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MongoDB Administrator???s Guide
MongoDB Administrator???s Guide

MongoDB Administrator???s Guide: Over 100 practical recipes to efficiently maintain and administer your MongoDB solution

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MongoDB Administrator???s Guide

Understanding and Managing Indexes

In this chapter, we will be covering the following topics:

  • Creating an index
  • Managing existing indexes
  • How to use compound indexes
  • Creating background indexes
  • Creating TTL-based indexes
  • Creating a sparse index
  • Creating a partial index
  • Creating a unique index

Introduction

In this chapter, we are going to look at how to create and manage database indexes in MongoDB. We will also look at how to view index sizes, create background indexes and creating various forms of indexes. So let's get started!

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...

Managing existing indexes

In this recipe, we will be looking at some common operations we can perform on indexes like viewing, deleting, checking index sizes, and re-indexing.

Getting ready

For this recipe, load the sample dataset and create an index on the city field, as described in the previous recipe.

How to do it...

  1. We begin by connecting to the mongo shell of the server and viewing all indexes on the system:
> db.mockdata.getIndexes()

The following result is obtained:

[
{
"v" : 2,
"key" : {
"_id" : 1
},
"name...

How to use compound indexes

The beauty of indexes is that they can be used with multiple keys. A single key index can be thought of as a table with one column. A multi-key index or compound index can be visualized as a multi column table where the first column is sorted first, and then the next, and so on. In this recipe, we will look at how to create a compound index and examine how it works.

Getting ready

Load the sample dataset and create an index on the city field, as described in the previous recipe.

How to do it...

  1. Assuming you have already created an index on the...

Creating background indexes

In the previous recipes, whenever we've created indexes, it has always been in the foreground that is, the database server blocks all changes to the database until the index creation is completed. This is definitely not suitable for larger datasets where index creation time can take a few seconds which could be application errors.

Getting ready

Load the sample dataset, as shown in the Creating an index recipe.

How to do it...

  1. Remove all indexes:
 > db.mockdata.dropIndexes()

{
"nIndexesWas" : 2,
"msg" : &quot...

Creating TTL-based indexes

In this recipe, we will explore the expireAfterSeconds property of MongoDB indexes to allow automatic deletion of documents from a collection.

Getting ready

For this recipe, all you need is a mongod instance running. We will be creating and working on a new collection called ttlcol in the database mydb.

How to do it...

  1. Ensure that our collection is empty:
db.ttlcol.drop()
  1. Add 200 random documents:
for(var x=1; x<=100; x++){
var past = new Date()
past.setSeconds(past.getSeconds() - (x * 60))
// Insert a document with timestamp in the...

Introduction


In this chapter, we are going to look at how to create and manage database indexes in MongoDB. We will also look at how to view index sizes, create background indexes and creating various forms of indexes. So let's get started!

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...

Managing existing indexes


In this recipe, we will be looking at some common operations we can perform on indexes like viewing, deleting, checking index sizes, and re-indexing.

Getting ready

For this recipe, load the sample dataset and create an index on the city field, as described in the previous recipe.

How to do it...

  1. We begin by connecting to the mongo shell of the server and viewing all indexes on the system:
> db.mockdata.getIndexes()

The following result is obtained:

[
  {
    "v" : 2,
    "key" : {
      "_id" : 1
    },
    "name" : "_id_",
    "ns" : "mydb.mockdata"
  },
  {
    "v" : 2,
    "key" : {
      "city" : 1,
      "first_name" : 1
    },
    "name" : "city_1_first_name_1",
    "ns" : "mydb.mockdata"
  }
]
  1. Execute a dropIndex() command to delete a particular index:
> db.mockdata.dropIndex('city_1_first_name_1')

You should see the following result:

 

{ "nIndexesWas" : 2, "ok" : 1 }
  1. Let's recreate the index:
> db.mockdata.createIndex({'city':1}, {name: 'city_index'})

{
   ...
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Key benefits

  • -Configure and deploy your MongoDB instance securely, without any hassle
  • -Optimize your database's query performance, perform scale-out operations, and make your database highly available
  • -Practical guide with a recipe-based approach to help you tackle any problem in the application and database administration aspects of MongoDB

Description

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.

Who is this book for?

Database administrators with a basic understanding of the features of MongoDB and who want to professionally configure, deploy, and administer a MongoDB database, will find this book essential. If you are a MongoDB developer and want to get into MongoDB administration, this book will also help you.

What you will learn

  • -Install and deploy MongoDB in production
  • -Manage and implement optimal indexes
  • -Optimize monitoring in MongoDB
  • -Fine-tune the performance of your queries
  • -Debug and diagnose your database s performance
  • -Optimize database backups and recovery and ensure high availability
  • -Make your MongoDB instance scalable
  • -Implement security and user authentication features in MongoDB
  • -Master optimal cloud deployment strategies
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Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Oct 25, 2017
Length: 226 pages
Edition : 1st
Language : English
ISBN-13 : 9781787126480
Vendor :
MongoDB
Category :
Tools :

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Product Details

Publication date : Oct 25, 2017
Length: 226 pages
Edition : 1st
Language : English
ISBN-13 : 9781787126480
Vendor :
MongoDB
Category :
Tools :

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Table of Contents

10 Chapters
Installation and Configuration Chevron down icon Chevron up icon
Understanding and Managing Indexes Chevron down icon Chevron up icon
Performance Tuning Chevron down icon Chevron up icon
High Availability with Replication Chevron down icon Chevron up icon
High Scalability with Sharding Chevron down icon Chevron up icon
Managing MongoDB Backups Chevron down icon Chevron up icon
Restoring MongoDB from Backups Chevron down icon Chevron up icon
Monitoring MongoDB Chevron down icon Chevron up icon
Authentication and Security in MongoDB Chevron down icon Chevron up icon
Deploying MongoDB in Production Chevron down icon Chevron up icon

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