What is Elasticsearch Analyzers?

Analyzers are pre-processors which are executed on the Text before generating inverted index. 

So why do we need Analyzers in Elasticsearch?

Consider a field which we want have inverted-index

Document 1: "Hello Elasticsearch World "
Document 2: "hello Elasticsearch world"

The Inverted Index looks like this:

Term	(Document,Frequency)
Hello	(1,1)
World	(1,1)
Elasticsearch	(1,1),(2,1)
hello	(2,1)
world	(2,1)

Its evident that "Hello" and "hello" are same words with change in case, As there are two separate indexes for the same word , the query returns partial result when we need a case insensitive search.

To fix the above issue,Now lets have the words converted to lowercase before creating the inverted-index.

Term	(Document,Frequency)
hello	(1,1),(2,1)
world	(1,1),(2,1)
Elasticsearch	(1,1),(2,1)

This is what analyzers in Elasticsearch are for. This a simple illustration and analyzers are designed to do more than the example used for illustration.

In simple terms an Analyzer does:

1. Split the text into individual terms or token, based on whitespace.
2. Standardize the individual terms so they are searchable.

What is Inverted Index in Elasticsearch

Elasticsearch is a Full Text Search Engine built on top of Lucene. The index structure used in Lucene to enable fast search lookups is called "Inverted Index". 

Inverted index is a simple concept, but yet powerful to enable efficient search. Its a list of unique words(terms) that appear in the documents stored. Each unique words map to list of documents in which they appear along with how many times the word has occurred in the document (Frequency).