37 lines
1.6 KiB
Markdown
37 lines
1.6 KiB
Markdown
---
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layout: default
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title: Analysis API Terminology
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parent: Analyze API
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nav_order: 1
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---
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# Terminology
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The following sections provide descriptions of important text analysis terms.
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## Analyzers
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Analyzers tell OpenSearch how to index and search text. An analyzer is composed of three components: a tokenizer, zero or more token filters, and zero or more character filters.
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OpenSearch provides *built-in* analyzers. For example, the `standard` built-in analyzer converts text to lowercase and breaks text into tokens based on word boundaries such as carriage returns and white space. The `standard` analyzer is also called the *default* analyzer and is used when no analyzer is specified in the text analysis request.
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If needed, you can combine tokenizers, token filters, and character filters to create a *custom* analyzer.
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#### Tokenizers
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Tokenizers break unstructured text into tokens and maintain metadata about tokens, such as their starting and ending positions in the text.
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#### Character filters
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Character filters examine text and perform translations, such as changing, removing, and adding characters.
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#### Token filters
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Token filters modify tokens, performing operations such as converting a token's characters to uppercase and adding or removing tokens.
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## Normalizers
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Similar to analyzers, normalizers tokenize text but return a single token only. Normalizers do not employ tokenizers; they make limited use of character and token filters, such as those that operate on one character at a time.
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By default, OpenSearch does not apply normalizers. To apply normalizers, you must add them to your data before creating an index. |