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使用MongoDB Search 更新 $text 查询以提高搜索性能

If your queries rely heavily on the $text aggregation pipeline stage, you can modify these queries to use $search instead to improve both the flexibility and performance of these queries.

MongoDB Search 功能优势

The $search aggregation stage provides the following features which are either not available through the $text operator, available but less performant, or available only with significant implementation work by the user:

语言认知
不区分大小写和不区分变音符号的搜索
Result text highlighting
Geospatial-aware queries with geoWithin and geoShape.
Character and word autocompletion with different tokenization strategies
模糊匹配
Filtering on 10 or more strings with the compound operator
Customizable relevance scoring and sorting
数组上的单个复合索引
Synonym search
Bucketing for faceted navigation
自定义分析器
Phrase queries

示例

创建索引

The examples in the following sections use queries against the sample_mflix.movies collection in the sample data to illustrate the improvements to flexibility and performance that MongoDB Search offers over $text. You can run the queries from both examples using the following indexes:

Text Index

MongoDB搜索索引

db.movies.createIndex(
  {
    genres: "text",
    plot: "text",
    year: -1
  }
)

{
  "mappings": {
    "dynamic": false,
    "fields": {
      "genres": {
        "type": "string"
      },
      "plot": {
        "type": "string"
      },
      "year": {
        "type": "number"
      }
    }
  }
}

Either index definition will index the genres and plot fields as text, and the year field as numeric. For instructions on creating $text indexes, see Create Text Index. For instructions on creating MongoDB Search indexes, see Create a MongoDB Search Index.

使用MongoDB Search 提高全文查询的灵活性

You can update your $text-based queries to use $search for greater flexibility and convenience. In this example, you will query the sample_mflix.movies collection in the sample data to retrieve entries with the word 'poet' in the plot field, sorted in ascending order by year.

The index definitions laid out in the previous section illustrate one of the flexibility enhancements of $search. In order to create the $text index on sample_mflix.movies, you must first delete any existing text index on the sample data using the db.collection.dropIndex() method, as MongoDB supports only a single text index per collection.

In contrast, you can create multiple MongoDB Search indexes for a single collection, allowing your applications to leverage distinct full text queries in parallel.

以下查询返回plot字段中包含“poet”的五部最新电影，显示它们的标题、类型、情节和上映年份。

Regex Index

MongoDB搜索索引

db.movies.find(
   {
     $text: { $search: "poet" }
   },
   {
     _id: 0,
     title: 1,
     genres: 1,
     plot: 1,
     year: 1
   }
).limit(5)

db.movies.aggregate([
   {
     "$search": {
       "text": {
         "path": "plot",
         "query": "poet"
       }
     }
   },
   {
     "$limit": 5
   },
   {
     "$project": {
       "_id": 0,
       "title": 1,
       "genres": 1,
       "plot": 1,
       "year": 1,
     }
   }
])

这两个查询都返回以下结果：

{
 plot: `It's the story of the murder of a poet, a man, a great film director: Pier Paolo Pasolini. The story begin with the arrest of "Pelosi", a young man then accused of the murder of the poet. ...`,
 genres: [ 'Crime', 'Drama' ],
 title: 'Who Killed Pasolini?',
 year: 1995
},
{
 plot: 'Friendship and betrayal between two poets during the French Revolution.',
 genres: [ 'Biography', 'Drama' ],
 title: 'Pandaemonium',
 year: 2000
},
{
 year: 2003,
 plot: 'Story of the relationship between the poets Ted Hughes and Sylvia Plath.',
 genres: [ 'Biography', 'Drama', 'Romance' ],
 title: 'Sylvia'
},
{
 year: 2003,
 plot: 'Story of the relationship between the poets Ted Hughes and Sylvia Plath.',
 genres: [ 'Biography', 'Drama', 'Romance' ],
 title: 'Sylvia'
},
{
 plot: 'A love-struck Italian poet is stuck in Iraq at the onset of an American invasion.',
 genres: [ 'Comedy', 'Drama', 'Romance' ],
 title: 'The Tiger and the Snow',
 year: 2005
}

Unique to MongoDB Search, you can add highlights to the results, displaying matches in the contexts in which they were found. To do so, replace the MongoDB Search query above with the following:

1 db.movies.aggregate([
2   {
3     "$search": {
4       "text": {
5         "path": "plot",
6         "query": "poet"
7       },
8       "highlight": {
9         "path": "plot"
10       }
11     }
12   },
13   {
14     "$limit": 1
15   },
16   {
17     "$project": {
18       "_id": 0,
19       "title": 1,
20       "genres": 1,
21       "plot": 1,
22       "year": 1,
23       "highlights": { "$meta": "searchHighlights" }
24     }
25   }
26 ])

