Hadoop: The Definitive Guide, 4th Edition

相似文件 换一批

是 否 +2 论坛币

k人 参与回答

经管之家送您一份

应届毕业生专属福利!

求职就业群

赵安豆老师微信：zhaoandou666

经管之家联合CDA

送您一个全额奖学金名额~ !

立即领取

感谢您参与论坛问题回答

经管之家送您两个论坛币！

+2 论坛币

Hadoop_ The Definitive Guide, 4th Edition.pdf (10.64 MB, 需要: 5 个论坛币)

2015-11-20 11:00:27 上传

The latest version: The definitive guide for Hadoop
需要: 5 个论坛币  [购买]

Get ready to unlock the power of your data. With the fourth edition of this comprehensive guide, you’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. You’ll learn about recent changes to Hadoop, and explore new case studies on Hadoop’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.
  

• Hadoop Fundamentals
  
  • Chapter 1Meet Hadoop
    
    • Data!
    • Data Storage and Analysis
    • Querying All Your Data
    • Beyond Batch
    • Comparison with Other Systems
    • A Brief History of Apache Hadoop
    • What’s in This Book?
      
      
  • Chapter 2MapReduce
    
    • A Weather Dataset
    • Analyzing the Data with Unix Tools
    • Analyzing the Data with Hadoop
    • Scaling Out
    • Hadoop Streaming
      
      
  • Chapter 3The Hadoop Distributed Filesystem
    
    • The Design of HDFS
    • HDFS Concepts
    • The Command-Line Interface
    • Hadoop Filesystems
    • The Java Interface
    • Data Flow
    • Parallel Copying with distcp
      
      
  • Chapter 4YARN
    
    • Anatomy of a YARN Application Run
    • YARN Compared to MapReduce 1
    • Scheduling in YARN
    • Further Reading
      
      
  • Chapter 5Hadoop I/O
    
    • Data Integrity
    • Compression
    • Serialization
    • File-Based Data Structures
      
      
    
    
• MapReduce
  
  • Chapter 1Developing a MapReduce Application
    
    • The Configuration API
    • Setting Up the Development Environment
    • Writing a Unit Test with MRUnit
    • Running Locally on Test Data
    • Running on a Cluster
    • Tuning a Job
    • MapReduce Workflows
      
      
  • Chapter 2How MapReduce Works
    
    • Anatomy of a MapReduce Job Run
    • Failures
    • Shuffle and Sort
    • Task Execution
      
      
  • Chapter 3MapReduce Types and Formats
    
    • MapReduce Types
    • Input Formats
    • Output Formats
      
      
  • Chapter 4MapReduce Features
    
    • Counters
    • Sorting
    • Joins
    • Side Data Distribution
    • MapReduce Library Classes
      
      
    
    
• Hadoop Operations
  
  • Chapter 1Setting Up a Hadoop Cluster
    
    • Cluster Specification
    • Cluster Setup and Installation
    • Hadoop Configuration
    • Security
    • Benchmarking a Hadoop Cluster
      
      
  • Chapter 2Administering Hadoop
    
    • HDFS
    • Monitoring
    • Maintenance
      
      
    
    
• Related Projects
  
  • Chapter 1Avro
    
    • Avro Data Types and Schemas
    • In-Memory Serialization and Deserialization
    • Avro Datafiles
    • Interoperability
    • Schema Resolution
    • Sort Order
    • Avro MapReduce
    • Sorting Using Avro MapReduce
    • Avro in Other Languages
      
      
  • Chapter 2Parquet
    
    • Data Model
    • Parquet File Format
    • Parquet Configuration
    • Writing and Reading Parquet Files
    • Parquet MapReduce
      
      
  • Chapter 3Flume
    
    • Installing Flume
    • An Example
    • Transactions and Reliability
    • The HDFS Sink
    • Fan Out
    • Distribution: Agent Tiers
    • Sink Groups
    • Integrating Flume with Applications
    • Component Catalog
    • Further Reading
      
      
  • Chapter 4Sqoop
    
    • Getting Sqoop
    • Sqoop Connectors
    • A Sample Import
    • Generated Code
    • Imports: A Deeper Look
    • Working with Imported Data
    • Importing Large Objects
    • Performing an Export
    • Exports: A Deeper Look
    • Further Reading
      
