google developer days brazil 2009 - java appengine

Google App Engine Now Serving Java Chris Schalk June 29, 2009

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Goals

• Help you understand... – what App Engine is.

– what App Engine is not.

– where App Engine preserves programming models.

– where App Engine changes programming models.

• Demonstrate that App Engine really is fast and free to get started.

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Overview

• Google App Engine

• Java on App Engine

• The App Engine Datastore

• Demo

• Questions

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What Is Google App Engine?

• A cloud-computing platform

• Run your web apps on Google’s infrastructure

• We provide the container and services (PaaS) – Hardware, connectivity

– Operating system

–  JVM

– Servlet container

– Software services

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Key Features

• No need to install or maintain your own stack

• We scale for you

• Use Google’s scalable services via standard APIs

• Charge only for actual usage – Always free to get started

• Built-in application management console

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App Engine Architecture

App Engine Front End

App Engine Front End

App Engine Front End

Incoming Requests

AppServer AppServer AppServer

Load Balancer

AppServer

API Layer

Other Google Infrastructure

- Bigtable

- Google Accounts

- Memcache

- Image manipulation

App App App

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When To Use Google App Engine

• Targeting web applications – Serve HTTP requests, limited to 30 seconds

– No long-running background processes

– No server push

• Sandboxed environment – No threads

– Read-only file system

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Java Support

• Servlets

• Software services

• Sandboxing

• DevAppServer

• Deployment

• Tooling

Demo! Java App Engine Basics

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Servlet API

• Full Servlet 2.5 Container – HTTP Session

–  JSP

• Uses Jetty and Jasper

– Powered by Google’s HTTP stack

– No Jetty-specific features

– Subject to change

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Software Services

Authentication Servlet API Google Accounts

Datastore JPA, JDO Bigtable

Caching javax.cache memcacheg

E-mail javax.mail Gmail gateway

URLFetch URLConnection Caching HTTP proxy

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Sandboxing

• What do we do? – Restrict JVM permissions

– WhiteList classes

• Why is it necessary? – Clustering - JVMs come and go

– Protect applications from one another

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Sandboxing Restrictions

Threads Async API (coming soon)

Direct network connections URLConnection

Direct file system writes Memory, memcache, datastore

Java2D Images API

Software rendering

Native code Pure Java libraries

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Flexible Sandboxing

• JVM Permissions often too coarse

• Reflection

– Access private fields, call private methods

• Class Loading

– Custom Class Loaders

– Dynamic bytecode

• Alternate JVM languages

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DevAppServer

• Emulates the production environment

• Customized Jetty server

• Local implementation of services –  LRU memcache

– Disk-backed datastore

– HttpClient-backed URLFetch

• Some sandbox restrictions difficult to emulate

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Deployment

• Your app lives at –  <app_id>.appspot.com, or

– Custom domain with Google Apps for your Domain

• Command line and IDE tools

• Application

• Datastore Indexes

• Cron Jobs

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Quotas and Billing

CPU 6.5 hours/day $0.10/hour

Bandwidth In 1GByte/day $0.10/GByte

Bandwidth Out 1GByte/day $0.12/GByte

Stored Data 1 GB $0.005/GB-day

Emails sent 2000/day to users 5000/day to admins $0.0001/email

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Tooling

• SDK Tools API – Command-line tools, Ant, and IDE plugins

• Provides – Deployment

– DevAppServer

– WhiteList for compile-time checks

– XML validation

• Google Eclipse Plugin

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The Datastore Is...

• Distributed

• Scalable

• Transactional

• Natively Partitioned

• Hierarchical

• Schema-less

• Based on Bigtable

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The Datastore Is Not...

• A relational database

• A SQL engine

• Just Bigtable

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Simplifying Storage

• Simplify development of apps

• Simplify management of apps

• App Engine services build on Google’s strengths

• Scale always matters – Request volume

– Data volume

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Datastore Storage Model

• Basic unit of storage is an Entity consisting of – Kind (table)

– Key (pk)

– Entity Group (top level ancestor) •  Has locking implications

–  0..N typed Properties (columns)

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Interesting Datastore Modeling Features

•  Ancestor

•  Multi-value properties

•  Variable properties

•  Heterogenous property types

Kind Person

Entity Group /Person:Ethel

Key /Person:Ethel

Age Int64: 30

Hobbies String: Tennis

Kind Person

Entity Group /Person:Ethel

Key /Person:Ethel/Person:Jane

Age Double: 3.5

Pets Key:/Turtle:Sam Key:/Dog:Ernie

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/Person:Ethel/Person:Jane

/Person:Ethel

/Person:Max

Transaction

Datastore Transactions

• Transactions apply to a single Entity Group – Global transactions are feasible

• get(), put(), delete() are transactional

• Queries are not transactional (yet)

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Datastore Queries

• Every query must be supported by an index – Built-in or user-defined

• Filters – Equality, inequality, intersection, ancestor

– Union, IN not supported (yet)

–  Joins not supported (unlikely, but never say never)

• Sorting

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Standards-based Persistence

• JDO or JPA (your choice) – Established apis and existing tooling

– Easier porting

– Mappable (mostly) to the datastore

– Soft schemas

• DataNucleus App Engine plugin

• Why not a JDBC driver instead?

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Kind Pet

Entity Group /Person:Ethel

Key /Person:Ethel/Pet:Sam

Transparent Entity Group Management

• Entity Group layout is important – Write throughput

– Atomicity of updates

• Ownership implies co-location within Entity Group

Demo! Building Apps with Java App Engine

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Coming Soon

• Task queues

• Full text search

•  Incoming email

• XMPP

• Large file storage and retrieval

• Datastore export tools

Q & A