wildcard

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Definition

Syntax
Options
Behavior
Examples

Definition

wildcard

The wildcard operator enables queries which use special characters in the search string that can match any character.

Character	Description
`?`	Matches any single character.
`*`	Matches 0 or more characters.
`\`	Escape character.

wildcard is a term-level operator, meaning that the query field is not analyzed. Term-level operators work well with the Keyword Analyzer, because the query field is treated as a single term, with special characters included. For an example of querying against an analyzed query field vs. a non-analyzed query field, see the analyzed field example.

Syntax

wildcard has the following syntax:

{
  $search: {
    "index": <index name>, // optional, defaults to "default"
    "wildcard": {
      "query": "<search-string>",
      "path": "<field-to-search>",
      "allowAnalyzedField": <boolean>,
      "score": <options>
    }
  }
}

Options

wildcard uses the following terms to construct a query:

Field	Type	Description	Necessity	Default
`query`	string or array of strings	String or strings to search for.	yes
`path`	string or array of strings	Indexed field or fields to search. You can also specify a wildcard path to search. See path construction for more information.	yes
`allowAnalyzedField`	boolean	Must be set to `true` if the query is run against an analyzed field.	no	`false`
`score`	object	Modify the score assigned to matching search term results. Options are: `boost`: multiply the result score by the given number. `constant`: replace the result score with the given number. `function`: replace the result score using the given expression. For information on using `score` in your query, see Score the Documents in the Results.	no

Behavior

wildcard is a term-level operator, meaning that the query field is not analyzed. It is possible to use the wildcard operator to perform searches on a field analyzed during indexing by setting the allowAnalyzedField option to true, but results will reflect that the query text is not analyzed.

Example

Suppose that a field foo bar baz is indexed with the standard analyzer. Atlas Search analyzes and indexes the field as foo, bar and baz. Searching for foo bar* on this field finds nothing, because the wildcard operator treats foo bar* as a single search term with a wildcard at the end. In other words, Atlas Search searches the field for any term that begins with foo bar but finds nothing, because no term exists.

Example

Searching for *Star Trek* on a field indexed with the keyword analyzer finds all documents in which the field contains the string Star Trek in any context. Searching for *Star Trek* on a field indexed with the standard analyzer finds nothing, because there is a space between Star and Trek, and the index contains no spaces.

Escape Character Behavior

When using the escape character in mongosh or with a driver, you must use a double backslash before the character to be escaped.

Example

To create a wildcard expression which searches for any string containing a literal asterisk in an aggregation pipeline, use the following expression:

"*\\**"

The first and last asterisks act as wildcards which match any characters, and the \\* matches a literal asterisk.

Note

Use the following expression to escape a literal backslash:

"*\\\*"

➤ Use the Select your language drop-down menu to set the language of the examples on this page.

Examples

The following examples use the movies collection in the sample_mflix database with a custom index definition that uses the keyword analyzer. If you have the sample dataset on your cluster, you can create an Atlas Search index on the movies collection and run the example queries on your cluster.

Tip

If you've already loaded the sample dataset, follow the Get Started with Atlas Search tutorial to create an index definition and run Atlas Search queries.

To view and edit query syntax in the Search Tester:

In Atlas, go to the Clusters page for your project.

If it's not already displayed, select the organization that contains your desired project from the Organizations menu in the navigation bar.
If it's not already displayed, select your desired project from the Projects menu in the navigation bar.
If it's not already displayed, click Clusters in the sidebar.
The Clusters page displays.

Go to the Atlas Search page for your cluster.

You can go the Atlas Search page from the sidebar, the Data Explorer, or your cluster details page.

In the sidebar, click Atlas Search under the Services heading.
From the Select data source dropdown, select your cluster and click Go to Atlas Search.
The Atlas Search page displays.

Click the Browse Collections button for your cluster.
Expand the database and select the collection.
Click the Search Indexes tab for the collection.
The Atlas Search page displays.

Click the cluster's name.
Click the Atlas Search tab.
The Atlas Search page displays.

View and edit the query syntax.

Click the Query button to the right of the index to query.
Click Edit Query to view a default query syntax sample in JSON format.