      
  • Chapter 5Pig
    
    • Installing and Running Pig
    • An Example
    • Comparison with Databases
    • Pig Latin
    • User-Defined Functions
    • Data Processing Operators
    • Pig in Practice
    • Further Reading
      
      
  • Chapter 6Hive
    
    • Installing Hive
    • An Example
    • Running Hive
    • Comparison with Traditional Databases
    • HiveQL
    • Tables
    • Querying Data
    • User-Defined Functions
    • Further Reading
      
      
  • Chapter 7Crunch
    
    • An Example
    • The Core Crunch API
    • Pipeline Execution
    • Crunch Libraries
    • Further Reading
      
      
  • Chapter 8Spark
    
    • Installing Spark
    • An Example
    • Resilient Distributed Datasets
    • Shared Variables
    • Anatomy of a Spark Job Run
    • Executors and Cluster Managers
    • Further Reading
      
      
  • Chapter 9HBase
    
    • HBasics
    • Concepts
    • Installation
    • Clients
    • Building an Online Query Application
    • HBase Versus RDBMS
    • Praxis
    • Further Reading
      
      
  • Chapter 10ZooKeeper
    
    • Installing and Running ZooKeeper
    • An Example
    • The ZooKeeper Service
    • Building Applications with ZooKeeper
    • ZooKeeper in Production
    • Further Reading
      
      
  • Case Studies
    
    • Chapter 1Composable Data at Cerner
      
      • From CPUs to Semantic Integration
      • Enter Apache Crunch
      • Building a Complete Picture
      • Integrating Healthcare Data
      • Composability over Frameworks
      • Moving Forward
        
        
    • Chapter 2Biological Data Science: Saving Lives with Software
      
      • The Structure of DNA
      • The Genetic Code: Turning DNA Letters into Proteins
      • Thinking of DNA as Source Code
      • The Human Genome Project and Reference Genomes
      • Sequencing and Aligning DNA
      • ADAM, A Scalable Genome Analysis Platform
      • From Personalized Ads to Personalized Medicine
      • Join In
        
        
    • Chapter 3Cascading
      
      • Fields, Tuples, and Pipes
      • Operations
      • Taps, Schemes, and Flows
      • Cascading in Practice
      • Flexibility
      • Hadoop and Cascading at ShareThis
      • Summary
        
        
    • Appendix Installing Apache Hadoop
      
      • Prerequisites
      • Installation
      • Configuration
        
        
    • Appendix Cloudera’s Distribution Including Apache Hadoop
    • Appendix Preparing the NCDC Weather Data
    • Appendix The Old and New Java MapReduce APIs
      
      
    
    
• Case Studies
  
  • Chapter 1Composable Data at Cerner
    
    • From CPUs to Semantic Integration
    • Enter Apache Crunch
    • Building a Complete Picture
    • Integrating Healthcare Data
    • Composability over Frameworks
    • Moving Forward
      
      
  • Chapter 2Biological Data Science: Saving Lives with Software
    
    • The Structure of DNA
    • The Genetic Code: Turning DNA Letters into Proteins
    • Thinking of DNA as Source Code
    • The Human Genome Project and Reference Genomes
    • Sequencing and Aligning DNA
    • ADAM, A Scalable Genome Analysis Platform
    • From Personalized Ads to Personalized Medicine
    • Join In
      
      
  • Chapter 3Cascading
    
    • Fields, Tuples, and Pipes
    • Operations
    • Taps, Schemes, and Flows
    • Cascading in Practice
    • Flexibility
    • Hadoop and Cascading at ShareThis
    • Summary
      
      
  • Appendix Installing Apache Hadoop
    
    • Prerequisites
    • Installation
    • Configuration
      
      
  • Appendix Cloudera’s Distribution Including Apache Hadoop
  • Appendix Preparing the NCDC Weather Data
  • Appendix The Old and New Java MapReduce APIs
    
  
  

扫码加我 拉你入群

请注明：姓名-公司-职位

以便审核进群资格，未注明则拒绝

分享0 收藏2 回帖

关键词：Definitive Edition Hadoop dition editio Hadoop Big Data

感谢分享~！另外楼主能另外给我发一份么？ jiayounet@163.com 我因为版主扣工资，把论坛币给扣掉了，55555~

daazx 发表于 2015-11-23 09:46
感谢分享~！另外楼主能另外给我发一份么？ jiayounet@163.com 我因为版主扣工资，把论坛币给扣掉了，55555~

check email for the book.