Testing analyzers (_analyze API) in Elasticsearch - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the purpose of the _analyze API in Elasticsearch?

The _analyze API helps you test how Elasticsearch breaks down text into tokens using a specific analyzer. It shows the tokens produced, their positions, and other details.

beginner

Which HTTP method is used to call the _analyze API?

You use the POST method to send text and analyzer settings to the _analyze API for testing.

intermediate

What key information does the _analyze API response provide?

It provides a list of tokens, each with its text, start and end offsets, position, and type. This helps you understand how text is processed.

intermediate

How can you specify a custom analyzer when using the _analyze API?

You include the analyzer name in the request body under the analyzer field, or define tokenizer and filters directly to test custom behavior.

beginner

Why is testing analyzers important before indexing data?

Testing analyzers ensures your text is tokenized as expected, which affects search accuracy and relevance. It helps catch issues early.

Which API helps you see how text is broken into tokens in Elasticsearch?

A _analyze API

B _search API

C _index API

D _mapping API

The _analyze API shows how text is tokenized by an analyzer.

What HTTP method do you use to test an analyzer with the _analyze API?

A GET

B PUT

C DELETE

D POST

You use POST to send text and analyzer settings to the _analyze API.

In the _analyze API response, what does each token include?

A Only the original text

B Text, position, offsets, and type

C Index name and document ID

D Search results count

Tokens include text, position, start and end offsets, and type.

How do you specify a custom analyzer in the _analyze API request?

A By setting the analyzer field in the request body

B By changing the index settings only

C By using the _search API

D By modifying the document mapping

You specify the analyzer in the request body to test it directly.

Why should you test analyzers before indexing data?

A To speed up indexing

B To delete old data

C To ensure text is tokenized correctly for accurate search

D To backup the index

Testing analyzers helps ensure search works well by tokenizing text properly.

Explain how the _analyze API helps you understand text processing in Elasticsearch.

Think about what happens to text before it is searchable.

Describe the steps to test a custom analyzer using the _analyze API.

Focus on how you send the request and what you look for in the response.