How to Use Synonyms with Atlas Search

Navigate to the Database Deployments page for your project.

1. If it is not already displayed, select the organization that contains your desired project from the Organizations menu in the navigation bar.
2. If it is not already displayed, select your desired project from the Projects menu in the navigation bar.
3. If the Database Deployments page is not already displayed, click Databases in the sidebar.

Click your cluster's Browse Collections button.

Create the sample synonyms collection in the sample_mflix database.

1. Expand the sample_mflix database and click the icon to open the Create Collection modal.
2. Type sample_synonyms in the Collection name field.
3. Click Create to create the collection in the sample_mflix database.

Load the sample data into the sample_synonyms collection.

1. Select the sample_synonyms collection if it's already not selected.
2. Click Insert Document for each of the sample documents to add to the collection.
3. Click the JSON view ({}) to replace the default document.

4. Copy and paste the following sample documents, one at a time, and click Insert to add the documents, one at a time, to the collection.

   {
     "mappingType": "equivalent",
     "synonyms": ["car", "vehicle", "automobile"]
   }

   {
     "mappingType": "explicit",
     "input": ["boat"],
     "synonyms": ["boat", "vessel", "sail"]
   }

Navigate to the Atlas Search page for your project.

1. If it is not already displayed, select the organization that contains your desired project from the Organizations menu in the navigation bar.
2. If it is not already displayed, select your desired project from the Projects menu in the navigation bar.
3. Click your cluster's name.
4. Click the Search tab.

Click Create Index.

Select the JSON Editor Configuration Method and click Next.

The Visual Editor Configuration Method doesn't support synonym mapping definition.

Enter the Index Name, and set the Database and Collection.

1. In the Index Name field, enter default.

   Note

   If you name your index default, you don't need to specify an index parameter when using the $search pipeline stage. Otherwise, you must specify the index name using the index parameter.

2. In the Database and Collection section, find the sample_mflix database, and select the movies collection.

Replace the default index definition with the following index definition and then click Next.

{
  "mappings": {
    "dynamic": false,
    "fields": {
      "title": {
        "analyzer": "lucene.english",
        "type": "string"
      }
    }
  },
  "synonyms": [
    {
      "analyzer": "lucene.english",
      "name": "mySynonyms",
      "source": {
        "collection": "sample_synonyms"
      }
    }
  ]
}

The above index definition specifies:

• The language analyzer lucene.english as the default analyzer for both indexing and querying the title field.
• The name mySynonyms as the name for this synonym mapping.
• The sample_synonyms collection as the source synonyms collection to look for synonyms for queries using mySynonyms mapping. mySynonyms can be used in text queries over any field indexed with the lucene.english analyzer (including the title field, in this example).

Click Create Search Index.

Close the You're All Set! Modal Window.

A modal window appears to let you know your index is building. Click the Close button.

Wait for the index to finish building.

The index should take about one minute to build. While it is building, the Status column reads Build in Progress. When it is finished building, the Status column reads Active.