Big Data Processing Using Spark In Cloud

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Big Data Processing Using Spark In Cloud

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Author : Mamta Mittal
language : en
Publisher: Springer
Release Date : 2018-06-16

Big Data Processing Using Spark In Cloud written by Mamta Mittal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-16 with Computers categories.

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.

Big Data Analytics

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Author : Dr. N. Bharathi, SVNN Mahesh Duriseati, Dr. Divvela Srinivasa Rao, J.Rohini
language : en
Publisher: BR Publications
Release Date : 2025-10-27

Big Data Analytics written by Dr. N. Bharathi, SVNN Mahesh Duriseati, Dr. Divvela Srinivasa Rao, J.Rohini and has been published by BR Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-27 with Computers categories.

Big Data Analytics is the process of examining large, complex, and rapidly growing datasets—called big data—to uncover hidden patterns, trends, correlations, and useful insights. These datasets are too large or fast-changing to be processed using traditional data analysis tools. Big Data Analytics uses advanced techniques such as machine learning, data mining, statistical analysis, and predictive modeling to extract meaningful information that supports decision-making.

Mastering Apache Spark

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Author : Greyson Chesterfield
language : en
Publisher: Independently Published
Release Date : 2024-12-09

Mastering Apache Spark written by Greyson Chesterfield and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-09 with Computers categories.

Unlock the power of big data with Mastering Apache Spark: Real-Time Big Data Analytics! This comprehensive guide is your ultimate resource for building, processing, and analyzing large-scale data using Apache Spark, the fast, flexible, and powerful open-source framework for big data processing. Whether you're a data engineer, scientist, or analyst, this book will teach you how to harness Spark's real-time analytics capabilities to process and analyze massive datasets. Apache Spark is widely used for its speed, ease of use, and scalability. It's the go-to solution for building data pipelines, running machine learning algorithms, and processing streams of real-time data. In this book, you'll learn everything from the fundamentals of Spark to advanced techniques for scaling your big data workflows. What's Inside: Getting Started with Apache Spark: Learn the core concepts behind Apache Spark, including Spark RDDs, DataFrames, and Spark SQL, and how to set up Spark on your system or in the cloud. Real-Time Data Processing: Dive into real-time data processing with Spark Streaming, handling live data streams, and building real-time analytics applications. Building Data Pipelines: Learn how to design and implement scalable data pipelines that can process large volumes of structured and unstructured data. Data Analytics with Spark: Explore how to analyze big data using Spark's powerful libraries, including Spark MLlib for machine learning and Spark GraphX for graph processing. Optimizing Spark Performance: Discover strategies to optimize Spark performance, including partitioning, caching, and using the Catalyst optimizer for SQL queries. Advanced Spark Topics: Get hands-on with advanced topics like Spark on Kubernetes, Spark integration with Hadoop, and deploying Spark on cloud platforms such as AWS and Azure. Batch vs. Stream Processing: Learn when to use batch processing and when to go for stream processing for different use cases in data analytics. Use Cases and Real-World Applications: Explore real-world use cases for Spark in industries like finance, healthcare, e-commerce, and IoT. By the end of this book, you'll be equipped with the knowledge and hands-on experience to build efficient, scalable data pipelines and perform advanced real-time big data analytics using Apache Spark. Ready to master big data with Spark? Grab your copy now and start building powerful, high-performance data solutions that scale with your business needs!

Advancement Of Machine Intelligence In Interactive Medical Image Analysis

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Author : Om Prakash Verma
language : en
Publisher: Springer Nature
Release Date : 2019-12-11

Advancement Of Machine Intelligence In Interactive Medical Image Analysis written by Om Prakash Verma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-11 with Computers categories.

The book discusses major technical advances and research findings in the field of machine intelligence in medical image analysis. It examines the latest technologies and that have been implemented in clinical practice, such as computational intelligence in computer-aided diagnosis, biological image analysis, and computer-aided surgery and therapy. This book provides insights into the basic science involved in processing, analysing, and utilising all aspects of advanced computational intelligence in medical decision-making based on medical imaging.

