Standard Analyzer

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Example

The standard analyzer is the default for all Atlas Search indexes and queries. It divides text into terms based on word boundaries, which makes it language-neutral for most use cases. It converts all terms to lower case and removes punctuation. It provides grammar-based tokenization that recognizes email addresses, acronyms, Chinese-Japanese-Korean characters, alphanumerics, and more.

You can see the tokens that the standard analyzer creates for a built-in sample document and query string when you create or edit an index in the Atlas UI Visual Editor. If you select Refine Your Index, the Atlas UI displays a section titled View text analysis of your selected index configuration within the Index Configurations section. If you expand this section, the Atlas UI displays the index and search tokens that the standard analyzer generates for each sample string.

Important

Atlas Search won't index string fields where analyzer tokens exceed 32766 bytes in size. If using the keyword analyzer, string fields which exceed 32766 bytes will not be indexed.

Example

The following example index definition specifies an index on the title field in the sample_mflix.movies collection using the standard analyzer. To follow along with this example, load the sample data on your cluster and navigate to the Create a Search Index page in the Atlas UI following the steps in the Create an Atlas Search Index tutorial. Then, select the minutes collection as your data source, and follow the example procedure to create an index in the Visual Editor or JSON editor.

Click Refine Your Index to configure your index.
In the Index Configurations section, toggle Dynamic Mapping to off.
In the Field Mappings section, click Add Field Mapping to open the Add Field Mapping window.
Click Customized Configuration.
Select title from the Field Name dropdown.
Click the Data Type dropdown and select String if it isn't already selected.

Expand String Properties and make the following changes:

Index Analyzer	Select `lucene.standard` from the dropdown if it isn't already selected.
Search Analyzer	Select `lucene.standard` from the dropdown if it isn't already selected.
Index Options	Use the default `offsets`.
Store	Use the default `true`.
Ignore Above	Keep the default setting.
Norms	Use the default `include`.

Click Add.
Click Save Changes.
Click Create Search Index.

Replace the default index definition with the following index definition.
```
{
  "mappings": {
    "fields": {
      "title": {
        "type": "string",
        "analyzer": "lucene.standard"
      }
    }
  }
}
```
Click Next.
Click Create Search Index.

The following query searches the title field for the term action and limits the output to two results.

db.movies.aggregate([
  {
    "$search": {
      "text": {
         "query": "action",
         "path": "title"
      }
    }
  },
  {
    "$limit": 2
  },
  {
    "$project": {
      "_id": 0,
      "title": 1
    }
  }
])

[
  {
    title: 'Action Jackson'
  },
  {
    title: 'Class Action'
  }
]

Atlas Search returned these documents because it matched the query term action to the token action for the documents, which Atlas Search created by doing the following for the text in the title field using the lucene.standard analyzer:

Convert the text to lowercase.
Split the text based on word boundaries and create separate tokens.

The following table shows the tokens (searchable terms) that Atlas Search creates using the Standard Analyzer and, by contrast, the tokens that Atlas Search creates for the Keyword Analyzer and Whitespace Analyzer for the documents in the results:

Title	Standard Analyzer Tokens	Keyword Analyzer Tokens	Whitespace Analyzer Tokens
`Action Jackson`	`action`, `jackson`	`Action Jackson`	`Action`, `Jackson`
`Class Action`	`class`, `action`	`Class Action`	`Class`, `Action`

If you index the field using the:

Keyword Analyzer, Atlas Search wouldn't match the documents in the results for the query term action because the keyword analyzer matches only documents in which the search term matches the entire contents of the field (Action Jackson and Class Action) exactly.
Whitespace Analyzer, Atlas Search wouldn't match the documents in the results for the query term action because the whitespace analyzer tokenizes the title field value in its original case (Action) and the query term has the lowercase action, which doesn't match the whitespace analyzer token.

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