As a developer, I'm enthusiastic about cloud computing platforms because they let me spend more time writing web applications and services and less time dealing with scalability and deployment issues. In particular, Google App Engine offers automatic scaling and potential cost savings if you design the applications to run on it with the proper discipline. In this article, I provide an overview of the Google Apps Engine platform for developers.
• The App Engine datastore is best understood as an object database. • Each data record is an entity, represented in code as an object. • Each entity has a key that uniquely identifies the entity across all entities in the datastore. Getting started with the Cloud Datastore on PHP App Engine, Part II Introduction This is the second in a series of posts on using the Google Cloud Datastore on PHP App Engine.
Along the way, I offer some tips for writing scalable and efficient Google App Engine applications. Google App Engine Overview. The non-relational datastore for Google App Engine is based on Google's Bigtable system for storing and retrieving structured data. Bigtable can store petabyte-sized data collections, and Google uses Bigtable internally for web indexing and as data storage for user facing applications like Google Docs, Google Finance, etc. Bigtable is built on top of the distributed Google File System (GFS). As a developer using Google App Engine, you can also create very large datastores.
The datastore uses a structured data model, and the unit of storage for this model is called an entity. The datastore is hierarchical, which provides a way to cluster data or to manage 'contains' type relationships. The way this works is fairly simple: each entity has a (primary) key and an entity group.
For a top-level entity, the entity group will simply be the (primary) key. For example, if I have a kind of entity (think of this as being a type or a class) called a Magazine, I might have an entity representing an issue of this magazine identified with a key value of /Magazine:programingillustrated0101 and the entity group value would be the same as the key. I might have another entity that is an article of kind Article that might have an entity group of /Magazine:programingillustrated0101 and a key of /Magazine:programingillustrated0101/Article:10234518. Thus, you know that this article belongs to this issue of the magazine. Entity groups also define those entities that can be updated atomically in a transaction. There is no schema for entities; you might have two entities of kind Article that have different properties. As an example, a second article might have an additional property relatedarticle that the first article does not have.
The datastore also naturally supports multiple values of any property. The primary technique for making your Google App Engine applications efficient and scalable is to rely on the datastorerather than your application codeto sort and filter data. The next most important technique is effectively caching data for HTTP requests, which can be reused until the data becomes 'stale.' Java and Python Language Support.
Google is being run by Indians, managerially and technically. Even though Page and Schmidt are CEO and Executive Chairman of Big G, but still we can’t forget that it was Amit Singhal, an IIT Roorkey Graduate, who re-wrote the whole algorithm of Google Search Engine in 2000 which made Google the best in the industry.
Then, Nikesh Arora of BHU-IT is the Chief Business Manager; Vic Goundotra is the man behind the whole Google Plus and, many many more. Search FAMOUS INDIANS WORKING IN GOOGLE for more details. App Engine DataStore Entity from.
Platform Rajdeep Dua Anirudh Dewani Google Developer Relations. Defined Classification of Cloud Computing Players What is App Engine? Why App Engine? Application Lifecycle with App Engine Development using App Engine Deploying Applications Security Quota & Pricing What's next?. Saas Report, May 2008. Platform to build Web applications on the cloud Dynamic web server, with full support for common web technologies Automatic scaling and load balancing Transactional DataStore Model Integration with Google Accounts through APIs.