HTML5 Modern Web App and Google Cloud Endpoints (Part 2 Of 3)

Ido Green

Brad Abrams and I had a great time doing this session: “HTML5 and App Engine: The Epic Tag Team Take on Modern Web Apps at Scale” at Google I/O 2012.  Here is a little walkthrough on ‘how to built it’ from zero to hero in less then 60 minutes.

Pre-reqs

  1. Google Plugin for Eclipse
  2. Google API JavaScript client library
  3. Sign up for Cloud Endpoints

User Experiences demands are pushing modern web apps to a more distributed architecture.  A pattern many developers have used is using a MVC framework on the client and communicate to the server with REST. Google App Engine’s easy to build, easy to manage environment makes it ideal for REST APIs for Web backends.  At Google IO 2012, we made it much easier to build REST APIs on App Engine with Cloud Endpoints.

Cloud Endpoints enables you to build REST and RPC…

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MapReduce Patterns, Algorithms, and Use Cases

excellent reference

Highly Scalable Blog

In this article I digested a number of MapReduce patterns and algorithms to give a systematic view of the different techniques that can be found on the web or scientific articles. Several practical case studies are also provided. All descriptions and code snippets use the standard Hadoop’s MapReduce model with Mappers, Reduces, Combiners, Partitioners, and sorting. This framework is depicted in the figure below.

MapReduce Framework

Basic MapReduce Patterns

Counting and Summing

Problem Statement: There is a number of documents where each document is a set of terms. It is required to calculate a total number of occurrences of each term in all documents. Alternatively, it can be an arbitrary function of the terms. For instance, there is a log file where each record contains a response time and it is required to calculate an average response time.

Solution:

Let start with something really simple. The code snippet below shows Mapper that simply…

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NoSQL Data Modeling Techniques

Great post about NoSQL data modeling.

Highly Scalable Blog

NoSQL databases are often compared by various non-functional criteria, such as scalability, performance, and consistency. This aspect of NoSQL is well-studied both in practice and theory because specific non-functional properties are often the main justification for NoSQL usage and fundamental results on distributed systems like the CAP theorem apply well to NoSQL systems.  At the same time, NoSQL data modeling is not so well studied and lacks the systematic theory found in relational databases. In this article I provide a short comparison of NoSQL system families from the data modeling point of view and digest several common modeling techniques.

I would like to thank Daniel Kirkdorffer who reviewed the article and cleaned up the grammar.

To  explore data modeling techniques, we have to start with a more or less systematic view of NoSQL data models that preferably reveals trends and interconnections. The following figure depicts imaginary “evolution” of the major NoSQL…

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