Hadoop Application Architectures

Author : Mark Grover,Ted Malaska,Jonathan Seidman,Gwen Shapira
Publisher : "O'Reilly Media, Inc."
Page : 399 pages
File Size : 40,8 Mb
Release : 2015-06-30
Category : Computers
ISBN : 9781491900079

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Hadoop Application Architectures by Mark Grover,Ted Malaska,Jonathan Seidman,Gwen Shapira Pdf

Get expert guidance on architecting end-to-end data management solutions with Apache Hadoop. While many sources explain how to use various components in the Hadoop ecosystem, this practical book takes you through architectural considerations necessary to tie those components together into a complete tailored application, based on your particular use case. To reinforce those lessons, the book’s second section provides detailed examples of architectures used in some of the most commonly found Hadoop applications. Whether you’re designing a new Hadoop application, or planning to integrate Hadoop into your existing data infrastructure, Hadoop Application Architectures will skillfully guide you through the process. This book covers: Factors to consider when using Hadoop to store and model data Best practices for moving data in and out of the system Data processing frameworks, including MapReduce, Spark, and Hive Common Hadoop processing patterns, such as removing duplicate records and using windowing analytics Giraph, GraphX, and other tools for large graph processing on Hadoop Using workflow orchestration and scheduling tools such as Apache Oozie Near-real-time stream processing with Apache Storm, Apache Spark Streaming, and Apache Flume Architecture examples for clickstream analysis, fraud detection, and data warehousing

Author : Mark Grover,Ted Malaska,Jonathan Seidman,Gwen Shapira
Publisher : Unknown
Page : 128 pages
File Size : 54,7 Mb
Release : 2015
Category : COMPUTERS
ISBN : 1491910313

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Hadoop Application Architectures by Mark Grover,Ted Malaska,Jonathan Seidman,Gwen Shapira Pdf

Author : Mark Grover
Publisher : Unknown
Page : 0 pages
File Size : 42,8 Mb
Release : 2015
Category : Apache Hadoop
ISBN : OCLC:919106725

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Hadoop Application Architectures by Mark Grover Pdf

"Get expert guidance on architecting end-to-end data management solutions with Apache Hadoop. While many sources explain how to use various components in the Hadoop ecosystem, this practical book takes you through architectural considerations necessary to tie those components together into a complete tailored application, based on your particular use case. To reinforce those lessons, the book's second section provides detailed examples of architectures used in some of the most commonly found Hadoop applications. Whether you're designing a new Hadoop application, or planning to integrate Hadoop into your existing data infrastructure, Hadoop Application Architectures will skillfully guide you through the process."--

Author : Jan Kunigk,Ian Buss,Paul Wilkinson,Lars George
Publisher : "O'Reilly Media, Inc."
Page : 636 pages
File Size : 48,8 Mb
Release : 2018-12-05
Category : Computers
ISBN : 9781491969229

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Architecting Modern Data Platforms by Jan Kunigk,Ian Buss,Paul Wilkinson,Lars George Pdf

There’s a lot of information about big data technologies, but splicing these technologies into an end-to-end enterprise data platform is a daunting task not widely covered. With this practical book, you’ll learn how to build big data infrastructure both on-premises and in the cloud and successfully architect a modern data platform. Ideal for enterprise architects, IT managers, application architects, and data engineers, this book shows you how to overcome the many challenges that emerge during Hadoop projects. You’ll explore the vast landscape of tools available in the Hadoop and big data realm in a thorough technical primer before diving into: Infrastructure: Look at all component layers in a modern data platform, from the server to the data center, to establish a solid foundation for data in your enterprise Platform: Understand aspects of deployment, operation, security, high availability, and disaster recovery, along with everything you need to know to integrate your platform with the rest of your enterprise IT Taking Hadoop to the cloud: Learn the important architectural aspects of running a big data platform in the cloud while maintaining enterprise security and high availability

Author : Ted Malaska,Jonathan Seidman
Publisher : "O'Reilly Media, Inc."
Page : 190 pages
File Size : 55,8 Mb
Release : 2018-08-29
Category : Computers
ISBN : 9781492038696

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Foundations for Architecting Data Solutions by Ted Malaska,Jonathan Seidman Pdf

While many companies ponder implementation details such as distributed processing engines and algorithms for data analysis, this practical book takes a much wider view of big data development, starting with initial planning and moving diligently toward execution. Authors Ted Malaska and Jonathan Seidman guide you through the major components necessary to start, architect, and develop successful big data projects. Everyone from CIOs and COOs to lead architects and developers will explore a variety of big data architectures and applications, from massive data pipelines to web-scale applications. Each chapter addresses a piece of the software development life cycle and identifies patterns to maximize long-term success throughout the life of your project. Start the planning process by considering the key data project types Use guidelines to evaluate and select data management solutions Reduce risk related to technology, your team, and vague requirements Explore system interface design using APIs, REST, and pub/sub systems Choose the right distributed storage system for your big data system Plan and implement metadata collections for your data architecture Use data pipelines to ensure data integrity from source to final storage Evaluate the attributes of various engines for processing the data you collect

