Author: Ben Spivey
Publisher: "O'Reilly Media, Inc."
ISBN: 1491901349
Category : Computers
Languages : en
Pages : 336

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Book Description
As more corporations turn to Hadoop to store and process their most valuable data, the risk of a potential breach of those systems increases exponentially. This practical book not only shows Hadoop administrators and security architects how to protect Hadoop data from unauthorized access, it also shows how to limit the ability of an attacker to corrupt or modify data in the event of a security breach. Authors Ben Spivey and Joey Echeverria provide in-depth information about the security features available in Hadoop, and organize them according to common computer security concepts. You’ll also get real-world examples that demonstrate how you can apply these concepts to your use cases. Understand the challenges of securing distributed systems, particularly Hadoop Use best practices for preparing Hadoop cluster hardware as securely as possible Get an overview of the Kerberos network authentication protocol Delve into authorization and accounting principles as they apply to Hadoop Learn how to use mechanisms to protect data in a Hadoop cluster, both in transit and at rest Integrate Hadoop data ingest into enterprise-wide security architecture Ensure that security architecture reaches all the way to end-user access

Author: Bhushan Lakhe
Publisher: Apress
ISBN: 1430265450
Category : Computers
Languages : en
Pages : 199

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Book Description
Practical Hadoop Security is an excellent resource for administrators planning a production Hadoop deployment who want to secure their Hadoop clusters. A detailed guide to the security options and configuration within Hadoop itself, author Bhushan Lakhe takes you through a comprehensive study of how to implement defined security within a Hadoop cluster in a hands-on way. You will start with a detailed overview of all the security options available for Hadoop, including popular extensions like Kerberos and OpenSSH, and then delve into a hands-on implementation of user security (with illustrated code samples) with both in-the-box features and with security extensions implemented by leading vendors. No security system is complete without a monitoring and tracing facility, so Practical Hadoop Security next steps you through audit logging and monitoring technologies for Hadoop, as well as ready to use implementation and configuration examples--again with illustrated code samples. The book concludes with the most important aspect of Hadoop security – encryption. Both types of encryptions, for data in transit and data at rest, are discussed at length with leading open source projects that integrate directly with Hadoop at no licensing cost. Practical Hadoop Security: Explains importance of security, auditing and encryption within a Hadoop installation Describes how the leading players have incorporated these features within their Hadoop distributions and provided extensions Demonstrates how to set up and use these features to your benefit and make your Hadoop installation secure without impacting performance or ease of use

Author: Sudheesh Narayanan
Publisher: Packt Publishing Ltd
ISBN: 1783285265
Category : Computers
Languages : en
Pages : 168

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Book Description
This book is a step-by-step tutorial filled with practical examples which will focus mainly on the key security tools and implementation techniques of Hadoop security.This book is great for Hadoop practitioners (solution architects, Hadoop administrators, developers, and Hadoop project managers) who are looking to get a good grounding in what Kerberos is all about and who wish to learn how to implement end-to-end Hadoop security within an enterprise setup. It’s assumed that you will have some basic understanding of Hadoop as well as be familiar with some basic security concepts.

Author: Boris Lublinsky
Publisher: John Wiley & Sons
ISBN: 1118824180
Category : Computers
Languages : en
Pages : 505

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Book Description
The go-to guidebook for deploying Big Data solutions with Hadoop Today's enterprise architects need to understand how the Hadoop frameworks and APIs fit together, and how they can be integrated to deliver real-world solutions. This book is a practical, detailed guide to building and implementing those solutions, with code-level instruction in the popular Wrox tradition. It covers storing data with HDFS and Hbase, processing data with MapReduce, and automating data processing with Oozie. Hadoop security, running Hadoop with Amazon Web Services, best practices, and automating Hadoop processes in real time are also covered in depth. With in-depth code examples in Java and XML and the latest on recent additions to the Hadoop ecosystem, this complete resource also covers the use of APIs, exposing their inner workings and allowing architects and developers to better leverage and customize them. The ultimate guide for developers, designers, and architects who need to build and deploy Hadoop applications Covers storing and processing data with various technologies, automating data processing, Hadoop security, and delivering real-time solutions Includes detailed, real-world examples and code-level guidelines Explains when, why, and how to use these tools effectively Written by a team of Hadoop experts in the programmer-to-programmer Wrox style Professional Hadoop Solutions is the reference enterprise architects and developers need to maximize the power of Hadoop.

Author: Eric Sammer
Publisher: "O'Reilly Media, Inc."
ISBN: 144932729X
Category : Computers
Languages : en
Pages : 298

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Book Description
If you’ve been asked to maintain large and complex Hadoop clusters, this book is a must. Demand for operations-specific material has skyrocketed now that Hadoop is becoming the de facto standard for truly large-scale data processing in the data center. Eric Sammer, Principal Solution Architect at Cloudera, shows you the particulars of running Hadoop in production, from planning, installing, and configuring the system to providing ongoing maintenance. Rather than run through all possible scenarios, this pragmatic operations guide calls out what works, as demonstrated in critical deployments. Get a high-level overview of HDFS and MapReduce: why they exist and how they work Plan a Hadoop deployment, from hardware and OS selection to network requirements Learn setup and configuration details with a list of critical properties Manage resources by sharing a cluster across multiple groups Get a runbook of the most common cluster maintenance tasks Monitor Hadoop clusters—and learn troubleshooting with the help of real-world war stories Use basic tools and techniques to handle backup and catastrophic failure

