Tiefpreis
CHF49.20
Auslieferung erfolgt in der Regel innert 2 bis 3 Wochen.
Autorentext
Sam R. Alapati has been working with various aspects of the Hadoop environment for the past six years. He is currently the principal Hadoop administrator at Sabre Corporation in Westlake, Texas, and works on a daily basis with multiple large Hadoop 2 clusters. In addition to being the point person for all Hadoop administration at Sabre, Sam manages multiple critical data-science- and data-analysis-related Hadoop job flows and is also an expert Oracle Database Administrator. His vast knowledge of relational databases and SQL contributes to his work with Hadoop related projects. Sam’s recognition in the database and middleware area includes having published 18 well-received books over the past 14 years, mostly on Oracle Database Administration and Oracle Weblogic Server. His experience dealing with numerous configuration, architectural, and performance-related Hadoop issues over the years led him to the realization that many working Hadoop administrators and developers would appreciate having a handy reference such as this book to turn to when creating, managing, securing and optimizing their Hadoop infrastructure.
Klappentext
In Expert Hadoop® Administration, leading Hadoop administrator Sam R. Alapati brings together authoritative knowledge for creating, configuring, securing, managing, and optimizing production Hadoop clusters in any environment. Drawing on his experience with large-scale Hadoop administration, Alapati integrates action-oriented advice with carefully researched explanations of both problems and solutions. He covers an unmatched range of topics and offers an unparalleled collection of realistic examples.
Alapati demystifies complex Hadoop environments, helping readers understand exactly what happens behind the scenes when they administer their cluster. Students will gain unprecedented insight as they walk through building clusters from scratch and configuring high availability, performance, security, encryption, and other key attributes.
Zusammenfassung
The Comprehensive, Up-to-Date Apache Hadoop Administration Handbook and Reference
“Sam Alapati has worked with production Hadoop clusters for six years. His unique depth of experience has enabled him to write the go-to resource for all administrators looking to spec, size, expand, and secure production Hadoop clusters of any size.”
–Paul Dix, Series Editor
In Expert Hadoop® Administration, leading Hadoop administrator Sam R. Alapati brings together authoritative knowledge for creating, configuring, securing, managing, and optimizing production Hadoop clusters in any environment. Drawing on his experience with large-scale Hadoop administration, Alapati integrates action-oriented advice with carefully researched explanations of both problems and solutions. He covers an unmatched range of topics and offers an unparalleled collection of realistic examples.
Alapati demystifies complex Hadoop environments, helping you understand exactly what happens behind the scenes when you administer your cluster. You’ll gain unprecedented insight as you walk through building clusters from scratch and configuring high availability, performance, security, encryption, and other key attributes. The high-value administration skills you learn here will be indispensable no matter what Hadoop distribution you use or what Hadoop applications you run.
Inhalt
Foreword xxvii
Preface xxix
Acknowledgments xxxv
About the Author xxxvii
Part I: Introduction to Hadoop—Architecture and Hadoop Clusters 1
Chapter 1: Introduction to Hadoop and Its Environment 3
Hadoop—An Introduction 4
Cluster Computing and Hadoop Clusters 12
Hadoop Components and the Hadoop Ecosphere 15
What Do Hadoop Administrators Do? 18
Key Differences between Hadoop 1 and Hadoop 2 21
Distributed Data Processing: MapReduce and Spark, Hive and Pig 24
Data Integration: Apache Sqoop, Apache Flume and
Apache Kafka 27
Key Areas of Hadoop Administration 28
Summary 31
Chapter 2: An Introduction to the Architecture of Hadoop 33
Distributed Computing and Hadoop 33
Hadoop Architecture 34
Data Storage—The Hadoop Distributed File System 37
Data Processing with YARN, the Hadoop Operating System 48
Summary 57
Chapter 3: Creating and Configuring a Simple Hadoop Cluster 59
Hadoop Distributions and Installation Types 60
Setting Up a Pseudo-Distributed Hadoop Cluster 62
Performing the Initial Hadoop Configuration 71
Operating the New Hadoop Cluster 86
Summary 90
Chapter 4: Planning for and Creating a Fully Distributed Cluster 91
Planning Your Hadoop Cluster 92
Going from a Single Rack to Multiple Racks 95
Creating a Multinode Cluster 102
Modifying the Hadoop Configuration 106
Starting Up the Cluster 114
Configuring Hadoop Services, Web Interfaces and Ports 119
Summary 126
Part II: Hadoop Application Frameworks 127
Chapter 5: Running Applications in a Cluster—The MapReduce Framework (and Hive and Pig) 129
The MapReduce Framework 129
Apache Hive 141
Apache Pig 144
Summary 145
Chapter 6: Running Applications in a Cluster—The Spark Framework 147
What Is Spark? 148
Why Spark? 149
The Spark Stack 153
Installing Spark 155
Spark Run Modes 158
Understanding the Cluster Managers 159
Spark and Data Access 164
Summary 167
Chapter 7: Running Spark Applications 169
The Spark Programming Model 169
Spark Applications 173
Architecture of a Spark Application 179
Running Spark Applications Interactively 181
Creating and Submitting Spark Applications 185
Configuring Spark Applications 192
Monitoring Spark Applications 194
Handling Streaming Data with Spark Streaming 194
Using Spark SQL for Handling Structured Data 198
Summary 201
Part III: Managing and Protecting Hadoop Data and High Availability 203
Chapter 8: The Role of the NameNode and How HDFS Works 205
HDFS—The Interaction between the NameNode and the DataNodes 205
Rack Awareness and Topology 209
HDFS Data Replication 212
How Clients Read and Write HDFS Data 218
Understanding HDFS Recovery Processes 224
Centralized Cache Management in HDFS 227
Hadoop Archival Storage, SSD and Memory (Heterogeneous Storage) 232
Summary 241
Chapter 9: HDFS Commands, HDFS Permissions and HDFS Storage 243
Managing HDFS through the HDFS Shell Commands 243
Using the dfsadmin Utility to Perform HDFS Operations 251
Managing HDFS Permissions and Users 255
Managing HDFS Storage 260
Rebalancing HDFS Data 267
Reclaiming HDFS Space 274
Summary 276
Chapter 10: Data Protection, File Formats and Accessing HDFS 277
Safeguarding Data 278
Data Compression 289
Hadoop File Formats 295
Using Hadoop WebHDFS and HttpFS 308
Summary 315
Chapter 11: NameNode Operations, High Availability and Federation 317
Understanding NameNode Operations 318
The Checkpointing Process 323
NameNode Safe Mode Operations 329
Configuring HDFS High Availability 334
HDFS Federation 349
Summa…