Author : Nitin Sawant,Himanshu Shah
Publisher : Apress
Page : 157 pages
File Size : 52,5 Mb
Release : 2014-01-24
Category : Computers
ISBN : 9781430262930

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Big Data Application Architecture Q&A by Nitin Sawant,Himanshu Shah Pdf

Big Data Application Architecture Pattern Recipes provides an insight into heterogeneous infrastructures, databases, and visualization and analytics tools used for realizing the architectures of big data solutions. Its problem-solution approach helps in selecting the right architecture to solve the problem at hand. In the process of reading through these problems, you will learn harness the power of new big data opportunities which various enterprises use to attain real-time profits. Big Data Application Architecture Pattern Recipes answers one of the most critical questions of this time 'how do you select the best end-to-end architecture to solve your big data problem?'. The book deals with various mission critical problems encountered by solution architects, consultants, and software architects while dealing with the myriad options available for implementing a typical solution, trying to extract insight from huge volumes of data in real–time and across multiple relational and non-relational data types for clients from industries like retail, telecommunication, banking, and insurance. The patterns in this book provide the strong architectural foundation required to launch your next big data application. The architectures for realizing these opportunities are based on relatively less expensive and heterogeneous infrastructures compared to the traditional monolithic and hugely expensive options that exist currently. This book describes and evaluates the benefits of heterogeneity which brings with it multiple options of solving the same problem, evaluation of trade-offs and validation of 'fitness-for-purpose' of the solution.

Author : Bahaaldine Azarmi
Publisher : Apress
Page : 147 pages
File Size : 51,6 Mb
Release : 2015-12-31
Category : Computers
ISBN : 9781484213261

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Scalable Big Data Architecture by Bahaaldine Azarmi Pdf

This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance. Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications , which involve web applications, RESTful API, and high throughput of large amount of data stored in highly scalable No-SQL data stores such as Couchbase and Elasticsearch. This book demonstrates how data processing can be done at scale from the usage of NoSQL datastores to the combination of Big Data distribution. When the data processing is too complex and involves different processing topology like long running jobs, stream processing, multiple data sources correlation, and machine learning, it’s often necessary to delegate the load to Hadoop or Spark and use the No-SQL to serve processed data in real time. This book shows you how to choose a relevant combination of big data technologies available within the Hadoop ecosystem. It focuses on processing long jobs, architecture, stream data patterns, log analysis, and real time analytics. Every pattern is illustrated with practical examples, which use the different open sourceprojects such as Logstash, Spark, Kafka, and so on. Traditional data infrastructures are built for digesting and rendering data synthesis and analytics from large amount of data. This book helps you to understand why you should consider using machine learning algorithms early on in the project, before being overwhelmed by constraints imposed by dealing with the high throughput of Big data. Scalable Big Data Architecture is for developers, data architects, and data scientists looking for a better understanding of how to choose the most relevant pattern for a Big Data project and which tools to integrate into that pattern.

Author : Benjamin Bengfort,Jenny Kim
Publisher : "O'Reilly Media, Inc."
Page : 288 pages
File Size : 49,5 Mb
Release : 2016-06-01
Category : Computers
ISBN : 9781491913758

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Data Analytics with Hadoop by Benjamin Bengfort,Jenny Kim Pdf

Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce. Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data. Understand core concepts behind Hadoop and cluster computing Use design patterns and parallel analytical algorithms to create distributed data analysis jobs Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase Use Sqoop and Apache Flume to ingest data from relational databases Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib

Author : Boris Lublinsky,Kevin T. Smith,Alexey Yakubovich
Publisher : John Wiley & Sons
Page : 504 pages
File Size : 54,6 Mb
Release : 2013-09-12
Category : Computers
ISBN : 9781118824184

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Professional Hadoop Solutions by Boris Lublinsky,Kevin T. Smith,Alexey Yakubovich Pdf

