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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 127.0.0.1
  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
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Chapter 8. Cluster Maintenance

Hadoop clusters require a moderate amount of day-to-day care and feeding in order to remain healthy and in optimal working condition. Maintenance tasks are usually performed in response to events: expanding the cluster, dealing with failures or errant jobs, managing logs, or upgrading software in a production environment. This chapter is written in “run book form,” with common tasks called out and simple processes for dealing with those situations. It’s not meant to supplant a complete understanding of the system, and as always, the normal caveats apply when dealing with systems that store data or serve critical functions.

Managing Hadoop Processes

It’s not at all unusual to need to start, stop, or restart Hadoop daemons because of configuration changes or as part of a larger process. Depending on the selected deployment model and distribution, this can be as simple as using standard service init scripts or by way of specialized scripts for Hadoop. Some administrators may use configuration management systems such as Puppet and Chef to manage processes.

Starting and Stopping Processes with Init Scripts

The most common reason administrators restart Hadoop processes is to enact configuration changes. Other common reasons are to upgrade Hadoop, add or remove worker nodes, or react to incidents. The effect of starting or stopping a process is entirely dependent upon the process in question. Starting a namenode will bring it into service after it loads the ...

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