You are previewing Programming Google App Engine.

Programming Google App Engine

Cover of Programming Google App Engine by Dan Sanderson Published by O'Reilly Media, Inc.
  1. Programming Google App Engine
    1. SPECIAL OFFER: Upgrade this ebook with O’Reilly
    2. Preface
      1. Using This Book
      2. Conventions Used in This Book
      3. Using Code Samples
      4. Safari® Books Online
      5. How to Contact Us
      6. Acknowledgments
    3. 1. Introducing Google App Engine
      1. The Runtime Environment
      2. The Static File Servers
      3. The Datastore
      4. The Services
      5. Google Accounts
      6. Task Queues and Cron Jobs
      7. Developer Tools
      8. The Administration Console
      9. Things App Engine Doesn’t Do...Yet
      10. Getting Started
    4. 2. Creating an Application
      1. Setting Up the SDK
      2. Developing the Application
      3. Registering the Application
      4. Uploading the Application
      5. Introducing the Administration Console
    5. 3. Handling Web Requests
      1. The App Engine Architecture
      2. Configuring the Frontend
      3. How the App Is Run
      4. Quotas and Limits
    6. 4. Datastore Entities
      1. Entities, Keys, and Properties
      2. Introducing the Python Datastore API
      3. Introducing the Java Datastore API
      4. Property Values
      5. Keys and Key Objects
      6. Using Entities
    7. 5. Datastore Queries
      1. Queries and Kinds
      2. Query Results and Keys
      3. GQL
      4. The Python Query API
      5. The Java Query API
      6. Introducing Indexes
      7. Automatic Indexes and Simple Queries
      8. Custom Indexes and Complex Queries
      9. Not-Equal and IN Filters
      10. Unset and Nonindexed Properties
      11. Sort Orders and Value Types
      12. Queries and Multivalued Properties
      13. Configuring Indexes
    8. 6. Datastore Transactions
      1. Entities and Entity Groups
      2. What Can Happen in a Transaction
      3. Transactions in Python
      4. Transactions in Java
      5. How Entities Are Updated
      6. How Entities Are Read
      7. Batch Updates
      8. How Indexes Are Updated
    9. 7. Data Modeling with Python
      1. Models and Properties
      2. Property Declarations
      3. Modeling Relationships
      4. Model Inheritance
      5. Queries and PolyModels
      6. Creating Your Own Property Classes
    10. 8. The Java Persistence API
      1. Setting Up JPA
      2. Entities and Keys
      3. Entity Properties
      4. Embedded Objects
      5. Saving, Fetching, and Deleting Objects
      6. Transactions in JPA
      7. Queries and JPQL
      8. Relationships
      9. For More Information
    11. 9. The Memory Cache
      1. The Python Memcache API
      2. The Java Memcache API
    12. 10. Fetching URLs and Web Resources
      1. Fetching URLs in Python
      2. Fetching URLs in Java
      3. Asynchronous Requests in Python
    13. 11. Sending and Receiving Mail and Instant Messages
      1. Enabling Inbound Services
      2. Sending Email Messages
      3. Receiving Email Messages
      4. Sending XMPP Messages
      5. Receiving XMPP Messages
    14. 12. Bulk Data Operations and Remote Access
      1. Setting Up the Remote API for Python
      2. Setting Up the Remote API for Java
      3. Using the Bulk Loader Tool
      4. Using the Remote Shell Tool
      5. Using the Remote API from a Script
    15. 13. Task Queues and Scheduled Tasks
      1. Task Queues
      2. Scheduled Tasks
    16. 14. The Django Web Application Framework
      1. Installing Django
      2. Creating a Django Project
      3. The Request Handler Script
      4. The Django App Engine Helper
      5. Creating a Django Application
      6. Using App Engine Models With Django
      7. Using Django Unit Tests and Fixtures
      8. Using Django Forms
    17. 15. Deploying and Managing Applications
      1. Uploading an Application
      2. Using Versions
      3. Managing Service Configuration
      4. Managing Indexes
      5. Browsing and Downloading Logs
      6. Inspecting the Datastore
      7. Application Settings
      8. Managing Developers
      9. Quotas and Billing
      10. Getting Help
    18. Index
    19. About the Author
    20. Colophon
    21. SPECIAL OFFER: Upgrade this ebook with O’Reilly
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Chapter 9. The Memory Cache

Durable data storage requires a storage medium that retains data through power loss and system restarts. Today’s medium of choice is the hard drive, a storage device composed of circular platters coated with magnetic material on which data is encoded. The platters spin at a constant rate while a sensor moves along the radius, reading and writing bits on the platters as they travel past. Reading or writing a specific piece of data requires a disk seek to position the sensor at the proper radius and wait for the platter to rotate until the desired data is underneath. Hard drives are astonishingly fast, all things considered, but for web applications, disk seeks can be costly. Fetching an entity from the datastore by key can take time on the order of tens of milliseconds.

Most high-performance web applications use a memory cache. A memory cache uses a volatile storage medium, usually the RAM of the cache machines, for very fast read and write access to values. A distributed memory cache provides scalable, consistent temporary storage for distributed systems, so many processes can access the same data. Because memory is volatile—it gets erased during an outage—the cache is not useful for long-term storage, or even short-term primary storage for important data. But it’s excellent as a secondary system for fast access to data also kept elsewhere, such as the datastore. It’s also sufficient as global high-speed memory for some uses.

The App Engine distributed ...

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