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Home > Data > Database Administration > Mastering RethinkDB
Mastering RethinkDB
Mastering RethinkDB

Mastering RethinkDB: Master the skills of building real-time apps dramatically easier with open source, scalable database - RethinkDB

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Mastering RethinkDB

Chapter 2. RethinkDB Query Language

ReQL means RethinkDB query language. It offers a powerful and easy way to perform operations on JSON documents. It is one of the most important parts of the RethinkDB architecture. It is built on three important principles: embedding ReQL in a programming language, ReQL queries being chainable, and ReQL queries being executed on the server.

Here is a list of topics we are going to cover, along with the mentioned principles:

  • Performing conditional queries
  • ReQL queries are chainable
  • ReQL queries are executed on a server
  • Traversing over nested fields
  • Performing string operations
  • Performing MapReduce operations
  • Calling HTTP APIs using ReQL
  • Handling binary objects
  • Performing JOINS
  • Accessing changefeed (real-time feed) in RethinkDB
  • Performing geolocation operations
  • Performing administrative operations

Let us look over each one of them.

Embedding ReQL in a programming language

RethinkDB provides client drivers for various programming languages. To explain, I am going to consider Node.js, and the steps are as follows:

  1. You can start the ReQL exploration journey by connecting to the database.
  2. Install the RethinkDB client module and make sure you have the RethinkDB server ready and running, listening to the default port.
  3. Make sure you have done npm install rethinkdb before running the following code:
          var rethinkdb = require('rethinkdb'); 
      var connection = null; 
      rethinkdb.connect({host : 'localhost', port :
                         28015},function(err,conn) { 
      if(err) {  
      throw new Error('Connection error');  
       } else { 
      connection = conn; 
       } 
       });

The preceding simple code snippet written in Node.js is importing the rethinkdb module and connecting to the RethinkDB server on the default port. It returns the callback function with error and the...

ReQL queries are chainable

Almost all ReQL queries are chainable. You can chain ReQL queries using the dot operator, just like you do with pipe in Unix. Data flows from left to right and data from one command is passed to the next one until the query gets executed. You can chain queries until your query is done.

Just like we performed some queries on the previous section, we chained the get() function with update() or delete() to perform the query.

Here is an example:

rethinkdb.table('users').delete(); 
rethinkdb.table('users').get('<<id>>').update({id : 10}); 
rethinkdb.db('test').table('users').distinct().count();

This way of design provides a natural way of reading and understanding queries. It's easy to learn, modify, and read.

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...

Performing conditional queries

ReQL supports conditional queries using subqueries, expressions, and the lambda function. In this section, we will look at each one of them using sample code written in Node.js.

In order to perform these queries, I have populated our users table in the test database with some documents. Here is the query executed from the RethinkDB web administrative screen:

r.db('test').table('users').insert([{ 
name : "John", 
age : 24 
}, { 
name : "Mary", 
age : 32 
},{ 
name : "Michael", 
age : 28 
}])

Note

In the web administrative screen, you do not need to provide the run function with a connection; it automatically appends and executes the query on the server.

Let us run a query to find out documents with an age greater than 30 years. We are going to execute the following code after getting a connection to the database, the same as we did in the former section:

rethinkdb.table('users').filter(function (user...

Embedding ReQL in a programming language

RethinkDB provides client drivers for various programming languages. To explain, I am going to consider Node.js, and the steps are as follows:

  1. You can start the ReQL exploration journey by connecting to the database.

  2. Install the RethinkDB client module and make sure you have the RethinkDB server ready and running, listening to the default port.

  3. Make sure you have done npm install rethinkdb before running the following code:

          var rethinkdb = require('rethinkdb'); 
      var connection = null; 
      rethinkdb.connect({host : 'localhost', port :
                         28015},function(err,conn) { 
      if(err) {  
      throw new Error('Connection error');  
       } else { 
      connection = conn; 
       } 
       });

The preceding simple code snippet written in Node.js is importing the rethinkdb module and connecting to the RethinkDB server on the default port. It returns the callback function...

ReQL queries are chainable

Almost all ReQL queries are chainable. You can chain ReQL queries using the dot operator, just like you do with pipe in Unix. Data flows from left to right and data from one command is passed to the next one until the query gets executed. You can chain queries until your query is done.

Just like we performed some queries on the previous section, we chained the get() function with update() or delete() to perform the query.

Here is an example:

rethinkdb.table('users').delete(); 
rethinkdb.table('users').get('<<id>>').update({id : 10}); 
rethinkdb.db('test').table('users').distinct().count();

This way of design provides a natural way of reading and understanding queries. It's easy to learn, modify, and read.