The go-to guidebook for deploying Big Data solutions withHadoop Today's enterprise architects need to understand how the Hadoopframeworks and APIs fit together, and how they can be integrated todeliver real-world solutions. This book is a practical, detailedguide to building and implementing those solutions, with code-levelinstruction in the popular Wrox tradition. It covers storing datawith HDFS and Hbase, processing data with MapReduce, and automatingdata processing with Oozie. Hadoop security, running Hadoop withAmazon Web Services, best practices, and automating Hadoopprocesses in real time are also covered in depth. With in-depth code examples in Java and XML and the latest onrecent additions to the Hadoop ecosystem, this complete resourcealso covers the use of APIs, exposing their inner workings andallowing architects and developers to better leverage and customizethem. The ultimate guide for developers, designers, and architectswho need to build and deploy Hadoop applications Covers storing and processing data with various technologies,automating data processing, Hadoop security, and deliveringreal-time solutions Includes detailed, real-world examples and code-levelguidelines Explains when, why, and how to use these tools effectively Written by a team of Hadoop experts in theprogrammer-to-programmer Wrox style Professional Hadoop Solutions is the reference enterprisearchitects and developers need to maximize the power of Hadoop.

Author : Andrés Solano,Hugo Ordoñez
Publisher : Springer
Page : 807 pages
File Size : 46,9 Mb
Release : 2017-08-14
Category : Computers
ISBN : 9783319665627

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Advances in Computing by Andrés Solano,Hugo Ordoñez Pdf

This book constitutes the refereed proceedings of the 12th Colombian Conference on Computing, CCC 2017, held in Cali, Colombia, in September 2017. The 56 revised full papers presented were carefully reviewed and selected from 186 submissions. The papers are organized in topical sections on information and knowledge management, software engineering and IT architectures, educational informatics, intelligent systems and robotics, human-computer interaction, distributed systems and large-scale architectures, image processing, computer vision and multimedia, security of the information, formal methods, computational logic and theory of computation.

Author : V Naresh Kumar,Prashant Shindgikar
Publisher : Packt Publishing Ltd
Page : 390 pages
File Size : 46,8 Mb
Release : 2018-03-30
Category : Computers
ISBN : 9781787128811

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Modern Big Data Processing with Hadoop by V Naresh Kumar,Prashant Shindgikar Pdf

A comprehensive guide to design, build and execute effective Big Data strategies using Hadoop Key Features -Get an in-depth view of the Apache Hadoop ecosystem and an overview of the architectural patterns pertaining to the popular Big Data platform -Conquer different data processing and analytics challenges using a multitude of tools such as Apache Spark, Elasticsearch, Tableau and more -A comprehensive, step-by-step guide that will teach you everything you need to know, to be an expert Hadoop Architect Book Description The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools. This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowledge you need to build expert Big Data systems. What you will learn Build an efficient enterprise Big Data strategy centered around Apache Hadoop Gain a thorough understanding of using Hadoop with various Big Data frameworks such as Apache Spark, Elasticsearch and more Set up and deploy your Big Data environment on premises or on the cloud with Apache Ambari Design effective streaming data pipelines and build your own enterprise search solutions Utilize the historical data to build your analytics solutions and visualize them using popular tools such as Apache Superset Plan, set up and administer your Hadoop cluster efficiently Who this book is for This book is for Big Data professionals who want to fast-track their career in the Hadoop industry and become an expert Big Data architect. Project managers and mainframe professionals looking forward to build a career in Big Data Hadoop will also find this book to be useful. Some understanding of Hadoop is required to get the best out of this book.

Author : Mark Grover,Gwen Shapira,Ted Malaska,Jonathan Seidman
Publisher : Unknown
Page : 128 pages
File Size : 55,6 Mb
Release : 2015
Category : Internet videos
ISBN : 1491923318

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Architectural Considerations for Hadoop Applications by Mark Grover,Gwen Shapira,Ted Malaska,Jonathan Seidman Pdf

"Implementing solutions with Apache Hadoop requires understanding notjust Hadoop, but a broad range of related projects in the Hadoopecosystem such as Hive, Pig, Oozie, Sqoop, and Flume. The good news isthat there's an abundance of materials - books, web sites,conferences, etc. - for gaining a deep understanding of Hadoop andthese related projects. The bad news is there's still a scarcity of information on how to integrate these components to implement completesolutions. In this video we'll walk through an end-to-end case studyof a clickstream analytics engine to provide a concrete example of howto architect and implement a complete solution with Hadoop."--Resource description page.

