文本搜索

To perform text search, MongoDB uses a text index and the $text operator.

插入用例数据

> db.stores.insert(
...    [
...      { _id: 1, name: "Java Hut", description: "Coffee and cakes" },
...      { _id: 2, name: "Burger Buns", description: "Gourmet hamburgers" },
...      { _id: 3, name: "Coffee Shop", description: "Just coffee" },
...      { _id: 4, name: "Clothes Clothes Clothes", description: "Discount clothing" },
...      { _id: 5, name: "Java Shopping", description: "Indonesian goods" }
...    ]
... )
BulkWriteResult({
    "writeErrors" : [ ],
    "writeConcernErrors" : [ ],
    "nInserted" : 5,
    "nUpserted" : 0,
    "nMatched" : 0,
    "nModified" : 0,
    "nRemoved" : 0,
    "upserted" : [ ]
})

文字索引

MongoDB provides text indexes to support text search queries on string content. text indexes can include any field whose value is a string or an array of string elements.

To perform text search queries, you must have a text index on your collection. A collection can only have one text search index, but that index can cover multiple fields.

For example you can run the following in a mongo shell to allow text search over the name and descriptionfields:

> db.stores.createIndex( { name: "text", description: "text" } )
{
    "createdCollectionAutomatically" : false,
    "numIndexesBefore" : 1,
    "numIndexesAfter" : 2,
    "ok" : 1
}
> 

$text运算符

使用$text查询运算符对具有文本索引的集合执行文本搜索。

$text将使用空格和大多数标点符号作为分隔符来OR标记搜索字符串，并对搜索字符串中的所有此类标记执行逻辑运算。

例如，您可以使用以下查询从列表“ coffee”，“ shop”和“ java”中查找包含任何术语的所有商店：

db.stores.find( { $text: { $search: "java coffee shop" } } )

精确匹配

您还可以通过将它们括在双引号中来搜索确切的短语
以下将查找包含“coffee shop”的所有文档：

db.stores.find( { $text: { $search: "\"coffee shop\"" } } )

排除单词

要排除一个单词，可以在前面加上一个“ -”字符。例如，要查找所有包含“ java”或“ shop”但不包含“ coffee”的商店，请使用以下命令：

> db.stores.find( { $text: { $search: "java shop -coffee" } } )
{ "_id" : 5, "name" : "Java Shopping", "description" : "Indonesian goods" }

排序

默认情况下，MongoDB将以未排序的顺序返回结果。但是，文本搜索查询将为每个文档计算相关性分数，以指定文档与查询的匹配程度。
要按相关性得分的顺序对结果进行排序，必须显式投影该字段并对其进行排序：$meta textScore field

> db.stores.find(
...    { $text: { $search: "java coffee shop" } },
...    { score: { $meta: "textScore" } }
... ).sort( { score: { $meta: "textScore" } } )
{ "_id" : 3, "name" : "Coffee Shop", "description" : "Just coffee", "score" : 2.25 }
{ "_id" : 1, "name" : "Java Hut", "description" : "Coffee and cakes", "score" : 1.5 }
{ "_id" : 5, "name" : "Java Shopping", "description" : "Indonesian goods", "score" : 1.5 }
> 

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