Building Integrated Applications on Google's Cloud Technologies


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Presentation given by Google Developer Advocate Chris Schalk on building integrated applications with Google's Cloud Technologies.

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Building Integrated Applications on Google's Cloud Technologies

  1. 1. Christian SchalkGoogle Developer Integrated Applications onGoogles Cloud TechnologiesDevFest 2011Jakarta
  2. 2. Agenda● Introduction● App Engine Recap● Googles new Cloud Technologies ○ Google Cloud Storage ○ Prediction API ○ BigQuery ○ Google Cloud SQL● Summary Q&A
  3. 3. Introduction Google App Engine
  4. 4. Introduction Google App Engine Google BigQuery Google Google Cloud SQL Prediction API Google Cloud Storage
  5. 5. New Google Cloud Technologies ● Google Cloud Storage ○ Store your data in Googles cloud ● Prediction API ○ Googles machine learning tech in an API ● BigQuery ○ Hi-speed data analysis on a massive scale ● Cloud SQL ○ A relational database in the cloud
  6. 6. Google Cloud StorageStore your data in Googles cloud
  7. 7. What Is Google Cloud Storage? ● Store your data in Googles cloud ○ any format, any amount, any time ● You control access to your data ○ private, shared, or public ● Access via Google APIs or 3rd party tools/libraries
  8. 8. Sample Use Cases Static content hosting e.g. static html, images, music, video Backup and recovery e.g. personal data, business records Sharing e.g. share data with your customers Data storage for applications e.g. used as storage backend for Android, AppEngine, Cloud based apps Storage for Computation e.g. BigQuery, Prediction API
  9. 9. Google Cloud Storage Benefits High Performance and Scalability Backed by Google infrastructure Strong Security and Privacy Control access to your data Easy to Use Get started fast with Google & 3rd party tools
  10. 10. Google Cloud Storage Technical Details ● RESTful API ○ Verbs: GET, PUT, POST, HEAD, DELETE ○ Resources: identified by URI ○ Compatible with S3 ● Buckets ○ Flat containers ● Objects ○ Any type ○ Size: 100 GB / object ● Access Control for Google Accounts ○ For individuals and groups ● Two Ways to Authenticate Requests ○ Sign request using access keys ○ Web browser login
  11. 11. Early Google Cloud Storage Adopters and more...
  12. 12. Simple Google Cloud Storage Demos GS (Web) Manager GSutil
  13. 13. Google Prediction APIGoogles prediction engine in the cloud
  14. 14. Google Prediction API as a simple example Predicts outcomes based on learned patterns
  15. 15. Potentially endless number of applications... Customer Transaction Species Message Diagnostics Sentiment Risk Identification Routing Churn Legal Docket Suspicious Work Roster InappropriatePrediction Classification Activity Assignment ContentRecommend Political Uplift Email Career Products Bias Marketing Filtering Counselling ... and more ...
  16. 16. Prediction API CapabilitiesData ● Input Features: numeric or unstructured text ● Output: up to hundreds of discrete categoriesTraining ● Many machine learning techniques ● Automatically selected ● Performed asynchronouslyAccess from many platforms: ● Web app from Google App Engine ● Apps Script (e.g. from Google Spreadsheet) ● Desktop app
  17. 17. How does it work? "english" The quick brown fox jumped over theThe Prediction API lazy dog.finds relevant "english" To err is human, but to really foul thingsfeatures in the up you need a computer.sample data during "spanish" No hay mal que por bien no "spanish" La tercera es la vencida.The Prediction APIlater searches for ? To be or not to be, that is the question.those features ? La fe mueve montañas.during prediction.
  18. 18. Using the Prediction APIA simple three step process... (REST Calls) Upload your training data to 1. Upload Google Storage Build a model from your data 2. Train 3. Predict Make new predictions
  19. 19. Prediction API - key features ● Multi-category prediction ○ Tag entry with multiple labels ● Multiple Prediction Output ○ Finer grained prediction rankings based on multiple labels ● Mixed Inputs ○ Both numeric and text inputs are now supportedCan combine continuous output with mixed inputs
  20. 20. Prediction Demos ● Command line Demos ○ Training a model ○ Checking training status ○ Making predictions ● A complete Web application using the JavaScript API for Prediction
  21. 21. Google BigQueryInteractive analysis of large datasets in Googles cloud
  22. 22. Introducing Google BigQuery ● Googles large data adhoc analysis technology ○ Analyze massive amounts of data in seconds ● Simple SQL-like query language ● Flexible access ○ REST APIs, JSON-RPC, Google Apps Script
  23. 23. Many Use Cases ... Interactive Trends Spam Tools Detection Web Network Dashboards Optimization
  24. 24. Key Capabilities of BigQuery ● Scalable: Billions of rows ● Fast: Response in seconds ● Simple: Queries in SQL ● Web Service ○ REST ○ JSON-RPC ○ Google App Scripts
  25. 25. Using BigQueryAnother simple three step process... (REST Calls) Upload your raw data to 1. Upload Google Storage Import raw data into 2. Import BigQuery table 3. Query Perform SQL queries on table
  26. 26. Writing QueriesCompact subset of SQL ○ SELECT ... FROM ... WHERE ... GROUP BY ... ORDER BY ... LIMIT ...;Common functions ○ Math, String, Time, ...Statistical approximations ○ TOP ○ COUNT DISTINCT
  27. 27. BigQuery via RESTGET /bigquery/v1/tables/{table name}GET /bigquery/v1/query?q={query}Sample JSON Reply:{ "results": { "fields": { [ {"id":"COUNT(*)","type":"uint64"}, ... ] }, "rows": [ {"f":[{"v":"2949"}, ...]}, {"f":[{"v":"5387"}, ...]}, ... ] }}Also supports JSON-RPC
  28. 28. BigQuery Security and PrivacyStandard Google Authentication ● Client Login ● AuthSub ● OAuthHTTPS support ● protects your credentials ● protects your dataRelies on Google Storage to manage access
  29. 29. New!Whats New in BigQuery V2? ● A new REST API ● A new web user interface ● Support for JOIN statements ● Export table or query result to a CSV file in Google Cloud Storage ● Support for ACLs on collections of tables ● A new object architecture describing tables, groups of tables, and queries. This new architecture is described under Main Concepts below.
  30. 30. BigQuery Demo BigQuery Web Browser
  31. 31. Google Cloud SQLA relational database in the cloud
  32. 32. Google Cloud SQL ● Developer console ○ Easy to use ● Fully managed ● High availability ○ Synchronous replication to multiple data centers ● Integrated with Google App Engine ○ Java: JDBC, Python: DB-API ○ Use with High Replication Datastore ● MySQL Compatible ○ Import / export
  33. 33. Cloud SQL Demos! ● Cloud SQL Console ● SQL via JDBC Access ● SQL from PHP!
  34. 34. Recap ● Google App Engine ○ General purpose application development platform for the cloud ● Google Cloud Storage ○ High speed cloud data storage on Googles infrastructure ● Prediction API ○ Googles machine learning technology ● BigQuery ○ Interactive analysis of very large data sets ● Google SQL ○ A relational SQL database in the cloud
  35. 35. Further info available at: ● Google App Engine ○ ● Google Cloud Storage ○ ● Prediction API ○ ● BigQuery ○ ● Cloud SQL ○
  36. 36. Thank You! Christian Schalk Google Developer Advocate @cschalk (Follow me on G+ to get the slides!)