Book Image

Mastering RethinkDB

By : Shaikh
Book Image

Mastering RethinkDB

By: Shaikh

Overview of this book

RethinkDB has a lot of cool things to be excited about: ReQL (its readable,highly-functional syntax), cluster management, primitives for 21st century applications, and change-feeds. This book starts with a brief overview of the RethinkDB architecture and data modeling, and coverage of the advanced ReQL queries to work with JSON documents. Then, you will quickly jump to implementing these concepts in real-world scenarios, by building real-time applications on polling, data synchronization, share market, and the geospatial domain using RethinkDB and Node.js. You will also see how to tweak RethinkDB's capabilities to ensure faster data processing by exploring the sharding and replication techniques in depth. Then, we will take you through the more advanced administration tasks as well as show you the various deployment techniques using PaaS, Docker, and Compose. By the time you have finished reading this book, you would have taken your knowledge of RethinkDB to the next level, and will be able to use the concepts in RethinkDB to develop efficient, real-time applications with ease.
Table of Contents (16 chapters)
Mastering RethinkDB
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface

ReQL queries are executed on a server


Queries are formed in the client but will be sent to server for execution when you run them. This makes sure there is no network round trip and bandwidth allocation. This provides efficiency in query execution.

We also mentioned in Chapter 1, The RethinkDB Architecture and Data Model, that RethinkDB executes queries in a lazy manner. It only fetches the data asked and required for the query to complete. Here is an example:

r.db('test').table('users').limit(5) 

To perform this query, RethinkDB will look for only the five documents only in the users table. It will perform enough operations to perform the data collection requested in the query. This avoids extra computation costs and CPU cycles.

To provide the highest level of efficiency, RethinkDB automatically parallelizes the query as much as possible across the server, CPU cores, or even data centers. RethinkDB automatically processes the complex queries into stages, parallelizes them across clusters...