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Author: Dipa Dubhashi Publisher: Packt Publishing Ltd ISBN: 1785885375 Category : Computers Languages : en Pages : 352
Book Description
The ultimate guide to managing, building, and deploying large-scale clusters with Apache Mesos About This Book Master the architecture of Mesos and intelligently distribute your task across clusters of machines Explore a wide range of tools and platforms that Mesos works with This real-world comprehensive and robust tutorial will help you become an expert Who This Book Is For The book aims to serve DevOps engineers and system administrators who are familiar with the basics of managing a Linux system and its tools What You Will Learn Understand the Mesos architecture Manually spin up a Mesos cluster on a distributed infrastructure Deploy a multi-node Mesos cluster using your favorite DevOps See the nuts and bolts of scheduling, service discovery, failure handling, security, monitoring, and debugging in an enterprise-grade, production cluster deployment Use Mesos to deploy big data frameworks, containerized applications, or even custom build your own applications effortlessly In Detail Apache Mesos is open source cluster management software that provides efficient resource isolations and resource sharing distributed applications or frameworks. This book will take you on a journey to enhance your knowledge from amateur to master level, showing you how to improve the efficiency, management, and development of Mesos clusters. The architecture is quite complex and this book will explore the difficulties and complexities of working with Mesos. We begin by introducing Mesos, explaining its architecture and functionality. Next, we provide a comprehensive overview of Mesos features and advanced topics such as high availability, fault tolerance, scaling, and efficiency. Furthermore, you will learn to set up multi-node Mesos clusters on private and public clouds. We will also introduce several Mesos-based scheduling and management frameworks or applications to enable the easy deployment, discovery, load balancing, and failure handling of long-running services. Next, you will find out how a Mesos cluster can be easily set up and monitored using the standard deployment and configuration management tools. This advanced guide will show you how to deploy important big data processing frameworks such as Hadoop, Spark, and Storm on Mesos and big data storage frameworks such as Cassandra, Elasticsearch, and Kafka. Style and approach This advanced guide provides a detailed step-by-step account of deploying a Mesos cluster. It will demystify the concepts behind Mesos.
Author: Dipa Dubhashi Publisher: Packt Publishing Ltd ISBN: 1785885375 Category : Computers Languages : en Pages : 352
Book Description
The ultimate guide to managing, building, and deploying large-scale clusters with Apache Mesos About This Book Master the architecture of Mesos and intelligently distribute your task across clusters of machines Explore a wide range of tools and platforms that Mesos works with This real-world comprehensive and robust tutorial will help you become an expert Who This Book Is For The book aims to serve DevOps engineers and system administrators who are familiar with the basics of managing a Linux system and its tools What You Will Learn Understand the Mesos architecture Manually spin up a Mesos cluster on a distributed infrastructure Deploy a multi-node Mesos cluster using your favorite DevOps See the nuts and bolts of scheduling, service discovery, failure handling, security, monitoring, and debugging in an enterprise-grade, production cluster deployment Use Mesos to deploy big data frameworks, containerized applications, or even custom build your own applications effortlessly In Detail Apache Mesos is open source cluster management software that provides efficient resource isolations and resource sharing distributed applications or frameworks. This book will take you on a journey to enhance your knowledge from amateur to master level, showing you how to improve the efficiency, management, and development of Mesos clusters. The architecture is quite complex and this book will explore the difficulties and complexities of working with Mesos. We begin by introducing Mesos, explaining its architecture and functionality. Next, we provide a comprehensive overview of Mesos features and advanced topics such as high availability, fault tolerance, scaling, and efficiency. Furthermore, you will learn to set up multi-node Mesos clusters on private and public clouds. We will also introduce several Mesos-based scheduling and management frameworks or applications to enable the easy deployment, discovery, load balancing, and failure handling of long-running services. Next, you will find out how a Mesos cluster can be easily set up and monitored using the standard deployment and configuration management tools. This advanced guide will show you how to deploy important big data processing frameworks such as Hadoop, Spark, and Storm on Mesos and big data storage frameworks such as Cassandra, Elasticsearch, and Kafka. Style and approach This advanced guide provides a detailed step-by-step account of deploying a Mesos cluster. It will demystify the concepts behind Mesos.
