The document discusses Google App Engine, a platform as a service (PaaS) that allows developers to focus on development rather than operations. It presents Google App Engine as having a "virtual raised floor" with the IDE above the floor and website/deployment system below. It provides an overview of Google App Engine's history and supported languages/data stores. It also summarizes code samples for a guestbook application and MapReduce workflow on Google App Engine.

1. Google App Engine
(Platform as a Service)
Boston Cloud Services Meetup
J Singh
January 14, 2014

2. PaaS Goal: Focus on Development, not Ops
• Virtual Raised Floor
– IDE above the floor
– Website for visibility
and control below
the floor
– Deployment System
( Tile Lifter)
© DataThinks 2013-14
2
2

3. IDE Above the Floor
• The programmer’s development environment
– Presentation layer: HTML, CSS, JavaScript
– Control layer: Web Server code
• Access to external APIs
– Data layer: Data Model
• Indexing advice
– Optionally, analytics
© DataThinks 2013-14
3
3

4. Ops below the floor
• Made visible through a web interface
–
–
–
–
–
–
Operating System
File System
User Authentication
Utilities (cron, etc.)
Logs
Database maintenance, backups, etc.
© DataThinks 2013-14
4
4

5. Deployment System
• Methods for continuous deployment
– Upload
– Version management
© DataThinks 2013-14
5
5

6. Google App Engine
• Strategic Technology Offering for Server-side applications
– Vehicle for introducing internal technology to the outside
developer community
– Not to be confused with Google Apps
– Frequent criticism:
• Single-source
• Except for AppScale (GAE code that runs on Amazon)
© DataThinks 2013-14
6
6

7. Google App Engine History
• Introduced in 2008
– Python, Google DataStore
• Now
– Languages
• Python, Go, PHP, Java
– And languages that compile to JVM byte codes
– Data Stores
• Google DataStore (NoSQL), CloudStore (Cloud intf to MySQL)
– Map Reduce
© DataThinks 2013-14
7
7

8. Sources
• Getting Started Instructions: (http://goo.gl/Wc4A9R)
• Map Reduce Instructions: (http://goo.gl/gzmj7T)
• Code: (http://goo.gl/SqmCKk) (a Github repository)
– Commit 0e24b6ad7: Guestbook application
– Commit 68f929415: Fetching from a Gutenberg.org URL
• Gets “Permission Denied” from gutenberg.org
• Change to read & parse pages from Wikipedia or another
source
– Commit 1740fedc6: Map Reduce changes
© DataThinks 2013-14
8
8

9. Guestbook Application
• Application Demo
(http://goo.gl/ItxjME)
• Code walk through:
– Dispatching
– Code
– Templates
– Write something in the
guestbook,
– Log in, write again,
– …
• Change page text
• Console walk through:
• Delete some guestbook
entries
– Dashboard
– DataStore
– Logs
© DataThinks 2013-14
9
9

10. Map Reduce Flow
© DataThinks 2013-14
10
10

11. Map Reduce Pipelines
• Map Reduce is rarely a singular operation
• Multiple Map Reduce operations are pipelined together
– Fan out, synchronization semantics
© DataThinks 2013-14
11
11

12. Map Reduce Application
• Application Demo
(http://goo.gl/KUPDc1)
• Code walk through:
– WordCountPipeline
– word_count_map
– word_count_reduce
• Where are the results?
© DataThinks 2013-14
12
12

13. Thank you
• J Singh
– Principal, DataThinks
• j.singh@datathinks.org
– Adj. Prof, WPI
© DataThinks 2013-14
13
13