上述查询的结果包括highlights字段，其中包含所有匹配项发生的上下文以及每个匹配项的相关性分数。例如，以下显示了$search结果中第一个文档的highlights字段。

{
  plot: `It's the story of the murder of a poet, a man, a great film director: Pier Paolo Pasolini. The story begin with the arrest of "Pelosi", a young man then accused of the murder of the poet. ...`,
  genres: [ 'Crime', 'Drama' ],
  title: 'Who Killed Pasolini?',
  year: 1995,
  highlights: [
    {
      score: 1.0902210474014282,
      path: 'plot',
      texts: [
        { value: "It's the story of the murder of a ", type: 'text' },
        { value: 'poet', type: 'hit' },
        {
          value: ', a man, a great film director: Pier Paolo Pasolini. ',
          type: 'text'
        }
      ]
    },
    {
      score: 1.0202842950820923,
      path: 'plot',
      texts: [
        {
          value: 'The story begin with the arrest of "Pelosi", a young man then accused of the murder of the ',
          type: 'text'
        },
        { value: 'poet', type: 'hit' },
        { value: '. ...', type: 'text' }
      ]
    }
  ]
}

使用MongoDB Search 提高查询性能

In addition to greater flexibility and convenience, MongoDB Search provides significant performance advantages over analogous $text queries. Consider a query against the sample_mflix.movies collection to retrieve movies released between 2000 and 2010, in the comedy genre, with 'poet' in the plot field.

运行以下查询：

Text Index

MongoDB搜索索引

db.movies.aggregate([
  {
    $match: {
      year: {$gte: 2000, $lte: 2010},
      $text: { $search: "poet" },
      genres : { $eq: "Comedy" }
    }
  },
  { "$sort": { "year": 1 } },
  {
    "$limit": 3
  },
  {
    "$project": {
      "_id": 0,
      "title": 1,
      "genres": 1,
      "plot": 1,
      "year": 1
    },
  }
])

db.movies.aggregate([
  {
    "$search": {
      "compound": {
        "filter": [{
          "range": {
            "gte": 2000,
            "lte": 2010,
            "path": "year"
          }
        },
        {
          "text": {
            "path": "plot",
            "query": "poet"
          }
        },
        {
          "text": {
            "path": "genres",
            "query": "comedy"
          }
        }]
      }
    }
  },
  { "$sort": { "year": 1 } },
  {
    "$limit": 3
  },
  {
    "$project": {
      "_id": 0,
      "title": 1,
      "genres": 1,
      "plot": 1,
      "year": 1
    }
  }
])

这两个查询都将返回以下三个文档。

   {
  year: 2000,
  plot: 'A film poem inspired by the Peruvian poet Cèsar Vallejo. A story about our need for love, our confusion, greatness and smallness and, most of all, our vulnerability. It is a story with many...',
  genres: [ 'Comedy', 'Drama' ],
  title: 'Songs from the Second Floor'
},
{
  plot: 'When his mother, who has sheltered him his entire 40 years, dies, Elling, a sensitive, would-be poet, is sent to live in a state institution. There he meets Kjell Bjarne, a gentle giant and...',
  genres: [ 'Comedy', 'Drama' ],
  title: 'Elling',
  year: 2001
},
{
  plot: 'Heart-broken after several affairs, a woman finds herself torn between a Poet and a TV Host.',
  genres: [ 'Comedy', 'Romance', 'Drama' ],
  title: 'Easy',
  year: 2003
}

Although $text is adequate for simple, narrow searches such as this, as the size of the datasets and breadth of your queries increases, the performance advantages of $search will significantly improve the responsiveness of your applications. We recommend that you use a MongoDB Search query through the $search aggregation pipeline stage.

了解详情

To learn more about MongoDB Search queries, see Queries and Indexes.
MongoDB University offers a free course on optimizing MongoDB Performance. To learn more, see Monitoring and Insights.

1	db.movies.aggregate([
2	{
3	"$search": {
4	"text": {
5	"path": "plot",
6	"query": "poet"
7	},
8	"highlight": {
9	"path": "plot"
10	}
11	}
12	},
13	{
14	"$limit": 1
15	},
16	{
17	"$project": {
18	"_id": 0,
19	"title": 1,
20	"genres": 1,
21	"plot": 1,
22	"year": 1,
23	"highlights": { "$meta": "searchHighlights" }
24	}
25	}
26	])