23 lines
3.3 KiB
Markdown
23 lines
3.3 KiB
Markdown
# `TermvectorsRequest` [interface-TermvectorsRequest]
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| Name | Type | Description |
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| - | - | - |
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| `body` | string | ({ [key: string]: any; } & { index?: never; id?: never; preference?: never; realtime?: never; doc?: never; filter?: never; per_field_analyzer?: never; fields?: never; field_statistics?: never; offsets?: never; payloads?: never; positions?: never; term_statistics?: never; routing?: never; version?: never; version_type?: never; }) | All values in `body` will be added to the request body. |
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| `doc` | TDocument | An artificial document (a document not present in the index) for which you want to retrieve term vectors. |
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| `field_statistics` | boolean | If `true`, the response includes: * The document count (how many documents contain this field). * The sum of document frequencies (the sum of document frequencies for all terms in this field). * The sum of total term frequencies (the sum of total term frequencies of each term in this field). |
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| `fields` | [Fields](./Fields.md) | A list of fields to include in the statistics. It is used as the default list unless a specific field list is provided in the `completion_fields` or `fielddata_fields` parameters. |
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| `filter` | [TermvectorsFilter](./TermvectorsFilter.md) | Filter terms based on their tf-idf scores. This could be useful in order find out a good characteristic vector of a document. This feature works in a similar manner to the second phase of the More Like This Query. |
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| `id` | [Id](./Id.md) | A unique identifier for the document. |
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| `index` | [IndexName](./IndexName.md) | The name of the index that contains the document. |
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| `offsets` | boolean | If `true`, the response includes term offsets. |
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| `payloads` | boolean | If `true`, the response includes term payloads. |
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| `per_field_analyzer` | Record<[Field](./Field.md), string> | Override the default per-field analyzer. This is useful in order to generate term vectors in any fashion, especially when using artificial documents. When providing an analyzer for a field that already stores term vectors, the term vectors will be regenerated. |
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| `positions` | boolean | If `true`, the response includes term positions. |
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| `preference` | string | The node or shard the operation should be performed on. It is random by default. |
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| `querystring` | { [key: string]: any; } & { index?: never; id?: never; preference?: never; realtime?: never; doc?: never; filter?: never; per_field_analyzer?: never; fields?: never; field_statistics?: never; offsets?: never; payloads?: never; positions?: never; term_statistics?: never; routing?: never; version?: never; version_type?: never; } | All values in `querystring` will be added to the request querystring. |
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| `realtime` | boolean | If true, the request is real-time as opposed to near-real-time. |
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| `routing` | [Routing](./Routing.md) | A custom value that is used to route operations to a specific shard. |
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| `term_statistics` | boolean | If `true`, the response includes: * The total term frequency (how often a term occurs in all documents). * The document frequency (the number of documents containing the current term). By default these values are not returned since term statistics can have a serious performance impact. |
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| `version_type` | [VersionType](./VersionType.md) | The version type. |
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| `version` | [VersionNumber](./VersionNumber.md) | If `true`, returns the document version as part of a hit. |
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