Abstract As Big Data processing problems evolve, many modern applications demonstrate
special characteristics. Data exists in the form of both large historical datasets and high …

This paper addresses online query processing for large-scale, incremental data analysis on
a distributed stream processing engine (DSPE). Our goal is to convert any SQL-like query to …

Apache Spark: a unified engine for big data processing Page 1 56 COMMUNICATIONS OF THE
ACM | NOVEMBER 2016 | VOL. 59 | NO. 11 contributed articles DOI:10.1145/2934664 This …

There is high demand for techniques and tools to process and analyze large sets of
streaming data in both industrial and academic settings. While existing work in this area has …

Design, process, and analyze large sets of complex data in real time About This Book Get
acquainted with transformations and database-level interactions, and ensure the reliability of …

The demand for stream processing is increasing at an unprecedented rate. Big data is no
longer limited to processing of big volumes of data. In most real-world scenarios, the need …

Abstract The era of Big Data has ushered in an unprecedented era of data abundance
across various domains. In this context, the need for processing and analyzing vast datasets …

Introduction to Apache Spark for Large-Scale Data Analytics | SpringerLink Skip to main
content Advertisement SpringerLink Account Menu Find a journal Publish with us Track your …

Today data are being continuously generated in large volume and high speed from
multitude of heterogeneous sources (eg, Internet of Things, smart cities, social media …

As many commercial businesses aspire for a competitive edge, real-time analysis on
streaming data employing a big data methodology has lately become widespread. The …