Author: Bill Havanki
Publisher: "O'Reilly Media, Inc."
ISBN: 1491959584
Category : Computers
Languages : en
Pages : 320

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Book Description
Until recently, Hadoop deployments existed on hardware owned and run by organizations. Now, of course, you can acquire the computing resources and network connectivity to run Hadoop clusters in the cloud. But there’s a lot more to deploying Hadoop to the public cloud than simply renting machines. This hands-on guide shows developers and systems administrators familiar with Hadoop how to install, use, and manage cloud-born clusters efficiently. You’ll learn how to architect clusters that work with cloud-provider features—not just to avoid pitfalls, but also to take full advantage of these services. You’ll also compare the Amazon, Google, and Microsoft clouds, and learn how to set up clusters in each of them. Learn how Hadoop clusters run in the cloud, the problems they can help you solve, and their potential drawbacks Examine the common concepts of cloud providers, including compute capabilities, networking and security, and storage Build a functional Hadoop cluster on cloud infrastructure, and learn what the major providers require Explore use cases for high availability, relational data with Hive, and complex analytics with Spark Get patterns and practices for running cloud clusters, from designing for price and security to dealing with maintenance

Author: Vinicius Aquino do Vale
Publisher: BPB Publications
ISBN: 9391392288
Category : Computers
Languages : en
Pages : 196

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Book Description
Understand data in a simple way using a data lake. KEY FEATURES ● In-depth practical demonstration of Hadoop/Yarn concepts with numerous examples. ● Includes graphical illustrations and visual explanations for Hadoop commands and parameters. ● Includes details of dimensional modeling and Data Vault modeling. ● Includes details of how to create and define a structure to a data lake. DESCRIPTION The book 'Data Processing and Modeling with Hadoop' explains how a distributed system works and its benefits in the big data era in a straightforward and clear manner. After reading the book, you will be able to plan and organize projects involving a massive amount of data. The book describes the standards and technologies that aid in data management and compares them to other technology business standards. The reader receives practical guidance on how to segregate and separate data into zones, as well as how to develop a model that can aid in data evolution. It discusses security and the measures that are utilized to reduce the impact of security. Self-service analytics, Data Lake, Data Vault 2.0, and Data Mesh are discussed in the book. After reading this book, the reader will have a thorough understanding of how to structure a data lake, as well as the ability to plan, organize, and carry out the implementation of a data-driven business with full governance and security. WHAT YOU WILL LEARN ● Learn the basics of components to the Hadoop Ecosystem. ● Understand the structure, files, and zones of a Data Lake. ● Learn to implement the security part of the Hadoop Ecosystem. ● Learn to work with the Data Vault 2.0 modeling. ● Learn to develop a strategy to define good governance. ● Learn new tools to work with Data and Big Data WHO THIS BOOK IS FOR This book caters to big data developers, technical specialists, consultants, and students who want to build good proficiency in big data. Knowing basic SQL concepts, modeling, and development would be good, although not mandatory. TABLE OF CONTENTS 1. Understanding the Current Moment 2. Defining the Zones 3. The Importance of Modeling 4. Massive Parallel Processing 5. Doing ETL/ELT 6. A Little Governance 7. Talking About Security 8. What Are the Next Steps?

Author: Sandeep Karanth
Publisher: Packt Publishing Ltd
ISBN: 1783983655
Category : Computers
Languages : en
Pages : 549

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Book Description
Do you want to broaden your Hadoop skill set and take your knowledge to the next level? Do you wish to enhance your knowledge of Hadoop to solve challenging data processing problems? Are your Hadoop jobs, Pig scripts, or Hive queries not working as fast as you intend? Are you looking to understand the benefits of upgrading Hadoop? If the answer is yes to any of these, this book is for you. It assumes novice-level familiarity with Hadoop.

Author: Eric Sammer
Publisher: "O'Reilly Media, Inc."
ISBN: 1449327052
Category : Computers
Languages : en
Pages : 298

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Book Description
For system administrators tasked with the job of maintaining large and complex Hadoop clusters, this book explains the particulars of Hadoop operations, from planning, installing, and configuring the system to providing ongoing maintenance.

Author: Tom White
Publisher: "O'Reilly Media, Inc."
ISBN: 1491901705
Category : Computers
Languages : en
Pages : 802

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Book Description
Get ready to unlock the power of your data. With the fourth edition of this comprehensive guide, youâ??ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. Using Hadoop 2 exclusively, author Tom White presents new chapters on YARN and several Hadoop-related projects such as Parquet, Flume, Crunch, and Spark. Youâ??ll learn about recent changes to Hadoop, and explore new case studies on Hadoopâ??s role in healthcare systems and genomics data processing. Learn fundamental components such as MapReduce, HDFS, and YARN Explore MapReduce in depth, including steps for developing applications with it Set up and maintain a Hadoop cluster running HDFS and MapReduce on YARN Learn two data formats: Avro for data serialization and Parquet for nested data Use data ingestion tools such as Flume (for streaming data) and Sqoop (for bulk data transfer) Understand how high-level data processing tools like Pig, Hive, Crunch, and Spark work with Hadoop Learn the HBase distributed database and the ZooKeeper distributed configuration service