Data Modeling for MongoDB Building Well-Designed and by Steve Hoberman

By Steve Hoberman

Congratulations! You accomplished the MongoDB software in the given tight time-frame and there's a occasion to have a good time your application's free up into creation. even though everyone is congratulating you on the party, you feel a few uneasiness within. to accomplish the venture on time required creating a lot of assumptions in regards to the facts, comparable to what phrases intended and the way calculations are derived. additionally, the negative documentation concerning the software may be of constrained use to the aid staff, and never investigating the entire inherent principles within the information might finally bring about poorly-performing constructions within the not-so-distant destiny.

Now, what when you had a time desktop and will return and skim this ebook. you'll research that even NoSQL databases like MongoDB require a few point of information modeling.
Data modeling is the method of studying concerning the info, and despite expertise, this technique needs to be played for a profitable application. you will examine the price of conceptual, logical, and actual information modeling and the way each one level raises our wisdom of the information and decreases assumptions and bad layout decisions.

Read this ebook to profit the right way to do info modeling for MongoDB functions, and attain those 5 objectives:

  1. Understand how info modeling contributes to the method of studying concerning the facts, and is, for that reason, a required strategy, even if the ensuing database isn't really relational. that's, NoSQL doesn't suggest NoDataModeling!
  2. Know how NoSQL databases range from conventional relational databases, and the place MongoDB fits.
  3. Explore every one MongoDB item and understand how each one compares to their info modeling and conventional relational database opposite numbers, and examine the fundamentals of including, querying, updating, and deleting information in MongoDB.
  4. Practice a streamlined, template-driven method of acting conceptual, logical, and actual information modeling. realize that info modeling doesn't consistently need to result in conventional info models!
  5. Distinguish top-down from bottom-up improvement methods and whole a top-down case research which ties all the modeling suggestions together.

This e-book is written for an individual who's operating with, or could be operating with MongoDB, together with enterprise analysts, information modelers, database directors, builders, venture managers, and knowledge scientists. There are 3 sections:

  • In part I, Getting Started, we'll show the ability of knowledge modeling and the tight connections to facts versions that exist whilst designing any form of database (Chapter 1), evaluate NoSQL with conventional relational databases and the place MongoDB suits (Chapter 2), discover each one MongoDB item and understand how every one compares to their info modeling and conventional relational database opposite numbers (Chapter 3), and clarify the fundamentals of including, querying, updating, and deleting information in MongoDB (Chapter 4).
  • In part II, Levels of Granularity, we hide Conceptual information Modeling (Chapter 5), Logical info Modeling (Chapter 6), and actual information Modeling (Chapter 7). observe the "ing" on the finish of every of those chapters. We specialize in the method of creating every one of those versions, that's the place we achieve crucial enterprise knowledge.
  • In part III, Case Study, we'll clarify either best down and backside up improvement ways and plow through a most sensible down case learn the place we begin with enterprise standards and finish with the MongoDB database. this situation research will tie jointly all the concepts within the earlier seven chapters.

Nike Senior info Architect Ryan Smith wrote the foreword. Key issues are incorporated on the finish of every bankruptcy in order to make stronger recommendations. furthermore, this booklet is loaded with hands-on workouts, besides their solutions supplied in App A. App B includes all the book’s references and App C the

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Additional resources for Data Modeling for MongoDB Building Well-Designed and Supportable MongoDB Databases

Sample text

Com. Note that the MongoDB shell is a full-featured JavaScript interpreter. You can therefore run any JavaScript commands such as: > y = 100 100 > y / 20 5 You can also use all of the standard JavaScript libraries and functions. When your MongoDB statement spans more than one line, press to go to the next line. The MongoDB client knows whether the statement is complete or not, and if the statement is not complete, the client will allow you to continue writing it on the next line. Pressing three times will cancel the statement and get you back to the > prompt.

85, orderTypeCode : “02”, orderTypeDescription : “Universities Sales”, orderStatusCode : “D”, orderStatusDescription : “Delivered”, orderLine : [ { productID : “9781935504375”, orderLineQuantity : 1 }, { productID : “9781935504511”, orderLineQuantity : 3 }, { productID : “9781935504535”, orderLineQuantity : 2 }]} In this example the Order document contains one order with three order lines. A document begins and ends with the squiggly braces { }, and the fields within the document are separated by commas.

Having a zero in the cardinality makes us use optional-sounding words such as may or can when reading the relationship. Without the zero, we use mandatory-sounding terms such as must or have to. So instead of being redundant and saying: Each Author may write zero, one or many Titles. We take out the word zero because it is expressed using the word may, which implies the zero: Each Author may write one or many Titles. Every relationship has a parent and a child. The parent entity appears on the one side of the relationship, and the child appears on the many side of the relationship.

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