Author: Javier Luraschi Publisher: O'Reilly Media ISBN: 1492046345 Category : Computers Languages : en Pages : 296
Book Description
If you’re like most R users, you have deep knowledge and love for statistics. But as your organization continues to collect huge amounts of data, adding tools such as Apache Spark makes a lot of sense. With this practical book, data scientists and professionals working with large-scale data applications will learn how to use Spark from R to tackle big data and big compute problems. Authors Javier Luraschi, Kevin Kuo, and Edgar Ruiz show you how to use R with Spark to solve different data analysis problems. This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users. Analyze, explore, transform, and visualize data in Apache Spark with R Create statistical models to extract information and predict outcomes; automate the process in production-ready workflows Perform analysis and modeling across many machines using distributed computing techniques Use large-scale data from multiple sources and different formats with ease from within Spark Learn about alternative modeling frameworks for graph processing, geospatial analysis, and genomics at scale Dive into advanced topics including custom transformations, real-time data processing, and creating custom Spark extensions
Author: Aditya Pratap Bhuyan Publisher: Aditya Pratap Bhuyan ISBN: Category : Computers Languages : en Pages : 210
Book Description
"Mastering Cloud Native: A Comprehensive Guide to Containers, DevOps, CI/CD, and Microservices" is your essential companion for navigating the transformative world of Cloud Native computing. Designed for both beginners and experienced professionals, this comprehensive guide provides a deep dive into the core principles and practices that define modern software development and deployment. In an era where agility, scalability, and resilience are paramount, Cloud Native computing stands at the forefront of technological innovation. This book explores the revolutionary concepts that drive Cloud Native, offering practical insights and detailed explanations to help you master this dynamic field. The journey begins with an "Introduction to Cloud Native," where you'll trace the evolution of cloud computing and understand the myriad benefits of adopting a Cloud Native architecture. This foundational knowledge sets the stage for deeper explorations into the key components of Cloud Native environments. Containers, the building blocks of Cloud Native applications, are covered extensively in "Understanding Containers." You'll learn about Docker and Kubernetes, the leading technologies in containerization, and discover best practices for managing and securing your containerized applications. The "DevOps in the Cloud Native World" chapter delves into the cultural and technical aspects of DevOps, emphasizing collaboration, automation, and continuous improvement. You'll gain insights into essential DevOps practices and tools, illustrated through real-world case studies of successful implementations. Continuous Integration and Continuous Deployment (CI/CD) are crucial for rapid and reliable software delivery. In the "CI/CD" chapter, you'll explore the principles and setup of CI/CD pipelines, popular tools, and solutions to common challenges. This knowledge will empower you to streamline your development processes and enhance your deployment efficiency. Microservices architecture, a key aspect of Cloud Native, is thoroughly examined in "Microservices Architecture." This chapter highlights the design principles and advantages of microservices over traditional monolithic systems, providing best practices for implementing and managing microservices in your projects. The book also introduces you to the diverse "Cloud Native Tools and Platforms," including insights into the Cloud Native Computing Foundation (CNCF) and guidance on selecting the right tools for your needs. This chapter ensures you have the necessary resources to build and manage robust Cloud Native applications. Security is paramount in any technology stack, and "Security in Cloud Native Environments" addresses the critical aspects of securing your Cloud Native infrastructure. From securing containers and microservices to ensuring compliance with industry standards, this chapter equips you with the knowledge to protect your applications and data. "Monitoring and Observability" explores the importance of maintaining the health and performance of your Cloud Native applications. You'll learn about essential tools and techniques for effective monitoring and observability, enabling proactive identification and resolution of issues. The book concludes with "Case Studies and Real-World Applications," presenting insights and lessons learned from industry implementations of Cloud Native technologies. These real-world examples provide valuable perspectives on the challenges and successes of adopting Cloud Native practices. "Mastering Cloud Native" is more than a technical guide; it's a comprehensive resource designed to inspire and educate. Whether you're a developer, operations professional, or technology leader, this book will equip you with the tools and knowledge to succeed in the Cloud Native era. Embrace the future of software development and unlock the full potential of Cloud Native computing with this indispensable guide.
Author: Romeo Kienzler Publisher: Packt Publishing Ltd ISBN: 178528522X Category : Computers Languages : en Pages : 345
Book Description
Advanced analytics on your Big Data with latest Apache Spark 2.x About This Book An advanced guide with a combination of instructions and practical examples to extend the most up-to date Spark functionalities. Extend your data processing capabilities to process huge chunk of data in minimum time using advanced concepts in Spark. Master the art of real-time processing with the help of Apache Spark 2.x Who This Book Is For If you are a developer with some experience with Spark and want to strengthen your knowledge of how to get around in the world of Spark, then this book is ideal for you. Basic knowledge of Linux, Hadoop and Spark is assumed. Reasonable knowledge of Scala is expected. What You Will Learn Examine Advanced Machine Learning and DeepLearning with MLlib, SparkML, SystemML, H2O and DeepLearning4J Study highly optimised unified batch and real-time data processing using SparkSQL and Structured Streaming Evaluate large-scale Graph Processing and Analysis using GraphX and GraphFrames Apply Apache Spark in Elastic deployments using Jupyter and Zeppelin Notebooks, Docker, Kubernetes and the IBM Cloud Understand internal details of cost based optimizers used in Catalyst, SystemML and GraphFrames Learn how specific parameter settings affect overall performance of an Apache Spark cluster Leverage Scala, R and python for your data science projects In Detail Apache Spark is an in-memory cluster-based parallel processing system that provides a wide range of functionalities such as graph processing, machine learning, stream processing, and SQL. This book aims to take your knowledge of Spark to the next level by teaching you how to expand Spark's functionality and implement your data flows and machine/deep learning programs on top of the platform. The book commences with an overview of the Spark ecosystem. It will introduce you to Project Tungsten and Catalyst, two of the major advancements of Apache Spark 2.x. You will understand how memory management and binary processing, cache-aware computation, and code generation are used to speed things up dramatically. The book extends to show how to incorporate H20, SystemML, and Deeplearning4j for machine learning, and Jupyter Notebooks and Kubernetes/Docker for cloud-based Spark. During the course of the book, you will learn about the latest enhancements to Apache Spark 2.x, such as interactive querying of live data and unifying DataFrames and Datasets. You will also learn about the updates on the APIs and how DataFrames and Datasets affect SQL, machine learning, graph processing, and streaming. You will learn to use Spark as a big data operating system, understand how to implement advanced analytics on the new APIs, and explore how easy it is to use Spark in day-to-day tasks. Style and approach This book is an extensive guide to Apache Spark modules and tools and shows how Spark's functionality can be extended for real-time processing and storage with worked examples.
Author: Cybellium Ltd Publisher: Cybellium Ltd ISBN: Category : Computers Languages : en Pages : 180
Book Description
Harness the Power of Stream Processing and Batch Data Analytics Are you ready to dive into the world of stream processing and batch data analytics with Apache Flink? "Mastering Apache Flink" is your comprehensive guide to unlocking the full potential of this cutting-edge framework for real-time data processing. Whether you're a data engineer looking to optimize data flows or a data scientist aiming to derive insights from large datasets, this book equips you with the knowledge and tools to master the art of Flink-based data processing. Key Features: 1. In-Depth Exploration of Apache Flink: Immerse yourself in the core principles of Apache Flink, understanding its architecture, components, and capabilities. Build a solid foundation that empowers you to process data in both real-time and batch modes. 2. Installation and Configuration: Master the art of installing and configuring Apache Flink on various platforms. Learn about cluster setup, resource management, and configuration tuning for optimal performance. 3. Flink Data Streams: Dive into Flink's data stream processing capabilities. Explore event time processing, windowing, and stateful computations for real-time data analysis. 4. Flink Batch Processing: Uncover the power of Flink for batch data analytics. Learn how to process large datasets using Flink's batch processing mode for efficient analysis. 5. Flink SQL: Delve into Flink's SQL and Table API. Discover how to write SQL queries and perform transformations on structured and semi-structured data for intuitive data manipulation. 6. Flink's State Management: Master Flink's state management mechanisms. Learn how to manage application state for fault tolerance and how to work with savepoints and checkpoints. 7. Complex Event Processing with CEP: Explore Flink's complex event processing capabilities. Learn how to detect patterns, anomalies, and trends in data streams for real-time insights. 8. Machine Learning with FlinkML: Embark on a journey into machine learning with FlinkML. Learn how to implement predictive analytics and machine learning algorithms for data-driven models. 9. Flink Ecosystem and Integrations: Navigate Flink's ecosystem of libraries and integrations. From data ingestion with Apache Kafka to collaborative analytics with Zeppelin, explore tools that enhance Flink's functionalities. 10. Real-World Applications: Gain insights into real-world use cases of Apache Flink across industries. From IoT data processing to fraud detection, explore how organizations leverage Flink for real-time insights. Who This Book Is For: "Mastering Apache Flink" is an indispensable resource for data engineers, analysts, and IT professionals who want to excel in stream processing and batch data analytics using Flink. Whether you're new to Flink or seeking advanced techniques, this book will guide you through the intricacies and empower you to harness the full potential of this powerful framework.