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...

Performing conditional queries

ReQL supports conditional queries using subqueries, expressions, and the lambda function. In this section, we will look at each one of them using sample code written in Node.js.

In order to perform these queries, I have populated our users table in the test database with some documents. Here is the query executed from the RethinkDB web administrative screen:

r.db('test').table('users').insert([{ 
name : "John", 
age : 24 
}, { 
name : "Mary", 
age : 32 
},{ 
name : "Michael", 
age : 28 
}])

Note

In the web administrative screen, you do not need to provide the run function with a connection; it automatically appends and executes the query on the server.

Let us run a query to find out documents with an age greater than 30 years. We are going to execute the following code after getting a connection to the database, the same as we did in the former section:

rethinkdb.table('users').filter(function (user) {  
return...

Performing string operations

ReQL provides the following functions to manipulate and search strings:

  • Match() takes a string or a regular expression as an input and performs a search over the field. If it matches, it returns the data in the cursor, which we can loop over to retrieve the actual data.

  • For example, we have to find all the users whose name starts with J. Here is the query for the same:

      rethinkdb.table("users").filter(function(user) { 
      return user("name").match("^J"); 
      }).run(connection,function(err,cursor) { 
      if(err) { 
      throw new Error(err); 
        } 
       cursor.toArray(function(err,data) { 
       console.log(data); 
        }); 
      });

  • Here we are first performing a filter, and inside it, we put our match() condition. The filter gives every document to the match() function and it appends it to the cursor. Upon running, you should be able to view the users with names starting with J.

  • split...

Performing MapReduce operations

MapReduce is the programming model to perform operations (mainly aggregation) on distributed sets of data across various clusters in different servers. This concept was coined by Google and was used in the Google file system initially and later was adopted by the open source Hadoop project.

MapReduce works by processing the data on each server and then combine it together to form a result set. It actually divides into two operations namely Map and Reduce.

  • Map: This performs the transformation of the elements in the group or individual sequence

  • Reduce: This performs the aggregation and combines the results from Map into a meaningful result set

In RethinkDB, MapReduce queries operate in three steps as follows:

  • Group operation: To process the data into groups. This step is optional

  • Map operation: To transform the data or group of data into a sequence

  • Reduce operation: To aggregate the sequence data to form a resultset

So mainly it is a Group MapReduce (GMR) operation...

Calling HTTP APIs using ReQL

RethinkDB provides support to call an external API that returns data in a JSON object, which most of the large API provider do. You can call HTTP API directly from your database hence no need of writing piece of code to just call an API and then dump into database. RethinkDB also handles it asynchronously so performance won't be affected if the API takes a longer time.

Let us try one basic API call before moving ahead with storing those in our table. We all know and use OMDb for movies review. There is a website called http://omdbapi.com/ that provides APIs to find out the movie information present in the OMDB database. Let's call one with the following code to fetch information about the Avengers movie and see how it goes:

rethinkdb.http("http://www.omdbapi.com/?t=avengers&y=2015&plot=short&r=json").run(connection,function(err,data) { 
if(err) { 
throw new Error(err); 
  } 
console.log(data); 
});

You should be receiving...

Handling binary objects

As we have mentioned in this chapter about RethinkDB binary object support, let's look over how to use it using ReQL. The syntax to store binary objects differs from client to client. In Node.js it uses buffers to convert the stream into binary and we can use RethinkDB to insert that in a table.

Let us take an example from the preceding document. There is a key called Poster, which is the official poster of the movie in a JPEG image format. We can store the image directly in RethinkDB in a binary format.

Consider the following code:

rethinkdb.http("http://www.omdbapi.com/?t=avengers&y=2015&plot=short&r=json").run(connection,function(err,data) { 
if(err) { 
throw new Error(err); 
  } 
rethinkdb.table("movies").insert({ 
movieName :data.Title, 
posterImage :rethinkdb.http(data.Poster, {resultFormat : 'binary'}) 
  }).run(connection,function(err,data) { 
if(err) { 
throw new Error(err); 
    } 
console.log...

Performing JOINS

JOINS are one of the features of NoSQL databases. RethinkDB provides the ReQL functions to perform various types of JOINS, such as inner, outer, and so on. Please refer to Chapter 1, The RethinkDB Architecture and Data Model, to study this more in detail.

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Key benefits

  • Master the powerful ReQL queries to manipulate your JSON data,
  • Learn how to develop scalable, real-time web applications using RethinkDB and Node.js and deploy them for production,
  • A detailed, step-by-step guide to help you master the concepts of RethinkDB programming with ease

Description

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.

Who is this book for?

