OReilly.Hadoop.The.Definitive.Guide.4th.Edition
Introduction
电子版自序
Foreword
Preface
Administrative Notes
What’s New in the Fourth Edition?
What’s New in the Third Edition?
What’s New in the Second Edition?
Conventions Used in This Book
Using Code Examples
Safari® Books Online
How to Contact Us
Acknowledgments
Part I. Hadoop Fundamentals
Chapter 1. Meet Hadoop
Data!
Data Storage and Analysis
Querying All Your Data
Beyond Batch
Comparison with Other Systems
Relational Database Management Systems
Grid Computing
Volunteer Computing
A Brief History of Apache Hadoop
What’s in This Book?
Chapter 2. MapReduce
A Weather Dataset
Data Format
Analyzing the Data with Unix Tools
Map and Reduce
Java MapReduce
Scaling Out
Data Flow
Combiner Functions
Running a Distributed MapReduce Job
Hadoop Streaming
Ruby
Python
Chapter 3. The Hadoop Distributed Filesystem
The Design of HDFS
HDFS Concepts
Blocks
Namenodes and Datanodes
Block Caching
HDFS Federation
HDFS High Availability
The Command-Line Interface
Basic Filesystem Operations
Hadoop Filesystems
Interfaces
The Java Interface
Reading Data from a Hadoop URL
Reading Data Using the FileSystem API
Writing Data
Directories
Querying the Filesystem
Deleting Data
Data Flow
Anatomy of a File Read
Anatomy of a File Write
Coherency Model
Parallel Copying with distcp
Keeping an HDFS Cluster Balanced
Chapter 4. YARN
Anatomy of a YARN Application Run
Resource Requests
Application Lifespan
Building YARN Applications
YARN Compared to MapReduce 1
Scheduling in YARN
Scheduler Options
Capacity Scheduler Configuration
Fair Scheduler Configuration
Delay Scheduling
Dominant Resource Fairness
Further Reading
Chapter 5. Hadoop I\/O
Data Integrity
Data Integrity in HDFS
LocalFileSystem
ChecksumFileSystem
Compression
Codecs
Compression and Input Splits
Using Compression in MapReduce
Serialization
The Writable Interface
Writable Classes
Implementing a Custom Writable
Serialization Frameworks
File-Based Data Structures
SequenceFile
MapFile
Other File Formats and Column-Oriented Formats
Part II. MapReduce
Chapter 6. Developing a MapReduce Application
The Configuration API
Combining Resources
Variable Expansion
Setting Up the Development Environment
Managing Configuration
GenericOptionsParser, Tool, and ToolRunner
Writing a Unit Test with MRUnit
Mapper
Reducer
Running Locally on Test Data
Running a Job in a Local Job Runner
Testing the Driver
Running on a Cluster
Packaging a Job
Launching a Job
The MapReduce Web UI
Retrieving the Results
Debugging a Job
Hadoop Logs
Remote Debugging
Tuning a Job
Profiling Tasks
MapReduce Workflows
Decomposing a Problem into MapReduce Jobs
JobControl
Apache Oozie
Chapter 7. How MapReduce Works
Anatomy of a MapReduce Job Run
Job Submission
Job Initialization
Task Assignment
Task Execution
Progress and Status Updates
Job Completion
Failures
Task Failure
Application Master Failure
Node Manager Failure
Resource Manager Failure
Shuffle and Sort
The Map Side
The Reduce Side
Configuration Tuning
Task Execution
The Task Execution Environment
Output Committers
Chapter 8. MapReduce Types and Formats
MapReduce Types
The Default MapReduce Job
Input Formats
Input Splits and Records
Text Input
Binary Input
Multiple Inputs
Database Input (and Output)
Output Formats
Text Output
Binary Output
Multiple Outputs
Lazy Output
Database Output
Chapter 9. MapReduce Features
Counters
Built-in Counters
User-Defined Java Counters
User-Defined Streaming Counters
Sorting
Preparation
Partial Sort
Total Sort
Secondary Sort
Joins
Map-Side Joins
Reduce-Side Joins
Side Data Distribution
Using the Job Configuration
Distributed Cache
MapReduce Library Classes
Part III. Hadoop Operations
Chapter 10. Setting Up a Hadoop Cluster
Cluster Specification
Cluster Sizing
Network Topology
Cluster Setup and Installation
Installing Java
Creating Unix User Accounts
Installing Hadoop
Configuring SSH
Configuring Hadoop
Formatting the HDFS Filesystem
Starting and Stopping the Daemons
Creating User Directories
Hadoop Configuration
Configuration Management
Environment Settings
Important Hadoop Daemon Properties
Hadoop Daemon Addresses and Ports
Other Hadoop Properties
Security
Kerberos and Hadoop
Delegation Tokens
Other Security Enhancements
Benchmarking a Hadoop Cluster
Hadoop Benchmarks
User Jobs
Chapter 11. Administering Hadoop
HDFS
Persistent Data Structures
Safe Mode
Audit Logging
Tools
Monitoring
Logging
Metrics and JMX
Maintenance
Routine Administration Procedures
Commissioning and Decommissioning Nodes
Upgrades
Part IV. Related Projects
Chapter 12. Avro
Avro Data Types and Schemas
In-Memory Serialization and Deserialization
The Specific API
Avro Datafiles
Interoperability
Python API
Avro Tools
Schema Resolution
Sort Order
Avro MapReduce
Sorting Using Avro MapReduce
Avro in Other Languages
