Web Development

New PDF release: Building Node Applications with MongoDB and Backbone

By Mike Wilson

Build an software from backend to browser with Node.js, and kick open the doorways to real-time occasion programming. With this hands-on publication, you’ll methods to create a social community software just like LinkedIn and fb, yet with a real-time twist. And you’ll construct it with only one programming language: JavaScript.

If you’re an skilled net developer unusual with JavaScript, the book’s first part introduces you to the project’s middle applied sciences: Node.js, Backbone.js, and the MongoDB information shop. You’ll then release into the project—a hugely responsive, hugely scalable application—guided by way of transparent causes and plenty of code examples.
• know about key modules in Node.js for construction real-time apps
• Use the Backbone.js framework to write down fresh browser code, and continue greater info integration with MongoDB
• constitution venture records as a origin for code that may arrive later
• Create consumer bills and how one can safe the information
• Use Backbone.js templates to construct the application’s UIs, and combine entry keep an eye on with Node.js
• increase a touch record to assist clients hyperlink to and music different bills
• Use Socket.io to create real-time chat performance
• expand your UIs to offer clients up to date details

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Read Online or Download Building Node Applications with MongoDB and Backbone PDF

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Additional resources for Building Node Applications with MongoDB and Backbone

Sample text

This is a useful safety valve to prevent you from accidentally trashing an entire collection because of a poorly thought out wildcard search pattern. info Example 4-4 demonstrates another useful operator: the $push command. This com‐ mand allows you to add a new item to the end of an array without modifying anything else in your document. As shown here, the keyword developer is added to the “50 Tips and Tricks for MongoDB Developers” book. Example 4-4. find(); "_id" : ObjectId("5063d1d89e302eaf24b259a0"), "author" : "Jamie Munro", "title" : "20 Recipes for Programming PhoneGap", "published" : ISODate("2012-04-03T07:00:00Z") } { "_id" : ObjectId("5063d6909e302eaf24b259a1"), "author" : "Kristina Chodorow", "keywords" : [ "design", "implementation", "optimization", "developer" ], "published" : ISODate("2011-05-06T07:00:00Z"), "title" : "50 Tips and Tricks for MongoDB Developers" } Querying Querying in MongoDB is analogous to SELECT in SQL.

Because Node exposes the nuts and bolts of the network to the pro‐ grammer, it is very straightforward to create a fairly feature-rich application in very few lines of code. Example 5-2 creates a functional and capable application in a short amount of code. Despite its small size, this program handles routing for incoming HTTP requests, pro‐ vides a view engine to render server-side views into browser-friendly HTML5 markup, and provides downloadable access to static file resources on the local filesystem.

If done properly, it can mean the difference between queries that take minutes versus queries that take seconds or less. MapReduce MapReduce is used to batch process huge amounts of data often across clusters of da‐ tabase servers. If you were to compare MongoDB to a traditional SQL-based server, MapReduce would fit in the space where you would normally use GROUP BY to collect aggregate results. A MapReduce operation involves two phases: the map phase, which plucks out the relevant data into key/value pairs for aggregation, and the reduce phase, which collects all of the keys and performs math on their values.

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