Book Image

MongoDB Administrator???s Guide

By : Cyrus Dasadia
Book Image

MongoDB Administrator???s Guide

By: Cyrus Dasadia

Overview of this book

MongoDB is a high-performance and feature-rich NoSQL database that forms the backbone of the systems that power many different organizations. Packed with many features that have become essential for many different types of software professional and incredibly easy to use, this cookbook contains more than 100 recipes to address the everyday challenges of working with MongoDB. Starting with database configuration, you will understand the indexing aspects of MongoDB. The book also includes practical recipes on how you can optimize your database query performance, perform diagnostics, and query debugging. You will also learn how to implement the core administration tasks required for high-availability and scalability, achieved through replica sets and sharding, respectively. You will also implement server security concepts such as authentication, user management, role-based access models, and TLS configuration. You will also learn how to back up and recover your database efficiently and monitor server performance. By the end of this book, you will have all the information you need—along with tips, tricks, and best practices—to implement a high-performance MongoDB solution.
Table of Contents (17 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Creating an index


In this recipe, we will be using a fairly large dataset and add it into MongoDB. Then we will examine how a query executes in this dataset with and without an index.

Getting ready

Assuming that you are already running a MongoDB server, we will be importing a dataset of around 100,000 records available in the form of a CSV file called chapter_2_mock_data.csv. You can download this file from the Packt website.

  1. Import the sample data to the MongoDB server:
$mongoimport --headerline --ignoreBlanks --type=csv -d mydb -c mockdata -h localhost chapter_2_mock_data.csv

You should see output like this:

2017-06-18T08:25:08.444+0530    connected to: localhost
2017-06-18T08:25:09.498+0530 imported 100000 documents
  1. Connect to the MongoDB instance and open a mongo shell:
mongo localhost:27017
  1. Check that the documents are in the right place:
use mydb
db.mockdata.count()

You should see the following result:

105000
  1. Let's fetch a document with the explain() method:
> db.mockdata.find({city:'Singapore...