Know About ElasticSearch and Kibana

I am quite excited to write and let you know about ElasticSearch & Kiban's features and strengths.

ElasticSearch is a Search engine helps us store and explore big data from live stream databases and itself within.

Kibana has built in ElasticSearch in addition various outstanding visualization features.

To start learning ElasticSearch, we must understand index/Indices concept in ElasticSearch. Let me give you brief explanation about the same.

Indices for Relations

The easiest and most familiar layout clones what you would expect from a relational database. You can (very roughly) think of an index like a database.

• MySQL => Databases => Tables => Columns/Rows
• Elasticsearch => Indices => Types => Documents with Properties

An Elasticsearch cluster can contain multiple Indices (databases), which in turn contain multiple Types(tables). These types hold multiple Documents (rows), and each document has Properties(columns).

So in your car manufacturing scenario, you may have a SubaruFactory index. Within this index, you have three different types:

• People
• Cars
• Spare_Parts

Each type then contains documents that correspond to that type (e.g. a Subaru Imprezza doc lives inside of the Cars type. This doc contains all the details about that particular car).

Searching and querying takes the format of: http://localhost:9200/[index]/[type]/[operation]

So to retrieve the Subaru document, I may do this:

$ curl -XGET localhost:9200/SubaruFactory/Cars/SubaruImprezza

I will keep posted here more....