Installing Elastic Search

• Used instructions from here to install elastic search
• Elastic search by default is configured to run on 9200. Try accessing http://<public ip>:9200
• To fix this lets change configuration in /etc/elasticsearch/elasticsearch.yml
• To know complete information about configuration files Refer Here
• For network.host setting Refer Here
• Basic Elastic search settings are configured to work with localhost, if you need make them work on production, focus on network configurations first.

Lets install Kibana on the same server

• Used Instructions From here to install kibana
• Since we configured repository on this machine already, directly execute command

sudo apt-get update && sudo apt-get install kibana

• Lets change the configuration of kibana (/etc/kibana/kibana.yml)
• Restart kibana after changing configurations and navigate to http://<publicip&gt;:5601
• Naviagate to DevTools
• Console in the DevTools will be our playground to understand elastic search concepts
• Here we have simply sent the GET / query. This is equivalent to curl command that we send to Elastic search for testing the setup curl http://<elasticsearchipaddress>:9200

Core Concepts of Elastic Search

• We need the understand the following core abstractions

  • Indexes
  • Types
  • Documents
  • Clusters
  • Nodes
  • Shards and replicas
  • Mappings and types
  • Inverted Indexes

• Lets Execute the following in the Kibana Dev Console

PUT /catalog/_doc/1
{
    "title": "Linux Bible, 9th Edition",
    "author": "Christopher Negus",
    "ISBN": "978-1-118-99987-5",
    "price": 50,
    "pages": 912,
    "pubished_date": "april 2015"

}

• To understand what has happened in the above image, lets try to understand core abstractions

Index

• An index is a container that stores and manages document of single type in Elastic.
• Concept of index in Elastic Search is almost equivalent to the database in relational database. However consider index as one database with only one table with multiple records.
• Index is logical container of Type. and Type will be logical collections records of the type defined
• Database = Index Table = Type Records = Documents (Json)
• From Elastic Search 7.0 one index can contain only one type, attempting add one more type in into index will create error.