Run the following command at mongosh prompt to use the sample_mflix database:

use sample_mflix

Index Definition

The following index definition indexes the title field in the movies collection with the keyword analyzer:

1 {
2   "mappings": {
3     "fields": {
4       "title": {
5         "analyzer": "lucene.keyword",
6         "type": "string"
7       }
8     }
9   }
10 }

The following example searches all title fields for movie titles that begin with Green D, followed by any number of other characters.

Copy and paste the following query into the Query Editor, and then click the Search button in the Query Editor.

[
  {
    $search: {
      "wildcard": {
        "path": "title",
        "query": "Green D*"
      }
    }
  }
]

db.movies.aggregate([
  {
    "$search": {
      "wildcard": {
        "path": "title",
        "query": "Green D*"
      }
    }
  },
  {
    "$project": {
      "_id": 0,
      "title": 1
    }
  }
])

In the Aggregations tab of the movies collection, configure each of the following pipeline stages by selecting the stage from the dropdown and adding the query for that stage. Click Add Stage to add additional stages.

Pipeline Stage

Query

$search

{
  "wildcard": {
    "query": "Green D*",
    "path": "title"
  }
}

$project

{
  "_id": 0,
  "title": 1,
}

using MongoDB.Bson;
using MongoDB.Bson.Serialization.Attributes;
using MongoDB.Bson.Serialization.Conventions;
using MongoDB.Driver;
using MongoDB.Driver.Search;
public class WildcardSingleCharacter
{
    private const string MongoConnectionString = "<connection-string>";
    public static void Main(string[] args)
    {
        // allow automapping of the camelCase database fields to our MovieDocument
        var camelCaseConvention = new ConventionPack { new CamelCaseElementNameConvention() };
        ConventionRegistry.Register("CamelCase", camelCaseConvention, type => true);
        // connect to your Atlas cluster
        var mongoClient = new MongoClient(MongoConnectionString);
        var mflixDatabase = mongoClient.GetDatabase("sample_mflix");
        var moviesCollection = mflixDatabase.GetCollection<MovieDocument>("movies");
        // define and run pipeline
        var results = moviesCollection.Aggregate()
            .Search(Builders<MovieDocument>.Search.Wildcard(movie => movie.Title, "Green D*"))
            .Project<MovieDocument>(Builders<MovieDocument>.Projection
                .Include(movie => movie.Title)
                .Exclude(movie => movie.Id))
            .ToList();
        // print results
        foreach (var movie in results)
        {
            Console.WriteLine(movie.ToJson());
        }
    }
}
[BsonIgnoreExtraElements]
public class MovieDocument
{
    [BsonIgnoreIfDefault]
    public ObjectId Id { get; set; }
    public string Title { get; set; }
}

package main
import (
	"context"
	"fmt"
	"go.mongodb.org/mongo-driver/bson"
	"go.mongodb.org/mongo-driver/mongo"
	"go.mongodb.org/mongo-driver/mongo/options"
)
func main() {
	// connect to your Atlas cluster
	client, err := mongo.Connect(context.TODO(), options.Client().ApplyURI("<connection-string>"))
	if err != nil {
		panic(err)
	}
	defer client.Disconnect(context.TODO())
	// set namespace
	collection := client.Database("sample_mflix").Collection("movies")
	// define pipeline stages
	searchStage := bson.D{{"$search", bson.D{{"wildcard", bson.D{{"path", "title"}, {"query", "Green D*"}}}}}}
	projectStage := bson.D{{"$project", bson.D{{"title", 1}, {"_id", 0}}}}
	// run pipeline
	cursor, err := collection.Aggregate(context.TODO(), mongo.Pipeline{searchStage, projectStage})
	if err != nil {
		panic(err)
	}
	// print results
	var results []bson.D
	if err = cursor.All(context.TODO(), &results); err != nil {
		panic(err)
	}
	for _, result := range results {
		fmt.Println(result)
	}
}

import static com.mongodb.client.model.Filters.eq;
import static com.mongodb.client.model.Aggregates.project;
import static com.mongodb.client.model.Projections.excludeId;
import static com.mongodb.client.model.Projections.fields;
import static com.mongodb.client.model.Projections.include;
import com.mongodb.client.MongoClient;
import com.mongodb.client.MongoClients;
import com.mongodb.client.MongoCollection;
import com.mongodb.client.MongoDatabase;
import org.bson.Document;
import java.util.Arrays;
public class WildcardSingleCharacter {
    public static void main(String[] args) {
        // connect to your Atlas cluster
        String uri = "<connection-string>";
        try (MongoClient mongoClient = MongoClients.create(uri)) {
            // set namespace
            MongoDatabase database = mongoClient.getDatabase("sample_mflix");
            MongoCollection<Document> collection = database.getCollection("movies");
            
