쿼리 텍스트

개요

In this guide, you can learn how to use the Rust driver to run a text query. A text query allows you to efficiently query fields with string values.

이 가이드에는 다음 섹션이 포함되어 있습니다.

• Sample Data for Examples presents the sample data that is used by the text query examples

• 텍스트 인덱스 는 문자열 값 필드 에 텍스트 인덱스 를 만드는 방법을 설명합니다.

• Text Query describes how to perform text queries with different search criteria

• Aggregation describes how to perform text queries by using aggregation pipelines

• 추가 정보에서 이 가이드에 언급된 유형 및 메소드에 대한 리소스 및 API 문서 링크를 찾을 수 있습니다.

예시용 샘플 데이터

이 가이드의 예시에서는 다음 Dish 구조체를 menu collection의 문서 모델로 사용합니다.

#[derive(Serialize, Deserialize, Debug)]
struct Dish {
    name: String,
    description: String,
}

이 예제에서는 레스토랑에서 주문할 수 있는 요리를 설명하는 다음 샘플 문서를 사용합니다.

{ "name": "Shepherd’s Pie", "description": "A vegetarian take on the classic dish that uses lentils as a base. Serves 2." },
{ "name": "Green Curry", "description": "A flavorful Thai curry, made vegetarian with tofu. Vegetarian and vegan friendly." },
{ "name": "Herbed Branzino", "description": "Grilled whole fish stuffed with herbs and pomegranate seeds. Serves 3-4." },
{ "name": "Kale Tabbouleh", "description": "A bright, herb-based salad. A perfect starter for vegetarians and vegans." },
{ "name": "Garlic Butter Trout", "description": "Baked trout seasoned with garlic, lemon, dill, and, of course, butter. Serves 2." }

Text Index

Before you perform a text query, you must create a text index on the collection. A text index specifies the string or string array field on which you can perform text queries.

The examples in this guide perform text queries on the description field of documents in the menu collection. To enable text queries on the description field, create a text index as shown in the following code:

let index = IndexModel::builder()
    .keys(doc! { "description": "text" })
    .build();
let idx_res = my_coll.create_index(index).await?;

텍스트 쿼리

A text query retrieves documents that contain a specified term or phrase in the value of the indexed field. A term is a sequence of characters that excludes whitespace characters. A phrase is a sequence of terms with any number of whitespace characters.

To perform a text query, include the $text evaluation query operator, followed by the $search field in your query filter. The $text operator specifies that you are performing a text query on the text-indexed fields. The $search field specifies the term or phrase to search for in the text-indexed field or fields.

Filters for text queries use the following format:

let filter = doc! { "$text": { "$search": "<search term or phrase>" } };

let filter = doc! { "$text": { "$search": "herb" } };
let mut cursor = my_coll.find(filter).await?;
while let Some(doc) = cursor.try_next().await? {
    println!("{:?}", doc);
}

Dish { name: "Kale Tabbouleh", description: "A bright, herb-based salad. A perfect starter for vegetarians and vegans." }
Dish { name: "Herbed Branzino", description: "Grilled whole fish stuffed with herbs and pomegranate seeds. Serves 3-4." }

let filter = doc! { "$text": { "$search": "\"<some phrase>\"" } };

let filter = doc! { "$text": { "$search": "\"serves 2\"" } };
let mut cursor = my_coll.find(filter).await?;
while let Some(doc) = cursor.try_next().await? {
    println!("{:?}", doc);
}

Dish { name: "Shepherd's Pie", description: "A vegetarian take on the classic dish that uses lentils as a base. Serves 2." }
Dish { name: "Garlic Butter Trout", description: "Baked trout seasoned with garlic, lemon, dill, and, of course, butter. Serves 2." }

let filter = doc! { "$text": { "$search": "<term> -<excluded term>" } };

let filter = doc! { "$text": { "$search": "vegan -tofu" } };
let mut cursor = my_coll.find(filter).await?;
while let Some(doc) = cursor.try_next().await? {
    println!("{:?}", doc);
}

Dish { name: "Kale Tabbouleh", description: "A bright, herb-based salad. A perfect starter for vegetarians and vegans." }

let filter = doc! { "$text": { "$search": "vegetarian" } };
let sort = doc! { "score": { "$meta": "textScore" } };
let projection =
    doc! { 
    "_id": 0, 
    "name": 1, 
    "score": { "$meta": "textScore" } 
};
let doc_coll: Collection<Document> = my_coll.clone_with_type();
let mut cursor = doc_coll.find(filter)
    .sort(sort)
    .projection(projection)
    .await?;
while let Some(doc) = cursor.try_next().await? {
    println!("{:?}", doc);
}

Document({"name": String("Green Curry"), "score": Double(0.9166666666666667)})
Document({"name": String("Kale Tabbouleh"), "score": Double(0.5625)})
Document({"name": String("Shepherd’s Pie"), "score": Double(0.5555555555555556)})

집계

You can include the $text evaluation query operator in a $match aggregation stage to perform a text query in an aggregation pipeline.

The following sections demonstrate how to perform text queries by using aggregation pipelines instead of the find() method.

let match_stage = doc! { "$match": { "$text": { "$search": "herb" } } };
let mut cursor = my_coll.aggregate([match_stage]).await?;
while let Some(doc) = cursor.try_next().await? {
    println!("{:?}", doc);
}

Document({"_id": ObjectId("..."), "name": String("Kale Tabbouleh"), "description": String("A bright, herb-based salad. A perfect starter for vegetarians and vegans.")})
Document({"_id": ObjectId("..."), "name": String("Herbed Branzino"), "description": String("Grilled whole fish stuffed with herbs and pomegranate seeds. Serves 3-4.")})

let match_stage = doc! { "$match": { "$text": { "$search": "vegetarian" } } };
let sort_stage = doc! { "$sort": { "score": { "$meta": "textScore" } } };
let proj_stage =
    doc! { "$project": { 
    "_id": 0, 
    "name": 1, 
    "score": { "$meta": "textScore" } 
} };
let pipeline = [match_stage, sort_stage, proj_stage];
let mut cursor = my_coll.aggregate(pipeline).await?;
while let Some(doc) = cursor.try_next().await? {
    println!("{:?}", doc);
}

Document({"name": String("Green Curry"), "score": Double(0.9166666666666667)})
Document({"name": String("Kale Tabbouleh"), "score": Double(0.5625)})
Document({"name": String("Shepherd’s Pie"), "score": Double(0.5555555555555556)})

추가 정보

find() 메서드를 사용하는 실행 가능한 예시 는 여러 문서 찾기 사용 예시 참조하세요.

이 가이드의 작업에 대해 자세히 알아보려면 다음 문서를 참조하세요.

• 쿼리 지정

• Retrieve Data

• 결과 정렬

• 집계

• Indexes

• 서버 매뉴얼의 텍스트 인덱스

• MongoDB Server 매뉴얼의 $text

• 서버 매뉴얼의 $meta