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Getting Started with RethinkDB

Getting Started with RethinkDB

By : Tiepolo
4 (1)
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Getting Started with RethinkDB

Getting Started with RethinkDB

4 (1)
By: Tiepolo

Overview of this book

RethinkDB is a high-performance document-oriented database with a unique set of features. This increasingly popular NoSQL database is used to develop real-time web applications and, together with Node.js, it can be used to easily deploy them to the cloud with very little difficulty. Getting Started with RethinkDB is designed to get you working with RethinkDB as quickly as possible. Starting with the installation and configuration process, you will learn how to start importing data into the database and run simple queries using the intuitive ReQL query language. After successfully running a few simple queries, you will be introduced to other topics such as clustering and sharding. You will get to know how to set up a cluster of RethinkDB nodes and spread database load across multiple machines. We will then move on to advanced queries and optimization techniques. You will discover how to work with RethinkDB from a Node.js environment and find out all about deployment techniques. Finally, we’ll finish by working on a fully-fledged example that uses the Node.js framework and advanced features such as Changefeeds to develop a real-time web application.
Table of Contents (9 chapters)
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8
Index

Updating data

Once a document is stored in a RethinkDB table, it can be changed using the update() command. This command accepts a JSON document or ReQL expression as input and returns the number of updated documents.

Updating existing attributes

Updating a document can alter one or more attributes already present within the document itself, or can add a new attribute. Let's pretend we made a mistake inserting Amy's year of birth and we want to change the value from 1998 to 1997; we can update the related document using the following query:

r.table('people').get('f1664276-1aad-4998-8240-410a82883115').update({"yearOfBirth": 1997})

First, we get the correct document using its primary key. Then we call the update() command, passing it a JSON document that contains the changes. In this case, the change is as follows:

({"yearOfBirth": 1997}

If we now query the database searching for Amy's document, we can see that year of birth has, in fact,...

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