Chapter 13. Parquet
Data Model
Nested Encoding
Parquet File Format
Parquet Configuration
Writing and Reading Parquet Files
Avro, Protocol Buffers, and Thrift
Parquet MapReduce
Chapter 14. Flume
Installing Flume
An Example
Transactions and Reliability
Batching
The HDFS Sink
Partitioning and Interceptors
File Formats
Fan Out
Delivery Guarantees
Replicating and Multiplexing Selectors
Distribution: Agent Tiers
Delivery Guarantees
Sink Groups
Integrating Flume with Applications
Component Catalog
Further Reading
Chapter 15. Sqoop
Getting Sqoop
Sqoop Connectors
A Sample Import
Text and Binary File Formats
Generated Code
Additional Serialization Systems
Imports: A Deeper Look
Controlling the Import
Imports and Consistency
Incremental Imports
Direct-Mode Imports
Working with Imported Data
Imported Data and Hive
Importing Large Objects
Performing an Export
Exports: A Deeper Look
Exports and Transactionality
Exports and SequenceFiles
Further Reading
Chapter 16. Pig
Installing and Running Pig
Execution Types
Local mode
MapReduce mode
Running Pig Programs
Grunt
Pig Latin Editors
An Example
Generating Examples
Comparison with Databases
Pig Latin
Structure
Statements
Expressions
Types
Schemas
Functions
Macros
User-Defined Functions
A Filter UDF
An Eval UDF
A Load UDF
Data Processing Operators
Loading and Storing Data
Filtering Data
Grouping and Joining Data
Sorting Data
Combining and Splitting Data
Pig in Practice
Parallelism
Anonymous Relations
Parameter Substitution
Further Reading
Chapter 17. Hive
Installing Hive
The Hive Shell
An Example
Running Hive
Configuring Hive
Hive Services
The Metastore
Comparison with Traditional Databases
Schema on Read Versus Schema on Write
Updates, Transactions, and Indexes
SQL-on-Hadoop Alternatives
HiveQL
Data Types
Operators and Functions
Tables
Managed Tables and External Tables
Partitions and Buckets
Storage Formats
Importing Data
Altering Tables
Dropping Tables
Querying Data
Sorting and Aggregating
MapReduce Scripts
Joins
Subqueries
Views
User-Defined Functions
Writing a UDF
Writing a UDAF
Further Reading
Chapter 18. Crunch
An Example
The Core Crunch API
Primitive Operations
Types
Sources and Targets
Functions
Materialization
Pipeline Execution
Running a Pipeline
Stopping a Pipeline
Inspecting a Crunch Plan
Iterative Algorithms
Checkpointing a Pipeline
Crunch Libraries
Further Reading
Chapter 19. Spark
Installing Spark
An Example
Spark Applications, Jobs, Stages, and Tasks
A Scala Standalone Application
A Java Example
A Python Example
Resilient Distributed Datasets
Creation
Transformations and Actions
Persistence
Serialization
Shared Variables
Broadcast Variables
Accumulators
Anatomy of a Spark Job Run
Job Submission
DAG Construction
Task Scheduling
Task Execution
Executors and Cluster Managers
Spark on YARN
Further Reading
Chapter 20. HBase
HBasics
Backdrop
Concepts
Whirlwind Tour of the Data Model
Implementation
Installation
Test Drive
Clients
Java
MapReduce
REST and Thrift
Building an Online Query Application
Schema Design
Loading Data
Online Queries
HBase Versus RDBMS
Successful Service
HBase
Praxis
HDFS
UI
Metrics
Counters
Further Reading
Chapter 21. ZooKeeper
Installing and Running ZooKeeper
An Example
Group Membership in ZooKeeper
Creating the Group
Joining a Group
Listing Members in a Group
Deleting a Group
The ZooKeeper Service
Data Model
Operations
Implementation
Consistency
Sessions
States
Building Applications with ZooKeeper
A Configuration Service
The Resilient ZooKeeper Application
A Lock Service
More Distributed Data Structures and Protocols
ZooKeeper in Production
Resilience and Performance
Configuration
Further Reading
Part V. Case Studies
Chapter 22. Composable Data at Cerner
From CPUs to Semantic Integration
Enter Apache Crunch
Building a Complete Picture
Integrating Healthcare Data
Composability over Frameworks
Moving Forward
Chapter 23. Biological 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
Literate programming with the Avro interface description language (IDL)
Column-oriented access with Parquet
A simple example: k-mer counting using Spark and ADAM
From Personalized Ads to Personalized Medicine
Join In
Chapter 24. Cascading
Fields, Tuples, and Pipes
Operations
Taps, Schemes, and Flows
Cascading in Practice
Flexibility
Hadoop and Cascading at ShareThis
Summary
Appendix A. Installing Apache Hadoop
Prerequisites
Installation
Configuration
Standalone Mode
Pseudodistributed Mode
Fully Distributed Mode
Appendix B. Cloudera’s Distribution Including Apache Hadoop
Appendix C. Preparing the NCDC Weather Data
Appendix D. The Old and New Java MapReduce APIs
Index
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Using Compression in MapReduce
Using Compression in MapReduce
Compressing map output
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