Share
Big Data Processing Using Spark in Cloud
Mittal, Mamta ; Balas, Valentina E. ; Goyal, Lalit Mohan (Author)
·
Springer
· Paperback
Big Data Processing Using Spark in Cloud - Mittal, Mamta ; Balas, Valentina E. ; Goyal, Lalit Mohan
Choose the list to add your product or create one New List
✓ Product added successfully to the Wishlist.
Go to My Wishlists
Origin: U.S.A.
(Import costs included in the price)
It will be shipped from our warehouse between
Friday, July 26 and
Friday, August 02.
You will receive it anywhere in United Kingdom between 1 and 3 business days after shipment.
Synopsis "Big Data Processing Using Spark in Cloud"
The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark. The book mainly focuses on the in-depth architecture of Spark and our understanding of Spark RDDs and how RDD complements big data's immutable nature, and solves it with lazy evaluation, cacheable and type inference. It also addresses advanced topics in Spark, starting with the basics of Scala and the core Spark framework, and exploring Spark data frames, machine learning using Mllib, graph analytics using Graph X and real-time processing with Apache Kafka, AWS Kenisis, and Azure Event Hub. It then goes on to investigate Spark using PySpark and R. Focusing on the current big data stack, the book examines the interaction with current big data tools, with Spark being the core processing layer for all types of data. The book is intended for data engineers and scientists working on massive datasets and big data technologies in the cloud. In addition to industry professionals, it is helpful for aspiring data processing professionals and students working in big data processing and cloud computing environments.
