DevOps Classroom Series – 16/Sept/2021

Schemaless and document-oriented

• Elastic search doesnot impose a strict structure on your data, you can store any json documents.
• JSON documents are first class citizens of Elastic search (as opposed to rows and columns in the Relational database).
• A document in Elastic Search is roughly equivalent to record in relational database table
• Traditional databases require a schema to defined beforehand
• JSON documents naturally support dynamic data

//first record
{
  "name": "John Doe",
  "email": "johndoe@gmail.com",
  "address": {
	"city": "New York"
  }
}

//second record
{
  "email": "jane_doe@gmail.com",
  "age": 45,
  "address": {
      "country": "USA",
      "zipcode": "10010"
  }
}

Searching capabilities

• The core strength of Elastic Search lies in its text-processing capabilities.
• Elastic search is great at searching especially full-text searches
• Full text search means searching through all the terms of the documents available in database, This requires entire content of all documents to be parsed and stored before hand.
• When you want to perform a search similar to Google search on your own data, Elastic search is your best bet, you can index emails, text documents, pdf files, web pages
• At a high level, Elastic search breaks up text data into terms and makes every term searchable by building lucene indexes

Analytics

• Elastic search supports wide variety of aggregations for analytics

Rich Client Library Support and REST API

• Elastic search has a very rich client library support to access from languages like JAVA, C#, python, JavaScript, Ruby & more
• Elastic search has a very rich REST API (Representational state transfer) which works on HTTP protocol.

Easy to Operate and easy to Scale

• Elastic search can run on single node and easily scale out to hunderds of nodes
• Unlike most traditional database that only allow vertical scaling, Elastic search can be scaled horizontally
• The client application doesn’t need to change wheter it is running against a single node or a hundred node cluster
• Elastic search clusters can keep running even when there are hardware failures such as node failure, network failure etc i.e. Elastic search is designed to scale and is fault-tolerant

Installing Elastic Search

• Refer Here to download elastic search
• Refer Here for the installation of elastic search
• For understanding features of elastic search lets try to run elastic search locally
  • Refer Here
• Unzip the downloaded file and do the following
• Run the command curl http://localhost:9200?pretty from git bash
• Open browser and navigate to http://localhost:9200?pretty

Install Kibana

• Download kibana zip from Refer Here
• Extract the file and RUN bin\kibana.bat
• Now open http://localhost:5601 in your browser

Lab Setup

• Installing necessary softwares on Windows Refer Here
• Install Windows Terminal Refer Here