Nowadays the world has entered the big data era. Big data processing platforms, such as
Hadoop and Spark, are increasingly adopted by many applications, in which there are …

Apache Spark is one of the most widely used open source processing engines for big data,
with rich language-integrated APIs and a wide range of libraries. Over the past two years …

The past decade has seen rapid growth of distributed stream data processing systems.
Under these systems, a stream application is realized as a Directed Acyclic Graph (DAG) of …

The need for modern data analytics to combine relational, procedural, and map-reduce-style
functional processing is widely recognized. State-of-the-art systems like Spark have added …

The proliferation of big data and analytic workloads has driven the need for cloud compute
and cluster-based job processing. With Apache Spark, users can process terabytes of data …

Apache Spark applications often execute in multiple stages where each stage consists of
multiple tasks running in parallel. However, prior efforts noted that the execution time of …

Advanced analytics on your Big Data with latest Apache Spark 2. x About This Book An
advanced guide with a combination of instructions and practical examples to extend the …

Today's scientific applications are increasingly relying on a variety of data sources, storage
facilities, and computing infrastructures, and there is a growing demand for data analysis …

Apache Spark is one of the most popular big data tools. Despite its popularity, there are no
studies regarding its overall usage among software developers. As such, essential …

The frequently difficult process of examining large and diverse amounts of information is
known as" big data analysis." The goal is to find insights, such as hidden patterns …