            // define pipeline
            Document agg = new Document("query", "Green D*").append("path", "title");
            // run pipeline and print results
            collection.aggregate(Arrays.asList(
                eq("$search", eq("wildcard", agg)),
                project(fields(excludeId(), include("title"))))).forEach(doc -> System.out.println(doc.toJson()));
        }
    }
}

import com.mongodb.client.model.Aggregates.project
import com.mongodb.client.model.Filters.eq
import com.mongodb.client.model.Projections.*
import com.mongodb.kotlin.client.coroutine.MongoClient
import kotlinx.coroutines.runBlocking
import org.bson.Document
fun main() {
    val uri = "<connection-string>"
    val mongoClient = MongoClient.create(uri)
    val database = mongoClient.getDatabase("sample_mflix")
    val collection = database.getCollection<Document>("movies")
    runBlocking {
        val agg = Document("query", "Green D*").append("path", "title")
        val resultsFlow = collection.aggregate<Document>(
            listOf(
                eq("\$search", eq("wildcard", agg)),
                project(fields(
                    excludeId(),
                    include("title")
                ))
            )
        )
        resultsFlow.collect { println(it) }
    }
    mongoClient.close()
}

const { MongoClient } = require("mongodb");
// connect to your Atlas cluster
const uri =
    "<connection-string>";
const client = new MongoClient(uri);
async function run() {
    try {
        await client.connect();
        // set namespace
        const database = client.db("sample_mflix");
        const coll = database.collection("movies");
        // define pipeline
        const agg = [
            {$search: {wildcard: {query: "Green D*", path: "title"}}},
            {$project: {_id: 0, title: 1}},
        ];
        // run pipeline
        const result = await coll.aggregate(agg);
        // print results
        await result.forEach((doc) => console.log(doc));
    } finally {
        await client.close();
    }
}
run().catch(console.dir);

import pymongo
# connect to your Atlas cluster
client = pymongo.MongoClient('<connection-string>')
# define pipeline
pipeline = [
    {"$search": {"wildcard": {"query": "Green D*", "path": "title"}}},
    {"$project": {"_id": 0, "title": 1}},
]
# run pipeline
result = client["sample_mflix"]["movies"].aggregate(pipeline)
# print results
for i in result:
    print(i)

The above query returns the following results:

SCORE: 1  _id:  "573a1393f29313caabcddaf5"
  plot: "Sophie loved Edmund, but he left town when her parents forced her to m…"
  genres: Array
  runtime: 141
SCORE: 1  _id:  "573a13a2f29313caabd0a4e4"
  plot: "The story of some Vietnamese refugees as they first arrive at Camp Pen…"
  genres: Array
  runtime: 115

The Search Tester might not display all the fields in the documents it returns. To view all the fields, including the field that you specify in the query path, expand the document in the results.

{ "title" : "Green Dolphin Street" }
{ "title" : "Green Dragon" }

{ "title" : "Green Dolphin Street" }
{ "title" : "Green Dragon" }

{ "title" : "Green Dolphin Street" }
{ "title" : "Green Dragon" }

[{title Green Dolphin Street}]
[{title Green Dragon}]

{"title": "Green Dolphin Street"}
{"title": "Green Dragon"}

Document{{title=Green Dolphin Street}}
Document{{title=Green Dragon}}

{ title: 'Green Dolphin Street' }
{ title: 'Green Dragon' }

{'title': 'Green Dolphin Street'}
{'title': 'Green Dragon'}

The following example searches all title fields for movie titles that begin with the string Wom?n (where ? may be any single character), followed by a space and then any number of additional characters.

Copy and paste the following query into the Query Editor, and then click the Search button in the Query Editor.

