Apache Spark 2 X For Java Developers

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Apache Spark 2 X For Java Developers

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Author : Sourav Gulati
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-07-26

Apache Spark 2 X For Java Developers written by Sourav Gulati 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 2017-07-26 with Computers categories.

Unleash the data processing and analytics capability of Apache Spark with the language of choice: Java About This Book Perform big data processing with Spark—without having to learn Scala! Use the Spark Java API to implement efficient enterprise-grade applications for data processing and analytics Go beyond mainstream data processing by adding querying capability, Machine Learning, and graph processing using Spark Who This Book Is For If you are a Java developer interested in learning to use the popular Apache Spark framework, this book is the resource you need to get started. Apache Spark developers who are looking to build enterprise-grade applications in Java will also find this book very useful. What You Will Learn Process data using different file formats such as XML, JSON, CSV, and plain and delimited text, using the Spark core Library. Perform analytics on data from various data sources such as Kafka, and Flume using Spark Streaming Library Learn SQL schema creation and the analysis of structured data using various SQL functions including Windowing functions in the Spark SQL Library Explore Spark Mlib APIs while implementing Machine Learning techniques to solve real-world problems Get to know Spark GraphX so you understand various graph-based analytics that can be performed with Spark In Detail Apache Spark is the buzzword in the big data industry right now, especially with the increasing need for real-time streaming and data processing. While Spark is built on Scala, the Spark Java API exposes all the Spark features available in the Scala version for Java developers. This book will show you how you can implement various functionalities of the Apache Spark framework in Java, without stepping out of your comfort zone. The book starts with an introduction to the Apache Spark 2.x ecosystem, followed by explaining how to install and configure Spark, and refreshes the Java concepts that will be useful to you when consuming Apache Spark's APIs. You will explore RDD and its associated common Action and Transformation Java APIs, set up a production-like clustered environment, and work with Spark SQL. Moving on, you will perform near-real-time processing with Spark streaming, Machine Learning analytics with Spark MLlib, and graph processing with GraphX, all using various Java packages. By the end of the book, you will have a solid foundation in implementing components in the Spark framework in Java to build fast, real-time applications. Style and approach This practical guide teaches readers the fundamentals of the Apache Spark framework and how to implement components using the Java language. It is a unique blend of theory and practical examples, and is written in a way that will gradually build your knowledge of Apache Spark.

Learning Spark

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Author : Jules S. Damji
language : en
Publisher: O'Reilly Media
Release Date : 2020-07-16

Learning Spark written by Jules S. Damji and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-16 with Computers categories.

Data is bigger, arrives faster, and comes in a variety of formatsâ??and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, youâ??ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow

Frank Kane S Taming Big Data With Apache Spark And Python

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Author : Frank Kane
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-06-30

Frank Kane S Taming Big Data With Apache Spark And Python written by Frank Kane 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 2017-06-30 with Computers categories.

Frank Kane's hands-on Spark training course, based on his bestselling Taming Big Data with Apache Spark and Python video, now available in a book. Understand and analyze large data sets using Spark on a single system or on a cluster. About This Book Understand how Spark can be distributed across computing clusters Develop and run Spark jobs efficiently using Python A hands-on tutorial by Frank Kane with over 15 real-world examples teaching you Big Data processing with Spark Who This Book Is For If you are a data scientist or data analyst who wants to learn Big Data processing using Apache Spark and Python, this book is for you. If you have some programming experience in Python, and want to learn how to process large amounts of data using Apache Spark, Frank Kane's Taming Big Data with Apache Spark and Python will also help you. What You Will Learn Find out how you can identify Big Data problems as Spark problems Install and run Apache Spark on your computer or on a cluster Analyze large data sets across many CPUs using Spark's Resilient Distributed Datasets Implement machine learning on Spark using the MLlib library Process continuous streams of data in real time using the Spark streaming module Perform complex network analysis using Spark's GraphX library Use Amazon's Elastic MapReduce service to run your Spark jobs on a cluster In Detail Frank Kane's Taming Big Data with Apache Spark and Python is your companion to learning Apache Spark in a hands-on manner. Frank will start you off by teaching you how to set up Spark on a single system or on a cluster, and you'll soon move on to analyzing large data sets using Spark RDD, and developing and running effective Spark jobs quickly using Python. Apache Spark has emerged as the next big thing in the Big Data domain – quickly rising from an ascending technology to an established superstar in just a matter of years. Spark allows you to quickly extract actionable insights from large amounts of data, on a real-time basis, making it an essential tool in many modern businesses. Frank has packed this book with over 15 interactive, fun-filled examples relevant to the real world, and he will empower you to understand the Spark ecosystem and implement production-grade real-time Spark projects with ease. Style and approach Frank Kane's Taming Big Data with Apache Spark and Python is a hands-on tutorial with over 15 real-world examples carefully explained by Frank in a step-by-step manner. The examples vary in complexity, and you can move through them at your own pace.

Cyber Physical Systems And Control

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Author : Dmitry G. Arseniev
language : en
Publisher: Springer Nature
Release Date : 2019-11-29

Cyber Physical Systems And Control written by Dmitry G. Arseniev and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-29 with Science categories.

