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Moving Hadoop to the Cloud. Harnessing Cloud Features and Flexibility for Hadoop Clusters - Helion

Moving Hadoop to the Cloud. Harnessing Cloud Features and Flexibility for Hadoop Clusters
ebook
Autor: Bill Havanki
ISBN: 978-14-919-5958-9
stron: 338, Format: ebook
Data wydania: 2017-07-14
Księgarnia: Helion

Cena książki: 126,65 zł (poprzednio: 147,27 zł)
Oszczędzasz: 14% (-20,62 zł)

Dodaj do koszyka Moving Hadoop to the Cloud. Harnessing Cloud Features and Flexibility for Hadoop Clusters

Until recently, Hadoop deployments existed on hardware owned and run by organizations. Now, of course, you can acquire the computing resources and network connectivity to run Hadoop clusters in the cloud. But there’s a lot more to deploying Hadoop to the public cloud than simply renting machines.

This hands-on guide shows developers and systems administrators familiar with Hadoop how to install, use, and manage cloud-born clusters efficiently. You’ll learn how to architect clusters that work with cloud-provider features—not just to avoid pitfalls, but also to take full advantage of these services. You’ll also compare the Amazon, Google, and Microsoft clouds, and learn how to set up clusters in each of them.

  • Learn how Hadoop clusters run in the cloud, the problems they can help you solve, and their potential drawbacks
  • Examine the common concepts of cloud providers, including compute capabilities, networking and security, and storage
  • Build a functional Hadoop cluster on cloud infrastructure, and learn what the major providers require
  • Explore use cases for high availability, relational data with Hive, and complex analytics with Spark
  • Get patterns and practices for running cloud clusters, from designing for price and security to dealing with maintenance

Dodaj do koszyka Moving Hadoop to the Cloud. Harnessing Cloud Features and Flexibility for Hadoop Clusters

 

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Dodaj do koszyka Moving Hadoop to the Cloud. Harnessing Cloud Features and Flexibility for Hadoop Clusters

Spis treści

Moving Hadoop to the Cloud. Harnessing Cloud Features and Flexibility for Hadoop Clusters eBook -- spis treści