[
  {
    $search: {
      "wildcard": {
        "path": "title",
        "query": "Wom?n *"
      }
    }
  }
]

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

db.movies.aggregate([
  {
    "$search": {
      "wildcard": {
        "path": "title",
        "query": "Wom?n *"
      }
    }
  },
  {
    "$limit": 5
  },
  {
    "$project": {
      "_id": 0,
      "title": 1
    }
  }
])

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

Pipeline Stage

Query

$search

{
  "wildcard": {
    "query": "Wom?n *",
    "path": "title"
  }
}

$limit

$project

{
  "_id": 0,
  "title": 1,
}

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

using MongoDB.Bson;
using MongoDB.Bson.Serialization.Attributes;
using MongoDB.Bson.Serialization.Conventions;
using MongoDB.Driver;
using MongoDB.Driver.Search;
public class WildcardMultipleCharacter
{
    private const string MongoConnectionString = "<connection-string>";
    public static void Main(string[] args)
    {
        // allow automapping of the camelCase database fields to our MovieDocument
        var camelCaseConvention = new ConventionPack { new CamelCaseElementNameConvention() };
        ConventionRegistry.Register("CamelCase", camelCaseConvention, type => true);
        // connect to your Atlas cluster
        var mongoClient = new MongoClient(MongoConnectionString);
        var mflixDatabase = mongoClient.GetDatabase("sample_mflix");
        var moviesCollection = mflixDatabase.GetCollection<MovieDocument>("movies");
        // define and run pipeline
        var results = moviesCollection.Aggregate()
            .Search(Builders<MovieDocument>.Search.Wildcard(movie => movie.Title, "Wom?n *"))
            .Project<MovieDocument>(Builders<MovieDocument>.Projection
                .Include(movie => movie.Title)
                .Exclude(movie => movie.Id))
            .Limit(5)
            .ToList();
        // print results
        foreach (var movie in results)
        {
            Console.WriteLine(movie.ToJson());
        }
    }
}
[BsonIgnoreExtraElements]
public class MovieDocument
{
    [BsonIgnoreIfDefault]
    public ObjectId Id { get; set; }
    public string Title { get; set; }
}

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

package main
import (
	"context"
	"fmt"
	"go.mongodb.org/mongo-driver/bson"
	"go.mongodb.org/mongo-driver/mongo"
	"go.mongodb.org/mongo-driver/mongo/options"
)
func main() {
	// connect to your Atlas cluster
	client, err := mongo.Connect(context.TODO(), options.Client().ApplyURI("<connection-string>"))
	if err != nil {
		panic(err)
	}
	defer client.Disconnect(context.TODO())
	// set namespace
	collection := client.Database("sample_mflix").Collection("movies")
	// define pipeline stages
	searchStage := bson.D{{"$search", bson.D{{"wildcard", bson.D{{"path", "title"}, {"query", "Wom?n *"}}}}}}
	limitStage := bson.D{{"$limit", 5}}
	projectStage := bson.D{{"$project", bson.D{{"title", 1}, {"_id", 0}}}}
	// run pipeline
	cursor, err := collection.Aggregate(context.TODO(), mongo.Pipeline{searchStage, limitStage, projectStage})
	if err != nil {
		panic(err)
	}
	// print results
	var results []bson.D
	if err = cursor.All(context.TODO(), &results); err != nil {
		panic(err)
	}
	for _, result := range results {
		fmt.Println(result)
	}
}

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

import static com.mongodb.client.model.Filters.eq;
import static com.mongodb.client.model.Aggregates.limit;
import static com.mongodb.client.model.Aggregates.project;
import static com.mongodb.client.model.Projections.excludeId;
import static com.mongodb.client.model.Projections.fields;
import static com.mongodb.client.model.Projections.include;
import com.mongodb.client.MongoClient;
import com.mongodb.client.MongoClients;
import com.mongodb.client.MongoCollection;
import com.mongodb.client.MongoDatabase;
import org.bson.Document;
import java.util.Arrays;
public class WildcardMultiCharacter {
    public static void main(String[] args) {
        // connect to your Atlas cluster
        String uri = "<connection-string>";
        try (MongoClient mongoClient = MongoClients.create(uri)) {
            // set namespsace
            MongoDatabase database = mongoClient.getDatabase("sample_mflix");
            MongoCollection<Document> collection = database.getCollection("movies");
            // define pipeline
            Document agg = new Document("query", "Wom?n *").append("path", "title");
            // run pipeline and print results
            collection.aggregate(Arrays.asList(
                eq("$search", eq("wildcard", agg)),
                limit(5),
                project(fields(excludeId(), include("title"))))).forEach(doc -> System.out.println(doc.toJson()));
        }
    }
}