This book caters to all the real-time application developers looking forward to master their skills using RethinkDB. A basic understanding of RethinkDB and Node.js is essential to get the most out of this book.

What you will learn

  • Master the web-based management console for data-center configuration (sharding, replication, and more), database monitoring, and testing queries.
  • Run queries using the ReQL language
  • Perform Geospatial queries (such as finding all the documents with locations within 5km of a given point).
  • Deal with time series data, especially across various times zones.
  • Extending the functionality of RethinkDB and integrate it with third party libraries such as ElasticSearch to enhance our search
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Publication date : Dec 16, 2016
Length: 330 pages
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ISBN-13 : 9781786461070
Category :
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Length: 330 pages
Edition : 1st
Language : English
ISBN-13 : 9781786461070
Category :
Data
Concepts :
Database Administration
Tools :
RethinkDB

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Table of Contents

10 Chapters
1. The RethinkDB Architecture and Data Model Chevron down icon Chevron up icon
1. The RethinkDB Architecture and Data Model
RethinkDB architectural components
Query execution in RethinkDB
Filesystem and data storage
Sharding and replication
Automatic failover handling in RethinkDB
About voting replicas
The RethinkDB data model
Constraints and limitation in RethinkDB
Summary
2. RethinkDB Query Language Chevron down icon Chevron up icon
2. RethinkDB Query Language
Embedding ReQL in a programming language
ReQL queries are chainable
ReQL queries are executed on a server
Performing conditional queries
Performing string operations
Performing MapReduce operations
Calling HTTP APIs using ReQL
Handling binary objects
Performing JOINS
Accessing changefeed (real-time feed) in RethinkDB
Performing geolocation operations
Performing administrative operations
Summary
3. Data Exploration Using RethinkDB Chevron down icon Chevron up icon
3. Data Exploration Using RethinkDB
Generating mock data
Executing data exploration use cases
Summary
4. Performance Tuning in RethinkDB Chevron down icon Chevron up icon
4. Performance Tuning in RethinkDB
Clustering
Creating and handling a RethinkDB cluster
Securing our RethinkDB cluster
Executing ReQL queries in a cluster
Performing replication of tables in RethinkDB
Sharding the table to scale the database
Running a RethinkDB proxy node
Optimizing query performance
Summary
5. Administration and Troubleshooting Tasks in RethinkDB Chevron down icon Chevron up icon
5. Administration and Troubleshooting Tasks in RethinkDB
Understanding access controls and permission in RethinkDB
Failover handling in RethinkDB
Performing a manual and automatic backup in RethinkDB
Data import and export in RethinkDB
Crash recovery in RethinkDB
Using third-party tools
Summary
6. RethinkDB Deployment Chevron down icon Chevron up icon
6. RethinkDB Deployment
Deploying RethinkDB using PaaS services
Deploying RethinkDB using Docker
Deploying RethinkDB on a standalone server
Summary
7. Extending RethinkDB Chevron down icon Chevron up icon
7. Extending RethinkDB
Integrating RethinkDB with ElasticSearch
Integrating RethinkDB with RabbitMQ
Understanding the RethinkDB protocol
Third-party libraries and tools
Summary
8. Full Stack Development with RethinkDB Chevron down icon Chevron up icon
8. Full Stack Development with RethinkDB
Project structure
Data modeling for our application
Creating a Node.js server and routes
Integrating RethinkDB with Node.js
Integrating AngularJS in the frontend
Socket.io integration for message broadcasting
Summary
9. Polyglot Persistence Using RethinkDB Chevron down icon Chevron up icon
9. Polyglot Persistence Using RethinkDB
Introducing Polyglot Persistence
Using the RethinkDB changefeed as a Polyglot agent
Developing a proof-of-concept application with MongoDB and MySQL
Developing the Polyglot agent
Developing event consumers
Running the app
Further improvements
Summary
10. Using RethinkDB and Horizon Chevron down icon Chevron up icon
10. Using RethinkDB and Horizon
Workings of Horizon
Installing and configuring Horizon
Developing a simple web application using Horizon
Horizon user management
Summary

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Causal Inference and Discovery in Python
Causal Inference and Discovery in Python
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May 2023 456 pages
Full star icon 4.5 (49)
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About the author

Profile icon Shaikh
Shaikh
Shahid Shaikh is an engineer, published author, and a blogger. He has written tons of tutorials on Node.js and various databases on his blog. He is a believer in open source and almost all his source code is on GitHub. He has also developed and launched a SaaS product called Spark to handle content sharing automation. Currently, he is building a next-generation email marketing tool called Hashmailer.
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Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

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Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

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Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela