In Elasticsearch, an analyzer is a combination of three different components, which are as follows:
1. Character filters: These filters are used to transform the input text before it is tokenized. They can be used to remove unwanted characters, convert characters to lowercase or uppercase, or replace specific characters with others.
2. Tokenizer: The tokenizer is responsible for breaking down the input text into individual tokens. It can be configured to use different strategies for tokenization, such as splitting on whitespace, punctuation, or specific characters.
3. Token filters: Once the text has been tokenized, token filters can be applied to modify the tokens. For example, you might want to remove stop words (common words like “the” or “and”), apply stemming to reduce words to their root form, or apply synonym expansion to replace tokens with their equivalent terms.
Each of these components can be configured independently, allowing you to create custom analyzers that suit the needs of your specific use case. You can also use pre-built analyzers provided by Elasticsearch or third-party libraries.