Author: Alex Kozlov Publisher: Packt Publishing Ltd ISBN: 178588526X Category : Computers Languages : en Pages : 310
Book Description
Advance your skills in efficient data analysis and data processing using the powerful tools of Scala, Spark, and Hadoop About This Book This is a primer on functional-programming-style techniques to help you efficiently process and analyze all of your data Get acquainted with the best and newest tools available such as Scala, Spark, Parquet and MLlib for machine learning Learn the best practices to incorporate new Big Data machine learning in your data-driven enterprise to gain future scalability and maintainability Who This Book Is For Mastering Scala Machine Learning is intended for enthusiasts who want to plunge into the new pool of emerging techniques for machine learning. Some familiarity with standard statistical techniques is required. What You Will Learn Sharpen your functional programming skills in Scala using REPL Apply standard and advanced machine learning techniques using Scala Get acquainted with Big Data technologies and grasp why we need a functional approach to Big Data Discover new data structures, algorithms, approaches, and habits that will allow you to work effectively with large amounts of data Understand the principles of supervised and unsupervised learning in machine learning Work with unstructured data and serialize it using Kryo, Protobuf, Avro, and AvroParquet Construct reliable and robust data pipelines and manage data in a data-driven enterprise Implement scalable model monitoring and alerts with Scala In Detail Since the advent of object-oriented programming, new technologies related to Big Data are constantly popping up on the market. One such technology is Scala, which is considered to be a successor to Java in the area of Big Data by many, like Java was to C/C++ in the area of distributed programing. This book aims to take your knowledge to next level and help you impart that knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees. Most of the data that we produce today is unstructured and raw, and you will learn to tackle this type of data with advanced topics such as regression, classification, integration, and working with graph algorithms. Finally, you will discover at how to use Scala to perform complex concept analysis, to monitor model performance, and to build a model repository. By the end of this book, you will have gained expertise in performing Scala machine learning and will be able to build complex machine learning projects using Scala. Style and approach This hands-on guide dives straight into implementing Scala for machine learning without delving much into mathematical proofs or validations. There are ample code examples and tricks that will help you sail through using the standard techniques and libraries. This book provides practical examples from the field on how to correctly tackle data analysis problems, particularly for modern Big Data datasets.
Author: Christine Bresnahan Publisher: John Wiley & Sons ISBN: 1119794463 Category : Computers Languages : en Pages : 576
Book Description
Achieve Linux system administration mastery with time-tested and proven techniques In Mastering Linux System Administration, Linux experts and system administrators Christine Bresnahan and Richard Blum deliver a comprehensive roadmap to go from Linux beginner to expert Linux system administrator with a learning-by-doing approach. Organized by do-it-yourself tasks, the book includes instructor materials like a sample syllabus, additional review questions, and slide decks. Amongst the practical applications of the Linux operating system included within, you’ll find detailed and easy-to-follow instruction on: Installing Linux servers, understanding the boot and initialization processes, managing hardware, and working with networks Accessing the Linux command line, working with the virtual directory structure, and creating shell scripts to automate administrative tasks Managing Linux user accounts, system security, web and database servers, and virtualization environments Perfect for entry-level Linux system administrators, as well as system administrators familiar with Windows, Mac, NetWare, or other UNIX systems, Mastering Linux System Administration is a must-read guide to manage and secure Linux servers.
