We mentioned in Chapter 1, Introduction to Efficient Indexing and Chapter 2, What is an Elasticsearch Index that all Apache Lucene's data is stored in the inverted index. This means that the data is being transformed. The process of transforming data is called analysis. The analysis process relies on two basic pillars: tokenizing and normalizing.
The first step of the analysis process is to break the text into tokens using tokenizer after processing by the character filters for the inverted index. Then, it normalizes these tokens (that is, terms) to make them easily searchable.
Inverted index processes are performed by analyzers. Generally, an analyzer is composed of a tokenizer and one or more token filters. During the indexing time, when Elasticsearch processes a field that must be indexed, it checks whether an analyzer is defined at several levels or not because an analyzer can be specified at several levels.
The check order is as follows:
At field level
At type level
At...