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MongoDB Cookbook - Second Edition
MongoDB Cookbook - Second Edition

MongoDB Cookbook - Second Edition: Modern Database Management Made Easy , Second Edition

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MongoDB Cookbook - Second Edition

Chapter 2. Command-line Operations and Indexes

In this chapter, we will cover the following topics:

  • Creating test data
  • Performing simple querying, projections, and pagination from the Mongo shell
  • Updating and deleting data from the shell
  • Creating an index and viewing plans of queries
  • Creating a background and foreground index in the shell
  • Creating and understanding sparse indexes
  • Expiring documents after a fixed interval using the TTL index
  • Expiring documents at a given time using the TTL index

Introduction

In this chapter we will be performing simple queries using the mongo shell. Later in the chapter, we will have a detailed look at commonly used MongoDB indexes.

Creating test data

This recipe is about creating test data for some of the recipes in this chapter and also for the later chapters in this book. We will demonstrate how to load a CSV file in a mongo database using the mongo import utility. This is a basic recipe, and if the reader is aware of the data import utility; they can just download the CSV file from the Packt website (pincodes.csv), load it in the collection by themselves, and skip the rest of the recipe. We will use the default database, test, and the collection will be named postalCodes.

Getting ready

The data used here is for postcodes in India. Download the pincodes.csv file from the Packt website. The file is a CSV file with 39,732 records; it should create 39,732 documents on successful import. We need to have the Mongo server up and running. Refer to the Installing single node MongoDB recipe from Chapter 1, Installing and Starting the Server for instructions on how to start the server. The server should begin listening for...

Performing simple querying, projections, and pagination from Mongo shell

In this recipe, we will get our hands dirty with a bit of querying to select documents from the test data that we set up in our previous recipe, Creating test data. There is nothing extravagant in this recipe and someone who is well versed with the query language basics can skip this recipe. Others who aren't too comfortable with basic querying or those who want to get a small refresher can continue to read the next section of the recipe. Additionally, this recipe is intended to get a feel of the test data setup from the previous recipe.

Getting ready

To execute simple queries, we need to have a server up and running. A simple single node is what we need. Refer to the Installing single node MongoDB recipe from Chapter 1, Installing and Starting the Server for instructions on how to start the server. The data that we would be operating on needs to be imported in the database. The steps to import the data are given...

Updating and deleting data from the shell

This again will be a simple recipe that will be looking at executing deletes and updates on a test collection. We won't be dealing with the same test data that we imported as we don't want to update/delete any of that, but instead, we will work on a test collection created for this recipe only.

Getting ready

For this recipe, we will create a collection called updAndDelTest. We will require the server to be up and running. Refer to the Installing single node MongoDB recipe from Chapter 1, Installing and Starting the Server for instructions on how to start the server. Start the shell with the UpdAndDelTest.js script loaded. This script will be available on the Packt website for download. To know how to start the shell with a script preloaded, refer to the Connecting to a single node in the Mongo shell with JavaScript recipe in Chapter 1, Installing and Starting the Server.

How to do it…

  1. Start the MongoDB shell and preload the script:
    ...

Creating index and viewing plans of queries

In this recipe, we will look at querying the data, analyzing its performance by explaining the query plan, and then optimizing it by creating indexes.

Getting ready

For the creation of indexes, we need to have a server up and running. A simple single node is what we need. Refer to the Installing single node MongoDB recipe from Chapter 1, Installing and Starting the Server for instructions on how to start the server. The data that we will operate on needs to be imported in the database. The steps to import the data are given in the previous recipe, Creating test data. Once this prerequisite is complete, we are good to go.

How to do it…

We are trying to write a query that would find us all the zip codes in a given state.

  1. Execute the following query to view the plan of this query:
    > db.postalCodes.find({state:'Maharashtra'}).explain('executionStats')
    

    Take a note of the following fields: stage, nReturned, totalDocsExamined...

Introduction


In this chapter we will be performing simple queries using the mongo shell. Later in the chapter, we will have a detailed look at commonly used MongoDB indexes.

Creating test data


This recipe is about creating test data for some of the recipes in this chapter and also for the later chapters in this book. We will demonstrate how to load a CSV file in a mongo database using the mongo import utility. This is a basic recipe, and if the reader is aware of the data import utility; they can just download the CSV file from the Packt website (pincodes.csv), load it in the collection by themselves, and skip the rest of the recipe. We will use the default database, test, and the collection will be named postalCodes.

Getting ready

The data used here is for postcodes in India. Download the pincodes.csv file from the Packt website. The file is a CSV file with 39,732 records; it should create 39,732 documents on successful import. We need to have the Mongo server up and running. Refer to the Installing single node MongoDB recipe from Chapter 1, Installing and Starting the Server for instructions on how to start the server. The server should begin listening for connections...