Big Data Analytics Systems Algorithms Applications

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Author : C.S.R. Prabhu
language : en
Publisher: Springer Nature
Release Date : 2019-10-14

Big Data Analytics Systems Algorithms Applications written by C.S.R. Prabhu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-14 with Computers categories.

This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.

The Smart Cyber Ecosystem For Sustainable Development

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Author : Pardeep Kumar
language : en
Publisher: John Wiley & Sons
Release Date : 2021-10-12

The Smart Cyber Ecosystem For Sustainable Development written by Pardeep Kumar and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-12 with Technology & Engineering categories.

The Smart Cyber Ecosystem for Sustainable Development As the entire ecosystem is moving towards a sustainable goal, technology driven smart cyber system is the enabling factor to make this a success, and the current book documents how this can be attained. The cyber ecosystem consists of a huge number of different entities that work and interact with each other in a highly diversified manner. In this era, when the world is surrounded by many unseen challenges and when its population is increasing and resources are decreasing, scientists, researchers, academicians, industrialists, government agencies and other stakeholders are looking toward smart and intelligent cyber systems that can guarantee sustainable development for a better and healthier ecosystem. The main actors of this cyber ecosystem include the Internet of Things (IoT), artificial intelligence (AI), and the mechanisms providing cybersecurity. This book attempts to collect and publish innovative ideas, emerging trends, implementation experiences, and pertinent user cases for the purpose of serving mankind and societies with sustainable societal development. The 22 chapters of the book are divided into three sections: Section I deals with the Internet of Things, Section II focuses on artificial intelligence and especially its applications in healthcare, whereas Section III investigates the different cyber security mechanisms. Audience This book will attract researchers and graduate students working in the areas of artificial intelligence, blockchain, Internet of Things, information technology, as well as industrialists, practitioners, technology developers, entrepreneurs, and professionals who are interested in exploring, designing and implementing these technologies.

Apache Spark 2 Data Processing And Real Time Analytics

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Author : Romeo Kienzler
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-21

Apache Spark 2 Data Processing And Real Time Analytics written by Romeo Kienzler and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-21 with Computers categories.

Build efficient data flow and machine learning programs with this flexible, multi-functional open-source cluster-computing framework Key FeaturesMaster the art of real-time big data processing and machine learning Explore a wide range of use-cases to analyze large data Discover ways to optimize your work by using many features of Spark 2.x and ScalaBook Description Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. This Learning Path includes content from the following Packt products: Mastering Apache Spark 2.x by Romeo KienzlerScala and Spark for Big Data Analytics by Md. Rezaul Karim, Sridhar AllaApache Spark 2.x Machine Learning Cookbook by Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen MeiCookbookWhat you will learnGet to grips with all the features of Apache Spark 2.xPerform highly optimized real-time big data processing Use ML and DL techniques with Spark MLlib and third-party toolsAnalyze structured and unstructured data using SparkSQL and GraphXUnderstand tuning, debugging, and monitoring of big data applications Build scalable and fault-tolerant streaming applications Develop scalable recommendation enginesWho this book is for If you are an intermediate-level Spark developer looking to master the advanced capabilities and use-cases of Apache Spark 2.x, this Learning Path is ideal for you. Big data professionals who want to learn how to integrate and use the features of Apache Spark and build a strong big data pipeline will also find this Learning Path useful. To grasp the concepts explained in this Learning Path, you must know the fundamentals of Apache Spark and Scala.

Advances And Applications Of Artificial Intelligence Machine Learning

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Author : Bhuvan Unhelkar
language : en
Publisher: Springer Nature
Release Date : 2023-11-14

Advances And Applications Of Artificial Intelligence Machine Learning written by Bhuvan Unhelkar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-14 with Technology & Engineering categories.