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

import com.mongodb.client.model.Aggregates.limit
import com.mongodb.client.model.Aggregates.project
import com.mongodb.client.model.Filters.eq
import com.mongodb.client.model.Projections.*
import com.mongodb.kotlin.client.coroutine.MongoClient
import kotlinx.coroutines.runBlocking
import org.bson.Document
fun main() {
    val uri = "<connection-string>"
    val mongoClient = MongoClient.create(uri)
    val database = mongoClient.getDatabase("sample_mflix")
    val collection = database.getCollection<Document>("movies")
    runBlocking {
        val agg = Document("query", "Wom?n *").append("path", "title")
        val resultsFlow = collection.aggregate<Document>(
            listOf(
                eq("\$search", eq("wildcard", agg)),
                limit(5),
                project(fields(
                    excludeId(),
                    include("title")
                ))
            )
        )
        resultsFlow.collect { println(it) }
    }
    mongoClient.close()
}

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

const { MongoClient } = require("mongodb");
// connect to your Atlas cluster
const uri =
    "<connection-string>";
const client = new MongoClient(uri);
async function run() {
    try {
        await client.connect();
        // set namespace
        const database = client.db("sample_mflix");
        const coll = database.collection("movies");
        // define pipeline
        const agg = [
            {$search: {wildcard: {query: "Wom?n *", path: "title"}}},
            {$limit: 5},
            {$project: {_id: 0,title: 1}}
        ];
        // run pipeline
        const result = await coll.aggregate(agg);
        // print results
        await result.forEach((doc) => console.log(doc));
    } finally {
        await client.close();
    }
}
run().catch(console.dir);

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

import pymongo
# connect to your Atlas cluster
client = pymongo.MongoClient('<connection-string>')
# define pipeline
pipeline = [
    {"$search": {"wildcard": {"query": "Wom?n *", "path": "title"}}},
    {"$limit": 5},
    {"$project": {"_id": 0, "title": 1}},
]
# run pipeline
result = client["sample_mflix"]["movies"].aggregate(pipeline)
# print results
for i in result:
    print(i)

The above query returns the following results:

SCORE: 1  _id:  "573a1393f29313caabcdcbdd"
  plot: "Rival reporters Sam and Tess fall in love and get married, only to fin…"
  genres: Array
  runtime: 114
SCORE: 1  _id:  "573a1394f29313caabce08c6"
  plot: "A married, middle-aged woman is shocked to discover that her husband, …"
  genres: Array
  runtime: 93
SCORE: 1  _id:  "573a1395f29313caabce254c"
  plot: "An entomologist searching for insects by the seaside is trapped by loc…"
  genres: Array
  runtime: 123
SCORE: 1  _id:  "573a1396f29313caabce42e5"
  plot: "The battle of the sexes and relationships among the elite of Britian's…"
  genres: Array
  runtime: 131
SCORE: 1  _id:  "573a1398f29313caabceb06d"
  fullplot: "A woman's lover leaves her, and she tries to contact him to find out w…"
  imdb: Object
  year: 1988
SCORE: 1  _id:  "573a139df29313caabcf9c83"
  plot: "A new woman comes between a widower and his adult son."
  genres: Array
  runtime: 110
SCORE: 1  _id:  "573a13a0f29313caabd050bf"
  fullplot: "Isabella is a great cook, making her husband's restaurant in Bahia, Br…"
  imdb: Object
  year: 2000
SCORE: 1  _id:  "573a13aaf29313caabd22c05"
  countries: Array
  genres: Array
  runtime: 115
SCORE: 1  _id:  "573a13aef29313caabd2d899"
  countries: Array
  genres: Array
  runtime: 72
SCORE: 1  _id:  "573a13aff29313caabd32566"
  fullplot: "An adaptation of Bishop T.D. Jakes' self-help novel, chronciling a wom…"
  imdb: Object
  year: 2004

The Search Tester might not display all the fields in the documents it returns. To view all the fields, including the field that you specify in the query path, expand the document in the results.