Performing simple querying, projections, and pagination from Mongo shell


In this recipe, we will get our hands dirty with a bit of querying to select documents from the test data that we set up in our previous recipe, Creating test data. There is nothing extravagant in this recipe and someone who is well versed with the query language basics can skip this recipe. Others who aren't too comfortable with basic querying or those who want to get a small refresher can continue to read the next section of the recipe. Additionally, this recipe is intended to get a feel of the test data setup from the previous recipe.

Getting ready

To execute simple queries, we need to have a server up and running. A simple single node is what we need. Refer to the Installing single node MongoDB recipe from Chapter 1, Installing and Starting the Server for instructions on how to start the server. The data that we would be operating on needs to be imported in the database. The steps to import the data are given in the...

Updating and deleting data from the shell


This again will be a simple recipe that will be looking at executing deletes and updates on a test collection. We won't be dealing with the same test data that we imported as we don't want to update/delete any of that, but instead, we will work on a test collection created for this recipe only.

Getting ready

For this recipe, we will create a collection called updAndDelTest. We will require the server to be up and running. Refer to the Installing single node MongoDB recipe from Chapter 1, Installing and Starting the Server for instructions on how to start the server. Start the shell with the UpdAndDelTest.js script loaded. This script will be available on the Packt website for download. To know how to start the shell with a script preloaded, refer to the Connecting to a single node in the Mongo shell with JavaScript recipe in Chapter 1, Installing and Starting the Server.

How to do it…

  1. Start the MongoDB shell and preload the script:

    $ mongo --shell updAndDelTest...
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Key benefits

  • Get to grips with the latest features of MongoDB 3
  • Interact with the MongoDB server and perform a wide range of query operations from the shell
  • From administration to automation, this cookbook keeps you up to date with the world’s leading NoSQL database

Description

MongoDB is a high-performance and feature-rich NoSQL database that forms the backbone of the systems that power many different organizations – it’s easy to see why it’s the most popular NoSQL database on the market. Packed with many features that have become essential for many different types of software professionals and incredibly easy to use, this cookbook contains many solutions to the everyday challenges of MongoDB, as well as guidance on effective techniques to extend your skills and capabilities. This book starts with how to initialize the server in three different modes with various configurations. You will then be introduced to programming language drivers in both Java and Python. A new feature in MongoDB 3 is that you can connect to a single node using Python, set to make MongoDB even more popular with anyone working with Python. You will then learn a range of further topics including advanced query operations, monitoring and backup using MMS, as well as some very useful administration recipes including SCRAM-SHA-1 Authentication. Beyond that, you will also find recipes on cloud deployment, including guidance on how to work with Docker containers alongside MongoDB, integrating the database with Hadoop, and tips for improving developer productivity. Created as both an accessible tutorial and an easy to use resource, on hand whenever you need to solve a problem, MongoDB Cookbook will help you handle everything from administration to automation with MongoDB more effectively than ever before.

Who is this book for?

This book is engineered for anyone who is interested in managing data in an easy and efficient way using MongoDB. You do not need any prior knowledge of MongoDB, but it would be helpful if you have some programming experience in either Java or Python.

What you will learn

  • Install, configure, and administer MongoDB sharded clusters and replica sets
  • Begin writing applications using MongoDB in Java and Python languages
  • Initialize the server in three different modes with various configurations
  • Perform cloud deployment and introduce PaaS for Mongo
  • Discover frameworks and products built to improve developer productivity using Mongo
  • Take an in-depth look at the Mongo programming driver APIs in Java and Python
  • Set up enterprise class monitoring and backups of MongoDB
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Length: 370 pages
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Table of Contents

11 Chapters
1. Installing and Starting the Server Chevron down icon Chevron up icon
2. Command-line Operations and Indexes Chevron down icon Chevron up icon
3. Programming Language Drivers Chevron down icon Chevron up icon
4. Administration Chevron down icon Chevron up icon
5. Advanced Operations Chevron down icon Chevron up icon
6. Monitoring and Backups Chevron down icon Chevron up icon
7. Deploying MongoDB on the Cloud Chevron down icon Chevron up icon
8. Integration with Hadoop Chevron down icon Chevron up icon
9. Open Source and Proprietary Tools Chevron down icon Chevron up icon
A. Concepts for Reference Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Full star icon 5
(2 Ratings)
5 star 100%
4 star 0%
3 star 0%
2 star 0%
1 star 0%
Dave Jul 14, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I have several books on MongoDB and manage a cluster of MongoDB servers. After this much experience, I *should* know a lot of what's already in this book (and do). However, there were several nuggets of great information that I hadn't seen before. Easy to read with lots of concise examples.
Amazon Verified review Amazon
oluyemi@lineone.net Jun 25, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
It a good book with Lots of useful examples
Amazon Verified review Amazon
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