This book presents the proceedings of the International Conference on Cyber-Physical Systems and Control (CPS&C'2019), held in Peter the Great St. Petersburg Polytechnic University, which is celebrating its 120th anniversary in 2019. The CPS&C'2019 was dedicated to the 35th anniversary of the partnership between Peter the Great St. Petersburg Polytechnic University and Leibniz University of Hannover. Cyber-physical systems (CPSs) are a new generation of control systems and techniques that help promote prospective interdisciplinary research. A wide range of theories and methodologies are currently being investigated and developed in this area to tackle various complex and challenging problems. Accordingly, CPSs represent a scientific and engineering discipline that is set to make an impact on future systems of industrial and social scale that are characterized by the deep integration of real-time processing, sensing, and actuation into logical and physical heterogeneous domains. The CPS&C'2019 brought together researchers and practitioners from all over the world and to discuss cross-cutting fundamental scientific and engineering principles that underline the integration of cyber and physical elements across all application fields. The participants represented research institutions and universities from Austria, Belgium, Bulgaria, China, Finland, Germany, the Netherlands, Russia, Syria, Ukraine, the USA, and Vietnam. These proceedings include 75 papers arranged into five sections, namely keynote papers, fundamentals, applications, technologies, and education and social aspects.

Hadoop Blueprints

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Author : Anurag Shrivastava
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-09-30

Hadoop Blueprints written by Anurag Shrivastava 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 2016-09-30 with Computers categories.

Use Hadoop to solve business problems by learning from a rich set of real-life case studies About This Book Solve real-world business problems using Hadoop and other Big Data technologies Build efficient data lakes in Hadoop, and develop systems for various business cases like improving marketing campaigns, fraud detection, and more Power packed with six case studies to get you going with Hadoop for Business Intelligence Who This Book Is For If you are interested in building efficient business solutions using Hadoop, this is the book for you This book assumes that you have basic knowledge of Hadoop, Java, and any scripting language. What You Will Learn Learn about the evolution of Hadoop as the big data platform Understand the basics of Hadoop architecture Build a 360 degree view of your customer using Sqoop and Hive Build and run classification models on Hadoop using BigML Use Spark and Hadoop to build a fraud detection system Develop a churn detection system using Java and MapReduce Build an IoT-based data collection and visualization system Get to grips with building a Hadoop-based Data Lake for large enterprises Learn about the coexistence of NoSQL and In-Memory databases in the Hadoop ecosystem In Detail If you have a basic understanding of Hadoop and want to put your knowledge to use to build fantastic Big Data solutions for business, then this book is for you. Build six real-life, end-to-end solutions using the tools in the Hadoop ecosystem, and take your knowledge of Hadoop to the next level. Start off by understanding various business problems which can be solved using Hadoop. You will also get acquainted with the common architectural patterns which are used to build Hadoop-based solutions. Build a 360-degree view of the customer by working with different types of data, and build an efficient fraud detection system for a financial institution. You will also develop a system in Hadoop to improve the effectiveness of marketing campaigns. Build a churn detection system for a telecom company, develop an Internet of Things (IoT) system to monitor the environment in a factory, and build a data lake – all making use of the concepts and techniques mentioned in this book. The book covers other technologies and frameworks like Apache Spark, Hive, Sqoop, and more, and how they can be used in conjunction with Hadoop. You will be able to try out the solutions explained in the book and use the knowledge gained to extend them further in your own problem space. Style and approach This is an example-driven book where each chapter covers a single business problem and describes its solution by explaining the structure of a dataset and tools required to process it. Every project is demonstrated with a step-by-step approach, and explained in a very easy-to-understand manner.

Sustainable Computing

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Author : Shashank Awasthi
language : en
Publisher: Springer Nature
Release Date : 2023-01-01

Sustainable Computing written by Shashank Awasthi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Technology & Engineering categories.

This book presents recent advancements in Industry 4.0 and addresses how these can be useful in achieving sustainable solutions in Society 5.0. The book also serves as a reference for developing sustainable engineering solutions to various socio-economic and techno-commercial issues. The book is meticulously structured into two sections: Section I sheds light on fundamentals, nitty-gritties, and principles of technological innovations and advancement in artificial intelligence, cloud computing, industrial Internet of Things (IIOT), and Society 5.0, whereas Section II covers viable engineering solutions developments for revamping Industry 4.0 to Society 5.0. Overall, the authors aim to show how technological advancements can be used to address social issues and improve society.

Hadoop Spark

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Author : 余辉著
language : zh-CN
Publisher: 清华大学出版社（崧博）
Release Date : 2017-09-01

Hadoop Spark written by 余辉著 and has been published by 清华大学出版社（崧博） this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-01 with Computers categories.