  • Foreword
  • Preface
    • Who This Book Is For
    • What You Should Already Know
    • What This Book Leaves Out
    • How This Book Works
    • Which Software Versions This Book Uses
    • Conventions Used in This Book
      • IP Addresses
    • Using Code Examples
    • OReilly Safari
    • How to Contact Us
    • Acknowledgments
  • I. Introduction to the Cloud
  • 1. Why Hadoop in the Cloud?
    • What Is the Cloud?
    • What Does Hadoop in the Cloud Mean?
    • Reasons to Run Hadoop in the Cloud
    • Reasons to Not Run Hadoop in the Cloud
      • What About Security?
    • Hybrid Clouds
    • Hadoop Solutions from Cloud Providers
      • Elastic MapReduce
      • Google Cloud Dataproc
      • HDInsight
      • Hadoop-Like Services
      • A Spectrum of Choices
    • Getting Started
  • 2. Overview and Comparison of Cloud Providers
    • Amazon Web Services
      • References
    • Google Cloud Platform
      • References
    • Microsoft Azure
      • References
    • Which One Should You Use?
  • II. Cloud Primer
  • 3. Instances
    • Instance Types
    • Regions and Availability Zones
    • Instance Control
    • Temporary Instances
      • Spot Instances
      • Preemptible Instances
    • Images
    • No Instance Is an Island
  • 4. Networking and Security
    • A Drink of CIDR
    • Virtual Networks
      • Private DNS
      • Public IP Addresses and DNS
    • Virtual Networks and Regions
    • Routing
      • Routing in AWS
      • Routing in Google Cloud Platform
      • Routing in Azure
    • Network Security Rules
      • Inbound Versus Outbound
      • Allow Versus Deny
      • Network Security Rules in AWS
        • Security groups
        • Network ACLs
      • Network Security Rules in Google Cloud Platform
      • Network Security Rules in Azure
    • Putting Networking and Security Together
    • What About the Data?
  • 5. Storage
    • Block Storage
      • Block Storage in AWS
      • Block Storage in Google Cloud Platform
      • Block Storage in Azure
    • Object Storage
      • Buckets
      • Data Objects
      • Object Access
      • Object Storage in AWS
      • Object Storage in Google Cloud Platform
      • Object Storage in Azure
    • Cloud Relational Databases
      • Cloud Relational Databases in AWS
      • Cloud Relational Databases in Google Cloud Platform
      • Cloud Relational Databases in Azure
    • Cloud NoSQL Databases
    • Where to Start?
  • III. A Simple Cluster in the Cloud
  • 6. Setting Up in AWS
    • Prerequisites
    • Allocating Instances
      • Generating a Key Pair
      • Launching Instances
        • The manager instance
        • The worker instances
    • Securing the Instances
    • Next Steps
  • 7. Setting Up in Google Cloud Platform
    • Prerequisites
    • Creating a Project
    • Allocating Instances
      • SSH Keys
      • Creating Instances
        • The manager instance
        • The worker instances
    • Securing the Instances
    • Next Steps
  • 8. Setting Up in Azure
    • Prerequisites
    • Creating a Resource Group
    • Creating Resources
    • SSH Keys
    • Creating Virtual Machines
      • The Manager Instance
      • The Worker Instances
    • Next Steps
  • 9. Standing Up a Cluster
    • The JDK
    • Hadoop Accounts
    • Passwordless SSH
    • Hadoop Installation
    • HDFS and YARN Configuration
      • The Environment
      • XML Configuration Files
      • Finishing Up Configuration
    • Startup
    • SSH Tunneling
    • Running a Test Job
      • What If the Job Hangs?
    • Running Basic Data Loading and Analysis
      • Wikipedia Exports
      • Analyzing a Small Export
        • Generating the export
        • The MapReduce jobs
    • Go Bigger
  • IV. Enhancing Your Cluster
  • 10. High Availability
    • Planning HA in the Cloud
      • HDFS HA
        • What about the datanodes?
      • YARN HA
    • Installing and Configuring ZooKeeper
    • Adding New HDFS and YARN Daemons
      • The Second Manager
      • HDFS HA Configuration
      • YARN HA Configuration
    • Testing HA
    • Improving the HA Configuration
      • A Bigger Cluster
      • Complete HA
      • A Third Availability Zone?
    • Benchmarking HA
      • MRBench
      • Terasort
      • Grains of Salt
  • 11. Relational Data with Apache Hive
    • Planning for Hive in the Cloud
    • Installing and Configuring Hive
    • Startup
    • Running Some Test Hive Queries
    • Switching to a Remote Metastore
      • The Remote Metastore and Stopped Clusters
    • Hive Control Scripts
    • Hive on S3
      • Configuring the S3 Filesystem
      • Adding Data to S3
      • Configuring S3 Authentication
      • Configuring the S3 Endpoint
      • External Table in S3
    • What About Google Cloud Platform and Azure?
    • A Step Toward Transient Clusters
    • A Different Means of Computation
  • 12. Streaming in the Cloud with Apache Spark
    • Planning for Spark in the Cloud
