JIYIK CN >

This article is a step-by-step installation and configuration guide for Elasticsearch on Windows and Ubuntu 20.04. It also demonstrates using Elasticsearch with MongoDB on both operating systems.

What is Elasticsearch

Elasticsearch is a NoSQL database, an open source real-time distributed and analytical engine designed to store logs. Elasticsearch is developed on Java programming and Apache Lucene.

Many well-known companies, including LinkedIn and OpenStack, use it. It supports full-text search based on documents rather than schemas and tables.

It is also used for data migration, indexing, and synchronization. Elasticsearch is the best choice when the application requires too many search operations and filters.

Installing Elasticsearch on Windows 10

Step 1: Check if Java is installed

To install Elasticsearch on Windows 10, we must install the latest version of Java on our machine. You can also use any of the following commands to confirm that Java is already installed on your machine.

Remember that if we want to install Elasticsearch, we must have Java version 7 or higher.

Step 2: Download the Elasticsearch .zipfile

Go to this website and click on the download link in the following screenshot. Next, select the platform on which we want to use Elasticsearch and then download .zipthe file.

Step 3: Run the Elasticsearch batch file

Once we have downloaded .zipthe file, extract it to your desired location. Then, navigate to binthe folder and double-click elasticsearchthe batch file.

It is nothing but a standard Windows batch file which contains the steps that are executed behind the scenes. Also, it helps in starting the Elasticsearch daemon on your machine as shown below.

Keep it open and follow the steps below.

Step 4: Disable Authentication (for learning purposes only)

By default, authentication is enabled, which means we have to enter the login credentials. You can use the default login credentials or change them by following this page.

For this article, we will disable authentication (for learning purposes only, but recommended for production environments). We use Notepad to open the file which can be located at %ES_HOME%\config\elasticsearch.ymlthe path elasticsearch.yml.

Here, ES_HOMEis your Elasticsearch home directory. For example, in our case, elasticsearch.ymlit can be located at C:\Users\DelftStack\Desktop\elasticsearch-8.2.2-windows-x86_64\elasticsearch-8.2.2\config.

Once the file opens elasticsearch.yml, search for xpack.security.enabledthe option and set its value to false, as shown in the screenshot below.

Stop Elasticsearch and elasticsearch.batstart it again by running the ./opt/Elasticsearch.exe file.

Step 5: Run Elasticsearch on your browser

Type it on your favorite browser http://localhost:9200. If you see a page similar to the following screenshot, it means Elasticsearch is up and running successfully.

Install Elasticsearch on Ubuntu 20.04

Step 1: Install required dependencies

Update/upgrade package index:

sudo apt update
sudo apt upgrade

Like Windows operating systems, Java is also required on Ubuntu to install Elasticsearch. If it is not installed yet, execute the following command to install the default JDK on Ubuntu 20.04.

sudo apt install openjdk-8-jdk

Once installed, java -versioncheck if it exists using .

We also need to install a APT Transportpackage to HTTPSmake all our repositories accessible through .

sudo apt install apt-transport-https

Step 2: Download and install Elasticsearch on Ubuntu

The next task is to add the Elasticsearch repository. Use wgetthe query to extract the public key.

If everything goes well, you should get OKas output.

wget -qO - https://artifacts.elastic.co/GPG-KEY-elasticsearch | sudo apt-key add -

Now, add the repository to the system by executing the following command. We are writing in the following command 8.xas this is the latest version at the time of writing this tutorial.

echo "deb https://artifacts.elastic.co/packages/8.x/apt stable main" | sudo tee -a /etc/apt/sources.list.d/elastic-8.x.list

Again, update the package index using the command given below.

sudo apt update

Install Elasticsearch by executing the following command. The installation may take some time.

So, let it be done successfully.

sudo apt install elasticsearch

After installation, we must start Elasticsearch as it will not start on its own. If we reboot our machine, we will also need to re-run Elasticsearch.

To avoid this, execute the following command to automatically reload Elasticsearch after a system reboot.

sudo systemctl daemon-reload
sudo systemctl enable elasticsearch.service
sudo systemctl start elasticsearch.service

Now, check the status of Elasticsearch using the following command.

sudo systemctl status elasticsearch

Step 3: Configure Elasticsearch

By default, Elasticsearch is pre-configured for basic usage. If we want to use a single node in our setup, we don’t have to make any changes to the configuration file.

If you want to edit the Elasticsearch configuration, edit the file /etc/elasticsearchin the directory elasticsearch.yml. You can also /var/log/elasticsearch/logging.ymlfind the configuration for logging in .

We are editing elasticsearch.ymlthe ./configure_authentication.xml file to disable authentication for this tutorial. We are changing xpack.security.enabledthe value of from trueto false.

Remember, whenever you edit elasticsearch.ymlthe file, don't forget to restart the service using the following command.

sudo systemctl restart elasticsearch.service

Next, check that Elasticsearch is up and running using the following command.

curl localhost:9200

We can also type on the browser , it should show the same result http://localhost:9200as the command given above .curl

Top Reasons to Use Elasticsearch with MongoDB

We use MongoDB to store and query data, and Elasticsearch is used to full-text index the data. Therefore, the combination of the two (Elasticsearch for indexing and MongoDB for storage) is one of the common architectures followed by many companies.

Elasticsearch was developed for search purposes and it also provides advanced features for data indexing. It is used for data analysis along with Kibanaand Logstash.

One of the advantages of using Elasticsearch is that it can quickly search all fields in a specified document. We can think of it as having our own personal Google to search our data.

We can also use Elasticsearch in different scenarios. For example, we can perform synchronization, build search engines, data migration, indexing, and more.

In this tutorial, we will learn to use Elasticsearch with MongoDB for synchronization purposes.

Synchronizing with Elasticsearch

We have to follow the steps given below to perform synchronization using Elasticsearch and MongoDB on Windows/Ubuntu. Before that, make sure you have all the dependencies.

For example, we use in this code sample Node.js. In addition, continue to run two database engines (MongoDB and Elasticsearch).

After that, let's follow the steps.

Sample code (put the whole code in one file, we put it app.jsin the .

//Step 1:
const mongoose     = require('mongoose');
const mongoosastic = require('mongoosastic');

//Step 2:
mongoose.connect('mongodb://localhost:27017/studentdb');

//Step 3:
var StudentSchema = new mongoose.Schema({
      firstname: String,
      lastname: String,
      city: String
});

//Step 4:
StudentSchema.plugin(mongoosastic, {
    "host": "localhost",
     "port": 9200
});

//Step 5:
var Student = mongoose.model('student', StudentSchema);
  Student.createMapping((err, mapping) => {
    console.log('mapping created');
});

//Step 6:
var newStudent = new Student({
     firstname: 'Mehvish',
     lastname: 'Ashiq',
     city: 'Lahore'
});

newStudent.save((err) => {
     if(err) {
         console.log(err);
     }
     console.log('Student is added in both databases');
})

newStudent.on('es-indexed', (err, result) => {
    console.log('indexed to elastic search');
});

Now, run this code; it looks like this:

Confirm the entries in MongoDB as follows.

Next, open http://localhost:9200/students/_searchto confirm on Elasticsearch. It will look similar to the following screenshot.