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Hadoop Operations

Cover of Hadoop Operations by Eric Sammer Published by O'Reilly Media, Inc.
  1. Hadoop Operations
  2. Dedication
  3. Preface
    1. Conventions Used in This Book
    2. Using Code Examples
    3. Safari® Books Online
    4. How to Contact Us
    5. Acknowledgments
  4. 1. Introduction
  5. 2. HDFS
    1. Goals and Motivation
    2. Design
    3. Daemons
    4. Reading and Writing Data
      1. The Read Path
      2. The Write Path
    5. Managing Filesystem Metadata
    6. Namenode High Availability
    7. Namenode Federation
    8. Access and Integration
      1. Command-Line Tools
      2. FUSE
      3. REST Support
  6. 3. MapReduce
    1. The Stages of MapReduce
    2. Introducing Hadoop MapReduce
      1. Daemons
      2. When It All Goes Wrong
    3. YARN
  7. 4. Planning a Hadoop Cluster
    1. Picking a Distribution and Version of Hadoop
      1. Apache Hadoop
      2. Cloudera’s Distribution Including Apache Hadoop
      3. Versions and Features
      4. What Should I Use?
    2. Hardware Selection
      1. Master Hardware Selection
      2. Worker Hardware Selection
      3. Cluster Sizing
      4. Blades, SANs, and Virtualization
    3. Operating System Selection and Preparation
      1. Deployment Layout
      2. Software
      3. Hostnames, DNS, and Identification
      4. Users, Groups, and Privileges
    4. Kernel Tuning
      1. vm.swappiness
      2. vm.overcommit_memory
    5. Disk Configuration
      1. Choosing a Filesystem
      2. Mount Options
    6. Network Design
      1. Network Usage in Hadoop: A Review
      2. 1 Gb versus 10 Gb Networks
      3. Typical Network Topologies
  8. 5. Installation and Configuration
    1. Installing Hadoop
      1. Apache Hadoop
      2. CDH
    2. Configuration: An Overview
      1. The Hadoop XML Configuration Files
    3. Environment Variables and Shell Scripts
    4. Logging Configuration
    5. HDFS
      1. Identification and Location
      2. Optimization and Tuning
      3. Formatting the Namenode
      4. Creating a /tmp Directory
    6. Namenode High Availability
      1. Fencing Options
      2. Basic Configuration
      3. Automatic Failover Configuration
      4. Format and Bootstrap the Namenodes
    7. Namenode Federation
    8. MapReduce
      1. Identification and Location
      2. Optimization and Tuning
    9. Rack Topology
    10. Security
  9. 6. Identity, Authentication, and Authorization
    1. Identity
    2. Kerberos and Hadoop
      1. Kerberos: A Refresher
      2. Kerberos Support in Hadoop
    3. Authorization
      1. HDFS
      2. MapReduce
      3. Other Tools and Systems
    4. Tying It Together
  10. 7. Resource Management
    1. What Is Resource Management?
    2. HDFS Quotas
    3. MapReduce Schedulers
      1. The FIFO Scheduler
      2. The Fair Scheduler
      3. The Capacity Scheduler
      4. The Future
  11. 8. Cluster Maintenance
    1. Managing Hadoop Processes
      1. Starting and Stopping Processes with Init Scripts
      2. Starting and Stopping Processes Manually
    2. HDFS Maintenance Tasks
      1. Adding a Datanode
      2. Decommissioning a Datanode
      3. Checking Filesystem Integrity with fsck
      4. Balancing HDFS Block Data
      5. Dealing with a Failed Disk
    3. MapReduce Maintenance Tasks
      1. Adding a Tasktracker
      2. Decommissioning a Tasktracker
      3. Killing a MapReduce Job
      4. Killing a MapReduce Task
      5. Dealing with a Blacklisted Tasktracker
  12. 9. Troubleshooting
    1. Differential Diagnosis Applied to Systems
    2. Common Failures and Problems
      1. Humans (You)
      2. Misconfiguration
      3. Hardware Failure
      4. Resource Exhaustion
      5. Host Identification and Naming
      6. Network Partitions
    3. “Is the Computer Plugged In?”
      1. E-SPORE
    4. Treatment and Care
    5. War Stories
      1. A Mystery Bottleneck
      2. There’s No Place Like
  13. 10. Monitoring
    1. An Overview
    2. Hadoop Metrics
      1. Apache Hadoop 0.20.0 and CDH3 (metrics1)
      2. Apache Hadoop 0.20.203 and Later, and CDH4 (metrics2)
      3. What about SNMP?
    3. Health Monitoring
      1. Host-Level Checks
      2. All Hadoop Processes
      3. HDFS Checks
      4. MapReduce Checks
  14. 11. Backup and Recovery
    1. Data Backup
      1. Distributed Copy (distcp)
      2. Parallel Data Ingestion
    2. Namenode Metadata
  15. A. Deprecated Configuration Properties
  16. Index
  17. About the Author
  18. Colophon
  19. Copyright

Chapter 9. Troubleshooting

Throughout this book, the notion that Hadoop is a distributed system made up of layered services has been a repeating theme. The interaction between these layers is what makes a system like this so complex and so difficult to troubleshoot. With complex moving parts, interdependent systems, sensitivity to environmental conditions and external factors, and numerous potential causes for numerous potential conditions, Hadoop starts to look like the human body. We’ll treat it as such (with my apologies to the medical field as a whole).

Differential Diagnosis Applied to Systems

A significant portion of problems encountered with systems, in general, remain so because of improper diagnosis.[21] You cannot fix something when you don’t know what’s truly wrong. The medical field commonly uses a differential diagnosis process as a way of investigating symptoms and their likelihood in order to properly diagnose a patient with a condition. Differential diagnoses, for those of us without an MD, is essentially a knowledge- and data-driven process of elimination whereby tests are performed to confirm or reject a potential condition. In fact, this isn’t as exotic a concept as it initially sounds when you think about how our brains attack these kinds of problems. It does, however, help to formalize such an approach and follow it, especially when things go wrong and your boss is standing over your shoulder asking you every five minutes whether it’s fixed yet. When things go ...

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