{ "title" : "Woman of the Year" }
{ "title" : "Woman in a Dressing Gown" }
{ "title" : "Woman in the Dunes" }
{ "title" : "Women in Love" }
{ "title" : "Women on the Verge of a Nervous Breakdown" }

{ "title" : "Woman of the Year" }
{ "title" : "Woman in a Dressing Gown" }
{ "title" : "Woman in the Dunes" }
{ "title" : "Women in Love" }
{ "title" : "Women on the Verge of a Nervous Breakdown" }

{ "title" : "Woman of the Year" }
{ "title" : "Woman in a Dressing Gown" }
{ "title" : "Woman in the Dunes" }
{ "title" : "Women in Love" }
{ "title" : "Women on the Verge of a Nervous Breakdown" }

[{title Woman of the Year}]
[{title Woman in a Dressing Gown}]
[{title Woman in the Dunes}]
[{title Women in Love}]
[{title Women on the Verge of a Nervous Breakdown}]

{"title": "Woman of the Year"}
{"title": "Woman in a Dressing Gown"}
{"title": "Woman in the Dunes"}
{"title": "Women in Love"}
{"title": "Women on the Verge of a Nervous Breakdown"}

Document{{title=Woman in the Meadow}}
Document{{title=Woman on the Beach}}
Document{{title=Woman in Love}}
Document{{title=Woman of the Year}}
Document{{title=Woman in a Dressing Gown}}

{ title: 'Woman of the Year' }
{ title: 'Woman in a Dressing Gown' }
{ title: 'Woman in the Dunes' }
{ title: 'Women in Love' }
{ title: 'Women on the Verge of a Nervous Breakdown' }

{'title': 'Woman of the Year'}
{'title': 'Woman in a Dressing Gown'}
{'title': 'Woman in the Dunes'}
{'title': 'Women in Love'}
{'title': 'Women on the Verge of a Nervous Breakdown'}

Escape Character Example

The following example searches for documents in which the title field ends with a question mark.

Note

The following example is intended to run in mongosh. For more information about using the escape characters with a driver, see Escape Character Behavior.

The * character in the query field matches any characters, and the \\? string matches a literal question mark.

Copy and paste the following query into the Query Editor, and then click the Search button in the Query Editor.

[
  {
    $search: {
      "wildcard": {
        "path": "title",
        "query": "*\\?"
      }
    }
  }
]

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

db.movies.aggregate([
  {
    "$search": {
      "wildcard": {
        "path": "title",
        "query": "*\\?"
      }
    }
  },
  {
    "$limit": 5
  },
  {
    "$project": {
      "_id": 0,
      "title": 1
    }
  }
])

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

Pipeline Stage

Query

$search

{
  "wildcard": {
    "query": "*\\?",
    "path": "title"
  }
}

$limit

$project

{
  "_id": 0,
  "title": 1,
}

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

using MongoDB.Bson;
using MongoDB.Bson.Serialization.Attributes;
using MongoDB.Bson.Serialization.Conventions;
using MongoDB.Driver;
using MongoDB.Driver.Search;
public class WildcardEscapeCharacter
{
    private const string MongoConnectionString = "<connection-string>";
    public static void Main(string[] args)
    {
        // allow automapping of the camelCase database fields to our MovieDocument
        var camelCaseConvention = new ConventionPack { new CamelCaseElementNameConvention() };
        ConventionRegistry.Register("CamelCase", camelCaseConvention, type => true);
        // connect to your Atlas cluster
        var mongoClient = new MongoClient(MongoConnectionString);
        var mflixDatabase = mongoClient.GetDatabase("sample_mflix");
        var moviesCollection = mflixDatabase.GetCollection<MovieDocument>("movies");
        // define and run pipeline
        var results = moviesCollection.Aggregate()
            .Search(Builders<MovieDocument>.Search.Wildcard(movie => movie.Title, "*\\?"))
            .Project<MovieDocument>(Builders<MovieDocument>.Projection
                .Include(movie => movie.Title)
                .Exclude(movie => movie.Id))
            .Limit(5)
            .ToList();
        // print results
        foreach (var movie in results)
        {
            Console.WriteLine(movie.ToJson());
        }
    }
}
[BsonIgnoreExtraElements]
public class MovieDocument
{
    [BsonIgnoreIfDefault]
    public ObjectId Id { get; set; }
    public string Title { get; set; }
}

