high-level API, introduced in Apache Spark 2.0 promises these and other enhancements to the Spark approach to streaming data processing.
Jun 17, 2016
Real-time streaming analytics and IoT seem to be the next big thing in the data and analytics industry. As enterprises adopt Apache Spark and Spark Streaming widely, IT teams are facing the challenge to provide the tools and the framework needed to make Apache Spark Streaming an easy-to-use, robust, scalable and multi-tenant service.