You are previewing Hadoop Operations.

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 7. Resource Management

What Is Resource Management?

In a perfect world, multiple groups of users, each with jobs with different service level agreements (SLAs), would be able to coexist on a shared system, blissfully unaware of one another. Disk space and IO, memory, CPU time, and network bandwidth would be limitless, and MapReduce jobs would run unimpeded by the mundane details of competing disk access patterns, activity oscillation throughout the work day, and poorly implemented algorithms that spew data to disk faster than your average administrator can rap a developer across the knuckles. We don’t live in that world and the infinite elastic utopia where the locality of terabytes (or more) of data is meaningless is not yet upon us. The question then, is how do we create an environment where competing interests can coexist peacefully, all the while ensuring the right jobs receive the right resources at the right time?

Resource management is about controlling how much of a finite resource should be allocated to a given user, group, or job. The resources—generally bisected into the categories of storage and compute—should be appropriately distributed across whatever designations make sense within the larger organization. This can mean allocation by the person for whom the work is performed, although more commonly, it is by line of business, where each group has jobs of varying criticality. Resource allocation is related to authentication in that we must know who someone is ...

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