Custom analyzers in Elasticsearch - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a custom analyzer in Elasticsearch?

A custom analyzer is a user-defined text processor that controls how text is broken down and transformed during indexing and searching. It combines tokenizer, filters, and character filters to tailor text analysis.

beginner

Name the three main components of a custom analyzer.

The three main components are:<br>1. Character filters (modify text before tokenizing)<br>2. Tokenizer (splits text into tokens)<br>3. Token filters (modify tokens after tokenizing)

intermediate

How do you define a custom analyzer in Elasticsearch settings?

You define it inside the index settings under the 'analysis' section, specifying the analyzer name and its components like tokenizer and filters. Example:

{"analysis": {"analyzer": {"my_analyzer": {"type": "custom", "tokenizer": "standard", "filter": ["lowercase", "asciifolding"]}}}}

beginner

Why use the 'asciifolding' filter in a custom analyzer?

The 'asciifolding' filter converts accented characters to their ASCII equivalents (e.g., 'é' to 'e'), helping match text regardless of accents.

intermediate

What happens if you omit token filters in a custom analyzer?

If you omit token filters, the analyzer will only tokenize the text without modifying tokens further. This might miss opportunities to normalize or improve search matching.

Which component of a custom analyzer splits text into words?

A Tokenizer

B Character filter

C Token filter

D Index filter

The tokenizer breaks the text into tokens or words.

Where do you define a custom analyzer in Elasticsearch?

A In the index settings under 'analysis'

B In the document mapping

C In the search query

D In the cluster settings

Custom analyzers are defined in the index settings inside the 'analysis' section.

What does the 'lowercase' token filter do?

A Removes accents

B Removes stop words

C Splits text into tokens

D Converts tokens to lowercase

The 'lowercase' filter converts all tokens to lowercase to make searches case-insensitive.

Which filter would help match 'café' and 'cafe'?

A lowercase

B stop

C asciifolding

D synonym

'asciifolding' converts accented characters to ASCII equivalents, matching 'café' to 'cafe'.

If you want to remove common words like 'the' or 'and', which filter should you use?

A asciifolding filter

B stop filter

C lowercase filter

D keyword marker filter

The stop filter removes common stop words to improve search relevance.

Explain how to create a custom analyzer in Elasticsearch and why you might want to use one.

Think about how text is processed before searching.

Describe the role of token filters in a custom analyzer and give two examples.

Filters help clean or change words for better matching.