This volume comprises the select peer-reviewed proceedings of the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning 2022 (ICAAAIML 2022). It aims to provide a comprehensive and broad-spectrum picture of state-of-the-art research and development in the areas of artificial intelligence, machine learning, deep learning, and their advanced applications in computer vision and blockchain. It also covers research in core concepts of computers, intelligent system design and deployment, real-time systems, WSN, sensors and sensor nodes, software engineering, image processing, and cloud computing. This volume will provide a valuable resource for those in academia and industry.

Computing Communication And Learning

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Author : Sanjaya Kumar Panda
language : en
Publisher: Springer Nature
Release Date : 2024-03-30

Computing Communication And Learning written by Sanjaya Kumar Panda and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-30 with Computers categories.

This volume constitutes the refereed proceedings of the Second International Conference on Computing, Communication and Learning, CoCoLe 2023, held in Warangal, India, in August 29–31, 2023. The 25 full papers presented were carefully reviewed and selected from 120 submissions. The CoCoLe conference focuses on Application of Supervised Learning in Computing; Application of Unsupervised Learning in Computing; and Computing in Communication Networks.

Ultimate Big Data Analytics With Apache Hadoop Master Big Data Analytics With Apache Hadoop Using Apache Spark Hive And Python

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Author : Simhadri Govindappa
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2024-09-09

Ultimate Big Data Analytics With Apache Hadoop Master Big Data Analytics With Apache Hadoop Using Apache Spark Hive And Python written by Simhadri Govindappa and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-09 with Computers categories.

Master the Hadoop Ecosystem and Build Scalable Analytics Systems Key Features● Explains Hadoop, YARN, MapReduce, and Tez for understanding distributed data processing and resource management. ● Delves into Apache Hive and Apache Spark for their roles in data warehousing, real-time processing, and advanced analytics. ● Provides hands-on guidance for using Python with Hadoop for business intelligence and data analytics. Book Description In a rapidly evolving Big Data job market projected to grow by 28% through 2026 and with salaries reaching up to $150,000 annually—mastering big data analytics with the Hadoop ecosystem is most sought after for career advancement. The Ultimate Big Data Analytics with Apache Hadoop is an indispensable companion offering in-depth knowledge and practical skills needed to excel in today's data-driven landscape. The book begins laying a strong foundation with an overview of data lakes, data warehouses, and related concepts. It then delves into core Hadoop components such as HDFS, YARN, MapReduce, and Apache Tez, offering a blend of theory and practical exercises. You will gain hands-on experience with query engines like Apache Hive and Apache Spark, as well as file and table formats such as ORC, Parquet, Avro, Iceberg, Hudi, and Delta. Detailed instructions on installing and configuring clusters with Docker are included, along with big data visualization and statistical analysis using Python. Given the growing importance of scalable data pipelines, this book equips data engineers, analysts, and big data professionals with practical skills to set up, manage, and optimize data pipelines, and to apply machine learning techniques effectively. Don’t miss out on the opportunity to become a leader in the big data field to unlock the full potential of big data analytics with Hadoop. What you will learn ● Gain expertise in building and managing large-scale data pipelines with Hadoop, YARN, and MapReduce. ● Master real-time analytics and data processing with Apache Spark’s powerful features. ● Develop skills in using Apache Hive for efficient data warehousing and complex queries. ● Integrate Python for advanced data analysis, visualization, and business intelligence in the Hadoop ecosystem. ● Learn to enhance data storage and processing performance using formats like ORC, Parquet, and Delta. ● Acquire hands-on experience in deploying and managing Hadoop clusters with Docker and Kubernetes. ● Build and deploy machine learning models with tools integrated into the Hadoop ecosystem. Table of Contents 1. Introduction to Hadoop and ASF 2. Overview of Big Data Analytics 3. Hadoop and YARN MapReduce and Tez 4. Distributed Query Engines: Apache Hive 5. Distributed Query Engines: Apache Spark 6. File Formats and Table Formats (Apache Ice-berg, Hudi, and Delta) 7. Python and the Hadoop Ecosystem for Big Data Analytics - BI 8. Data Science and Machine Learning with Hadoop Ecosystem 9. Introduction to Cloud Computing and Other Apache Projects Index