Big Data Processing Using Spark in Cloud – Mamta Mittal

The edited book “Big Data Processing using Spark in Cloud” takes deep into Spark while starting with the basics of Scala and core Spark framework, and then explore Spark data frames, machine learning using MLlib, graph analytics using graph X, and real-time processing with Apache Kafka, AWS Kinesis, and Azure Event Hub. We will also explore Spark using PySpark and R., apply the knowledge that so far we have learnt about Spark, and will work on real datasets and do some exploratory analytics first, then move on to predictive modeling on Boston Housing Datasets, and then move forward to build news content-based recommender system using NLP and MLlib, collaborative filtering-based movies recommender system, and page rank using GraphX. This book also discusses how to tune Spark parameters for production scenarios and how to write robust applications in Apache Spark using Scala in cloud computing environment.

The book is organized into 11 chapters.

Chapter “A Survey on Big Data—Its Challenges and Solution from Vendors” carried out a detailed survey depicting the enormous information and its difficulties alongside the advancements required to deal with huge data. This moreover por­trays the conventional methodologies which were utilized before to manage information, their impediments, and how it is being overseen by the new approach Hadoop. It additionally portrays the working of Hadoop along with its pros and cons and security on huge data.

Chapter “Big Data Streaming with Spark” introduces many concepts associated with Spark Streaming, including a discussion of supported operations. Finally, two other important platforms and their integration with Spark, namely Apache Kafka and Amazon Kinesis, are explored.

Chapter “Big Data Analysis in Cloud and Machine Learning” discusses data which is considered to be the lifeblood of any business organization, as it is the data that streams into actionable insights of businesses. The data available with the organizations is so much in volume that it is popularly referred as Big Data. It is the hottest buzzword spanning the business and technology worlds. Economies over the world are using Big Data and Big Data analytics as a new frontier for business so as to plan smarter business moves, improve productivity and performance, and plan strategy more effectively. To make Big Data analytics effective, storage technologies and analytical tools play a critical role. However, it is evident that Big Data places rigorous demands on networks, storage, and servers, which has motivated organi­zations and enterprises to move on cloud, in order to harvest maximum benefits of the available Big Data. Furthermore, we are also aware that traditional analytics tools are not well suited to capturing the full value of Big Data. Hence, machine learning seems to be an ideal solution for exploiting the opportunities hidden in Big Data. In this chapter, we shall discuss Big Data and Big Data analytics with a special focus on cloud computing and machine learning.

Chapter “Cloud Computing Based Knowledge Mapping Between Existing and Possible Academic Innovations—An Indian Techno-Educational Context” dis­cusses various applications in cloud computing that allow healthy and wider effi­cient computing services in terms of providing centralized services of storage, applications, operating systems, processing, and bandwidth. Cloud computing is a type of architecture which helps in the promotion of scalable computing. Cloud computing is also a kind of resource-sharing platform and thus needed in almost all the spectrum and areas regardless of its type. Today, cloud computing has a wider market, and it is growing rapidly. The manpower in this field is mainly outsourced from the IT and computing services, but there is an urgent need to offer cloud computing as full-fledged bachelors and masters programs. In India also, cloud computing is rarely seen as an education program, but the situation is now changing. There is high potential to offer cloud computing in Indian educational segment. This paper is conceptual in nature and deals with the basics of cloud computing, its need, features, types existing, and possible programs in the Indian context, and also proposed several programs which ultimately may be helpful for building solid Digital India.


  1. A Survey on Big Data—Its Challenges and Solution from Vendors
  2. Big Data Streaming with Spark
  3. Big Data Analysis in Cloud and Machine Learning
  4. Cloud Computing Based Knowledge Mapping Between Existing and Possible Academic Innovations—An Indian Techno-Educational Context
  5. Data Processing Framework Using Apache and Spark Technologies in Big Data
  6. Implementing Big Data Analytics Through Network Analysis Software Applications in Strategizing Higher Learning Institutions
  7. Machine Learning on Big Data: A Developmental Approach on Societal Applications
  8. Personalized Diabetes Analysis Using Correlation-Based Incremental Clustering Algorithm
  9. Processing Using Spark—A Potent of BD Technology
  10. Recent Developments in Big Data Analysis Tools and Apache Spark
  11. SCSI: Real-Time Data Analysis with Cassandra and Spark
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