本书用于Hadoop+Spark快速上手，全面解析Hadoop和Spark生态系统，通过原理解说和实例操作每一个组件，让读者能够轻松跨入大数据分析与开发的大门。 全书共12章，大致分为3个部分，第1部分（第1～7章）讲解Hadoop的原生态组件，包括Hadoop、ZooKeeper、HBase、Hive环境搭建与安装，以及介绍MapReduce、HDFS、ZooKeeper、HBase、Hive原理和Apache版本环境下实战操作。第2部分（第8～11章）讲解Spark的原生态组件，包括Spark Core、Spark SQL、Spark Streaming、DataFrame，以及介绍Scala、Spark API、Spark SQL、Spark Streaming、DataFrame原理和CDH版本环境下实战操作，其中Flume和Kafka属于Apache顶级开源项目也放在本篇讲解。第3部分（第12章）讲解两个大数据项目，包络网页日志离线项目和实时项目，在CDH版本环境下通过这两个项目将Hadoop和Spark原生态组件进行整合，一步步带领读者学习和实战操作。 本书适合想要快速掌握大数据技术的初学者，也适合作为高等院校和培训机构相关专业师生的教学参考书和实验用书。

Apache Spark 2 X Cookbook

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Author : Rishi Yadav
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-05-31

Apache Spark 2 X Cookbook written by Rishi Yadav 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 2017-05-31 with Computers categories.

Over 70 recipes to help you use Apache Spark as your single big data computing platform and master its libraries About This Book This book contains recipes on how to use Apache Spark as a unified compute engine Cover how to connect various source systems to Apache Spark Covers various parts of machine learning including supervised/unsupervised learning & recommendation engines Who This Book Is For This book is for data engineers, data scientists, and those who want to implement Spark for real-time data processing. Anyone who is using Spark (or is planning to) will benefit from this book. The book assumes you have a basic knowledge of Scala as a programming language. What You Will Learn Install and configure Apache Spark with various cluster managers & on AWS Set up a development environment for Apache Spark including Databricks Cloud notebook Find out how to operate on data in Spark with schemas Get to grips with real-time streaming analytics using Spark Streaming & Structured Streaming Master supervised learning and unsupervised learning using MLlib Build a recommendation engine using MLlib Graph processing using GraphX and GraphFrames libraries Develop a set of common applications or project types, and solutions that solve complex big data problems In Detail While Apache Spark 1.x gained a lot of traction and adoption in the early years, Spark 2.x delivers notable improvements in the areas of API, schema awareness, Performance, Structured Streaming, and simplifying building blocks to build better, faster, smarter, and more accessible big data applications. This book uncovers all these features in the form of structured recipes to analyze and mature large and complex sets of data. Starting with installing and configuring Apache Spark with various cluster managers, you will learn to set up development environments. Further on, you will be introduced to working with RDDs, DataFrames and Datasets to operate on schema aware data, and real-time streaming with various sources such as Twitter Stream and Apache Kafka. You will also work through recipes on machine learning, including supervised learning, unsupervised learning & recommendation engines in Spark. Last but not least, the final few chapters delve deeper into the concepts of graph processing using GraphX, securing your implementations, cluster optimization, and troubleshooting. Style and approach This book is packed with intuitive recipes supported with line-by-line explanations to help you understand Spark 2.x's real-time processing capabilities and deploy scalable big data solutions. This is a valuable resource for data scientists and those working on large-scale data projects.

Forthcoming Books

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Author : Rose Arny
language : en
Publisher:
Release Date : 2003

Forthcoming Books written by Rose Arny and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with American literature categories.

Spark In Action

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Author : Marko Bonaci
language : en
Publisher: Simon and Schuster
Release Date : 2016-11-03

Spark In Action written by Marko Bonaci and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-03 with Computers categories.

Summary Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. Fully updated for Spark 2.0. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Big data systems distribute datasets across clusters of machines, making it a challenge to efficiently query, stream, and interpret them. Spark can help. It is a processing system designed specifically for distributed data. It provides easy-to-use interfaces, along with the performance you need for production-quality analytics and machine learning. Spark 2 also adds improved programming APIs, better performance, and countless other upgrades. About the Book Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. You'll get comfortable with the Spark CLI as you work through a few introductory examples. Then, you'll start programming Spark using its core APIs. Along the way, you'll work with structured data using Spark SQL, process near-real-time streaming data, apply machine learning algorithms, and munge graph data using Spark GraphX. For a zero-effort startup, you can download the preconfigured virtual machine ready for you to try the book's code. What's Inside Updated for Spark 2.0 Real-life case studies Spark DevOps with Docker Examples in Scala, and online in Java and Python About the Reader Written for experienced programmers with some background in big data or machine learning. About the Authors Petar Zečević and Marko Bonaći are seasoned developers heavily involved in the Spark community. Table of Contents PART 1 - FIRST STEPS Introduction to Apache Spark Spark fundamentals Writing Spark applications The Spark API in depth PART 2 - MEET THE SPARK FAMILY Sparkling queries with Spark SQL Ingesting data with Spark Streaming Getting smart with MLlib ML: classification and clustering Connecting the dots with GraphX PART 3 - SPARK OPS Running Spark Running on a Spark standalone cluster Running on YARN and Mesos PART 4 - BRINGING IT TOGETHER Case study: real-time dashboard Deep learning on Spark with H2O