Author : Bhushan Lakhe
Publisher : Apress
Page : 321 pages
File Size : 42,6 Mb
Release : 2016-08-10
Category : Computers
ISBN : 9781484212875

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Practical Hadoop Migration by Bhushan Lakhe Pdf

Re-architect relational applications to NoSQL, integrate relational database management systems with the Hadoop ecosystem, and transform and migrate relational data to and from Hadoop components. This book covers the best-practice design approaches to re-architecting your relational applications and transforming your relational data to optimize concurrency, security, denormalization, and performance. Winner of IBM’s 2012 Gerstner Award for his implementation of big data and data warehouse initiatives and author of Practical Hadoop Security, author Bhushan Lakhe walks you through the entire transition process. First, he lays out the criteria for deciding what blend of re-architecting, migration, and integration between RDBMS and HDFS best meets your transition objectives. Then he demonstrates how to design your transition model. Lakhe proceeds to cover the selection criteria for ETL tools, the implementation steps for migration with SQOOP- and Flume-based data transfers, and transition optimization techniques for tuning partitions, scheduling aggregations, and redesigning ETL. Finally, he assesses the pros and cons of data lakes and Lambda architecture as integrative solutions and illustrates their implementation with real-world case studies. Hadoop/NoSQL solutions do not offer by default certain relational technology features such as role-based access control, locking for concurrent updates, and various tools for measuring and enhancing performance. Practical Hadoop Migration shows how to use open-source tools to emulate such relational functionalities in Hadoop ecosystem components. What You'll Learn Decide whether you should migrate your relational applications to big data technologies or integrate them Transition your relational applications to Hadoop/NoSQL platforms in terms of logical design and physical implementation Discover RDBMS-to-HDFS integration, data transformation, and optimization techniques Consider when to use Lambda architecture and data lake solutions Select and implement Hadoop-based components and applications to speed transition, optimize integrated performance, and emulate relational functionalities Who This Book Is For Database developers, database administrators, enterprise architects, Hadoop/NoSQL developers, and IT leaders. Its secondary readership is project and program managers and advanced students of database and management information systems.

Author : Nitin Kumar
Publisher : Mercury Learning and Information
Page : 237 pages
File Size : 50,8 Mb
Release : 2021-03-24
Category : Computers
ISBN : 9781683926436

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Big Data Using Hadoop and Hive by Nitin Kumar Pdf

This book is the basic guide for developers, architects, engineers, and anyone who wants to start leveraging the open-source software Hadoop and Hive to build distributed, scalable concurrent big data applications. Hive will be used for reading, writing, and managing the large, data set files. The book is a concise guide on getting started with an overall understanding on Apache Hadoop and Hive and how they work together to speed up development with minimal effort. It will refer to simple concepts and examples, as they are likely to be the best teaching aids. It will explain the logic, code, and configurations needed to build a successful, distributed, concurrent application, as well as the reason behind those decisions. FEATURES: Shows how to leverage the open-source software Hadoop and Hive to build distributed, scalable, concurrent big data applications Includes material on Hive architecture with various storage types and the Hive query language Features a chapter on big data and how Hadoop can be used to solve the changes around it Explains the basic Hadoop setup, configuration, and optimization

Author : George Trujillo,Charles Kim,Steve Jones,Rommel Garcia,Justin Murray
Publisher : VMWare Press
Page : 799 pages
File Size : 47,6 Mb
Release : 2015-07-14
Category : Computers
ISBN : 9780133811131

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Virtualizing Hadoop by George Trujillo,Charles Kim,Steve Jones,Rommel Garcia,Justin Murray Pdf

Plan and Implement Hadoop Virtualization for Maximum Performance, Scalability, and Business Agility Enterprises running Hadoop must absorb rapid changes in big data ecosystems, frameworks, products, and workloads. Virtualized approaches can offer important advantages in speed, flexibility, and elasticity. Now, a world-class team of enterprise virtualization and big data experts guide you through the choices, considerations, and tradeoffs surrounding Hadoop virtualization. The authors help you decide whether to virtualize Hadoop, deploy Hadoop in the cloud, or integrate conventional and virtualized approaches in a blended solution. First, Virtualizing Hadoop reviews big data and Hadoop from the standpoint of the virtualization specialist. The authors demystify MapReduce, YARN, and HDFS and guide you through each stage of Hadoop data management. Next, they turn the tables, introducing big data experts to modern virtualization concepts and best practices. Finally, they bring Hadoop and virtualization together, guiding you through the decisions you’ll face in planning, deploying, provisioning, and managing virtualized Hadoop. From security to multitenancy to day-to-day management, you’ll find reliable answers for choosing your best Hadoop strategy and executing it. Coverage includes the following: • Reviewing the frameworks, products, distributions, use cases, and roles associated with Hadoop • Understanding YARN resource management, HDFS storage, and I/O • Designing data ingestion, movement, and organization for modern enterprise data platforms • Defining SQL engine strategies to meet strict SLAs • Considering security, data isolation, and scheduling for multitenant environments • Deploying Hadoop as a service in the cloud • Reviewing the essential concepts, capabilities, and terminology of virtualization • Applying current best practices, guidelines, and key metrics for Hadoop virtualization • Managing multiple Hadoop frameworks and products as one unified system • Virtualizing master and worker nodes to maximize availability and performance • Installing and configuring Linux for a Hadoop environment