Author: Cybellium Ltd Publisher: Cybellium Ltd ISBN: Category : Computers Languages : en Pages : 248
Book Description
Unleash the Potential of Distributed Data Processing with Apache Spark Are you prepared to venture into the realm of distributed data processing and analytics with Apache Spark? "Mastering Apache Spark" is your comprehensive guide to unlocking the full potential of this powerful framework for big data processing. Whether you're a data engineer seeking to optimize data pipelines or a business analyst aiming to extract insights from massive datasets, this book equips you with the knowledge and tools to master the art of Spark-based data processing. Key Features: 1. Deep Dive into Apache Spark: Immerse yourself in the core principles of Apache Spark, comprehending its architecture, components, and versatile functionalities. Construct a robust foundation that empowers you to manage big data with precision. 2. Installation and Configuration: Master the art of installing and configuring Apache Spark across diverse platforms. Learn about cluster setup, resource allocation, and configuration tuning for optimal performance. 3. Spark Core and RDDs: Uncover the core of Spark—Resilient Distributed Datasets (RDDs). Explore the functional programming paradigm and leverage RDDs for efficient and fault-tolerant data processing. 4. Structured Data Processing with Spark SQL: Delve into Spark SQL for querying structured data with ease. Learn how to execute SQL queries, perform data manipulations, and tap into the power of DataFrames. 5. Streamlining Data Processing with Spark Streaming: Discover the power of real-time data processing with Spark Streaming. Learn how to handle continuous data streams and perform near-real-time analytics. 6. Machine Learning with MLlib: Master Spark's machine learning library, MLlib. Dive into algorithms for classification, regression, clustering, and recommendation, enabling you to develop sophisticated data-driven models. 7. Graph Processing with GraphX: Embark on a journey through graph processing with Spark's GraphX. Learn how to analyze and visualize graph data to glean insights from complex relationships. 8. Data Processing with Spark Structured Streaming: Explore the world of structured streaming in Spark. Learn how to process and analyze data streams with the declarative power of DataFrames. 9. Spark Ecosystem and Integrations: Navigate Spark's rich ecosystem of libraries and integrations. From data ingestion with Apache Kafka to interactive analytics with Apache Zeppelin, explore tools that enhance Spark's capabilities. 10. Real-World Applications: Gain insights into real-world use cases of Apache Spark across industries. From fraud detection to sentiment analysis, discover how organizations leverage Spark for data-driven innovation. Who This Book Is For: "Mastering Apache Spark" is a must-have resource for data engineers, analysts, and IT professionals poised to excel in the world of distributed data processing using Spark. Whether you're new to Spark or seeking advanced techniques, this book will guide you through the intricacies and empower you to harness the full potential of this transformative framework.
Author: Bill Chambers Publisher: "O'Reilly Media, Inc." ISBN: 1491912294 Category : Computers Languages : en Pages : 594
Book Description
Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. Youâ??ll explore the basic operations and common functions of Sparkâ??s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Sparkâ??s scalable machine-learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasetsâ??Sparkâ??s core APIsâ??through worked examples Dive into Sparkâ??s low-level APIs, RDDs, and execution of SQL and DataFrames Understand how Spark runs on a cluster Debug, monitor, and tune Spark clusters and applications Learn the power of Structured Streaming, Sparkâ??s stream-processing engine Learn how you can apply MLlib to a variety of problems, including classification or recommendation
Author: Dipa Dubhashi
Author: Dipa Dubhashi
Author: Javier Luraschi
Author: Aditya Pratap Bhuyan
Author: Cybellium Ltd
Author: Romeo Kienzler
Author: Cybellium Ltd
Author: Alex Kozlov
Author: Christine Bresnahan
Author: Cybellium Ltd
Author: Bill Chambers