MongoDB Applied Design Patterns
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Synnopsis : Whether you re building a social media site or an internal-use enterprise application, this hands-on guide shows you the connection between MongoDB and the business problems it s designed to solve.
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Review of "MongoDB Applied Design Patterns" by Rick Copeland
Like this presentation? Why not share! However, in all the hype surrounding big data, many sites have launched their business on NoSQL databases without an understanding of the techniques necessary to effectively use the features of their chosen database. MongoDB Applied Design Patterns provides the much-needed connection between the features of MongoDB and the business problems that it is suited to solve. The book's focus on the practical aspects of the MongoDB implementation makes it an ideal purchase for developers charged with bringing MongoDB's scalability to bear on the particular problem you've been tasked to solve.
Whether you're building the newest and hottest social media web site or developing an internal-use-only enterprise business intelligence application, scaling your data model has never been more important. Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,, in stock items - you're bound to find what you want, at a price you'll love!
Books :: MongoDB Applied Design Patterns: Practical Use Cases with the Leading NoSQL Database
Please view eBay estimated delivery times at the top of the listing. We are unable to deliver faster than stated. Most often the question is whether to embed or to link, and what data should be normalized or denormalized. Copeland uses an extensive description of disk seek times to explain the motivations for embedding and denormalization, better than prior MongoDB schema-design materials have.
Many presentations, my own included, have claimed that you can migrate your schema lazily with MongoDB: your application can start writing data in a new format, and read data in both new and old formats, while a batch job slowly migrates old data. MongoDB Applied Design Patterns finally presents a complete example of lazy migration, including example code in Python for reading data in both formats while the migration is in progress. Without general-purpose transactions, MongoDB requires new techniques to guarantee that a series of changes is atomic: that is, to guarantee that in the long run your data either reflects all the changes or none of them.
The simple approach is to put all related data in one document and use update operators to modify all the data in one shot. If there's no way to restrict your atomic operation to one document, your next best bet is optimistic concurrency control: try to complete the operation, check if another process overwrote your changes, and if so retry them. There are a number of examples of this in the wild the MongoDB Manual , Dan Crosta , Scott Hernandez ; Copeland's contribution is unusually complete, with example code for handling every case that can arise.
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Part 2 of the book is much longer, and covers six kinds of application in depth, both conventional a social network and unusual a role-playing game. Here Copeland excels. Where he covers well-tread ground his designs are more detailed and better thought out than prior authors', and where he innovates he chooses interesting problems to solve.