    • Installing and Configuring Spark
    • Startup
    • Running Some Test Jobs
    • Configuring Hive on Spark
      • Add Spark Libraries to Hive
      • Configure Hive for Spark
      • Switch YARN to the Fair Scheduler
      • Try Out Hive on Spark on YARN
    • Spark Streaming from AWS Kinesis
      • Creating a Kinesis Stream
      • Populating the Stream with Data
      • Streaming Kinesis Data into Spark
        • Packaging the streaming job
        • Running the streaming job
        • Stopping the streaming job
    • What About Google Cloud Platform and Azure?
    • Building Clusters Versus Building Clusters Well
  • V. Care and Feeding of Hadoop in the Cloud
  • 13. Pricing and Performance
    • Picking Instance Types
      • The Criteria
      • General Cluster Instance Roles
    • Persistent Versus Ephemeral Block Storage
    • Stopping and Starting Entire Clusters
    • Using Temporary Instances
    • Geographic Considerations
      • Regions
      • Availability Zones
    • Performance and Networking
  • 14. Network Topologies
    • Public and Private Subnets
      • SSH Tunneling
      • SOCKS Proxy
      • VPN Access
      • Access from Other Subnets
    • Cluster Topologies
      • The Public Cluster
      • The Secured Public Cluster
      • Gateway Instances
      • The Private Cluster
      • Cluster Access to the Internet and Cloud Provider Services
    • Geographic Considerations
      • Regions
      • Availability Zones
    • Starting Topologies
    • Higher-Level Planning
  • 15. Patterns for Cluster Usage
    • Long-Running or Transient?
    • Single-User or Multitenant?
    • Self-Service or Managed?
    • Cloud-Only or Hybrid?
    • Watching Cost
    • The Rising Need for Automation
  • 16. Using Images for Cluster Management
    • The Structure of an Image
      • EC2 Images
      • GCE Images
      • Azure Images
    • Image Preparation
      • Wait, Im Using That!
    • Image Creation
      • Image Creation in AWS
      • Image Creation in Google Cloud Platform
      • Image Creation in Azure
    • Image Use
      • Scripting Hadoop Configuration
    • Image Maintenance
    • Image Deletion
      • Image Deletion in AWS
      • Image Deletion in Google Cloud Platform
      • Image Deletion in Azure
    • Automated Image Creation with Packer
    • Automated Cloud Cluster Creation
      • Cloudera Director
      • Hortonworks Data Cloud
      • Qubole Data Service
      • General System Management Tools
    • Images or Tools?
    • More Tooling
  • 17. Monitoring and Automation
    • Monitoring Choices
      • Cloud Provider Monitoring Services
      • Rolling Your Own
    • Cloud Provider Command-Line Interfaces
      • AWS CLI
      • Google Cloud Platform CLI
      • Azure CLI
      • Data Formatting for CLI Results
    • What to Monitor
      • Instance Existence
      • Instance Reachability
        • Reachability checks using a provider CLI
        • Rolling your own reachability checks
      • Hadoop Daemon Status
        • Cloud provider custom metrics
        • Rolling your own Hadoop daemon status checks
      • System Load
        • AWS system monitoring
        • Google Cloud Platform system monitoring
        • Azure system monitoring
        • Rolling your own system checks
      • Putting Scripting to Use
    • Custom Metrics in CloudWatch
      • Basic Metrics
      • Defining a Custom Metric
      • Feeding Custom Metric Data to CloudWatch
      • Setting an Alarm on a Custom Metric
    • Elastic Compute Using a Custom Metric
      • A Custom Metric for Compute Capacity
      • Prerequisites for Autoscaling Compute
      • Triggering Autoscaling with an Alarm Action
      • What About Shrinking?
      • Other Things to Watch
    • Ingesting Logs into CloudWatch
      • Creating an IAM User for Log Streaming
      • Installing the CloudWatch Agent
      • Creating a Metric Filter
      • Creating an Alarm from a Metric Filter
    • So Much More to See and Do
  • 18. Backup and Restoration
    • Patterns to Supplement Backups
    • Backup via Imaging
    • HDFS Replication
      • Cloud Storage Filesystems
      • HDFS Snapshots
    • Hive Metastore Replication
    • Logs
    • A General Cloud Hadoop Backup Strategy
    • Not So Different, But Better
    • To the Cloud
  • A. Hadoop Component Start and Stop Scripts
    • Apache ZooKeeper
    • Apache Hive
  • B. Hadoop Cluster Configuration Scripts
    • SSH Key Creation and Distribution
    • Configuration Update Script
      • New Worker Configuration Update Script
  • C. Monitoring Cloud Clusters with Nagios
    • Where Nagios Should Run
    • Instance Existence Through Ping
    • Hosts and Host Groups
    • Services and Service Groups
    • Provider CLI Integration
  • Index

Dodaj do koszyka Moving Hadoop to the Cloud. Harnessing Cloud Features and Flexibility for Hadoop Clusters

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