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

package main
import (
	"context"
	"fmt"
	"go.mongodb.org/mongo-driver/bson"
	"go.mongodb.org/mongo-driver/mongo"
	"go.mongodb.org/mongo-driver/mongo/options"
)
func main() {
	// connect to your Atlas cluster
	client, err := mongo.Connect(context.TODO(), options.Client().ApplyURI("<connection-string>"))
	if err != nil {
		panic(err)
	}
	defer client.Disconnect(context.TODO())
	// set namespace
	collection := client.Database("sample_mflix").Collection("movies")
	// define pipeline stages
	searchStage := bson.D{{"$search", bson.D{{"wildcard", bson.D{{"path", "title"}, {"query", "*\\?"}}}}}}
	limitStage := bson.D{{"$limit", 5}}
	projectStage := bson.D{{"$project", bson.D{{"title", 1}, {"_id", 0}}}}
	// run pipeline
	cursor, err := collection.Aggregate(context.TODO(), mongo.Pipeline{searchStage, limitStage, projectStage})
	if err != nil {
		panic(err)
	}
	// print results
	var results []bson.D
	if err = cursor.All(context.TODO(), &results); err != nil {
		panic(err)
	}
	for _, result := range results {
		fmt.Println(result)
	}
}

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

import static com.mongodb.client.model.Filters.eq;
import static com.mongodb.client.model.Aggregates.limit;
import static com.mongodb.client.model.Aggregates.project;
import static com.mongodb.client.model.Projections.excludeId;
import static com.mongodb.client.model.Projections.fields;
import static com.mongodb.client.model.Projections.include;
import com.mongodb.client.MongoClient;
import com.mongodb.client.MongoClients;
import com.mongodb.client.MongoCollection;
import com.mongodb.client.MongoDatabase;
import org.bson.Document;
import java.util.Arrays;
public class WildcardEscapeCharacter {
    public static void main(String[] args) {
        // connect to your Atlas cluster
        String uri = "<connection-string>";
        try (MongoClient mongoClient = MongoClients.create(uri)) {
            // set namespace
            MongoDatabase database = mongoClient.getDatabase("sample_mflix");
            MongoCollection<Document> collection = database.getCollection("movies");
            
            // define pipeline
            Document agg = new Document("query", "*\\?").append("path", "title");
            // run pipeline and print results
            collection.aggregate(Arrays.asList(
                eq("$search", eq("wildcard", agg)),
                limit(5),
                project(fields(excludeId(), include("title"))))).forEach(doc -> System.out.println(doc.toJson()));
        }
    }
}

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

import com.mongodb.client.model.Aggregates.limit
import com.mongodb.client.model.Aggregates.project
import com.mongodb.client.model.Filters.eq
import com.mongodb.client.model.Projections.*
import com.mongodb.kotlin.client.coroutine.MongoClient
import kotlinx.coroutines.runBlocking
import org.bson.Document
fun main() {
    val uri = "<connection-string>"
    val mongoClient = MongoClient.create(uri)
    val database = mongoClient.getDatabase("sample_mflix")
    val collection = database.getCollection<Document>("movies")
    runBlocking {
        val agg = Document("query", "*\\?").append("path", "title")
        val resultsFlow = collection.aggregate<Document>(
            listOf(
                eq("\$search", eq("wildcard", agg)),
                limit(5),
                project(fields(
                    excludeId(),
                    include("title")
                ))
            )
        )
        resultsFlow.collect { println(it) }
    }
    mongoClient.close()
}

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

const { MongoClient } = require("mongodb");
// connect to your Atlas cluster
const uri =
    "<connection-string>";
const client = new MongoClient(uri);
async function run() {
    try {
        await client.connect();
        // set namespace
        const database = client.db("sample_mflix");
        const coll = database.collection("movies");
        // define pipeline
        const agg = [
            {$search: {wildcard: {query: "*\\?", path: "title"}}},
            {$limit: 5},
            {$project: {_id: 0,title: 1}}
        ];
        // run pipeline
        const result = await coll.aggregate(agg);
        // print results
        await result.forEach((doc) => console.log(doc));
    } finally {
        await client.close();
    }
}
run().catch(console.dir);

The $limit stage limits the results to 5 documents, while the $project stage limits the results to only the title field.

import pymongo
# connect to your Atlas cluster
client = pymongo.MongoClient('<connection-string>')
# define pipeline
pipeline = [
    {"$search": {"wildcard": {"query": "*\\?", "path": "title"}}},
    {"$limit": 5},
    {"$project": {"_id": 0, "title": 1}},
]
# run pipeline
result = client["sample_mflix"]["movies"].aggregate(pipeline)
# print results
for i in result:
    print(i)

The above query returns the following results:

SCORE: 1  _id:  "573a1390f29313caabcd5ea4"
  plot: "A District Attorney's outspoken stand on abortion gets him in trouble …"
  genres: Array
  runtime: 62
SCORE: 1  _id:  "573a1392f29313caabcdab4a"
  plot: "Robin is crooning to a Mae West-like Jenny Wren when he is shot with a…"
  genres: Array
  runtime: 8
SCORE: 1  _id:  "573a1394f29313caabce08ab"
  plot: "Elmer Fudd is again hunting rabbits - only this time it's an opera. Wa…"
  genres: Array
  runtime: 7
SCORE: 1  _id:  "573a1394f29313caabce08c8"
  plot: "To save his career, an ad man wants a sex symbol to endorse a lipstick…"
  genres: Array
  runtime: 93
SCORE: 1  _id:  "573a1395f29313caabce1555"
  plot: "In order to get back into the good graces with his wife with whom he h…"
  genres: Array
  runtime: 115
SCORE: 1  _id:  "573a1395f29313caabce1dce"
  plot: "A former child star torments her crippled sister in a decaying Hollywo…"
  genres: Array
  runtime: 134
SCORE: 1  _id:  "573a1395f29313caabce2422"
  plot: "Roger Willoughby is considered to be a leading expert on sports fishin…"
  genres: Array
  runtime: 120
SCORE: 1  _id:  "573a1395f29313caabce2d63"
  plot: "The true story of the departure of the German occupiers from Paris in …"
  genres: Array
  runtime: 173
SCORE: 1  _id:   "573a1395f29313caabce2db5"
  plot: "In this excoriating satire of the fashion industry, Polly Maggoo is a …"
  genres: Array
  runtime: 101
SCORE: 1  _id:   "573a1395f29313caabce2ecc"
  plot: "A bitter aging couple with the help of alcohol, use a young couple to …"
  genres: Array
  runtime: 131

The Search Tester might not display all the fields in the documents it returns. To view all the fields, including the field that you specify in the query path, expand the document in the results.

{ "title" : "Where Are My Children?" }
{ "title" : "Who Killed Cock Robin?" }
{ "title" : "What's Opera, Doc?" }
{ "title" : "Will Success Spoil Rock Hunter?" }
{ "title" : "Who Was That Lady?" }

{ "title" : "Where Are My Children?" }
{ "title" : "Who Killed Cock Robin?" }
{ "title" : "What's Opera, Doc?" }
{ "title" : "Will Success Spoil Rock Hunter?" }
{ "title" : "Who Was That Lady?" }

{ "title" : "Where Are My Children?" }
{ "title" : "Who Killed Cock Robin?" }
{ "title" : "What's Opera, Doc?" }
{ "title" : "Will Success Spoil Rock Hunter?" }
{ "title" : "Who Was That Lady?" }

[{title Where Are My Children?}]
[{title Who Killed Cock Robin?}]
[{title What's Opera, Doc?}]
[{title Will Success Spoil Rock Hunter?}]
[{title Who Was That Lady?}]

{"title": "Where Are My Children?"}
{"title": "Who Killed Cock Robin?"}
{"title": "What's Opera, Doc?"}
{"title": "Will Success Spoil Rock Hunter?"}
{"title": "Who Was That Lady?"}

Document{{title=Who Are You, Polly Magoo?}}
Document{{title=Where Were You When the Lights Went Out?}}
Document{{title=Why Does Herr R. Run Amok?}}
Document{{title=What's Up, Doc?}}
Document{{title=Who Is Killing the Great Chefs of Europe?}}

{ title: 'Where Are My Children?' }
{ title: 'Who Killed Cock Robin?' }
{ title: "What's Opera, Doc?" }
{ title: 'Will Success Spoil Rock Hunter?' }
{ title: 'Who Was That Lady?' }

{'title': 'Where Are My Children?'}
{'title': 'Who Killed Cock Robin?'}
{'title': "What's Opera, Doc?"}
{'title': 'Will Success Spoil Rock Hunter?'}
{'title': 'Who Was That Lady?'}

Back

text

3. Construct Query Path

1	{
2	"mappings": {
3	"fields": {
4	"title": {
5	"analyzer": "lucene.keyword",
6	"type": "string"
7	}
8	}
9	}
10	}