MongoDB Text Index Practice Questions with Solutions

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Introduction

A Text Index in MongoDB is used to efficiently search text stored in string fields. It is useful when you want to find documents containing specific words instead of matching an entire field value. In this chapter, you will practice creating text indexes, using the $text operator, searching for words and phrases, checking text indexes, and removing them. MongoDB Text Index Practice Questions with Solutions to help you understand the concepts.

Q1. Create a Text Index on a Description Field

Problem Statement

Create a text index on the description field of the products collection.

MongoDB Command / Query

db.products.createIndex({
  description: "text"
})

Expected Output

description_text

Explanation

The "text" index type tells MongoDB that the field will be used for text searching.

Q2. Insert Products for Text Searching

Problem Statement

Insert some products containing different descriptions.

MongoDB Command / Query

db.products.insertMany([
  {
    name: "Laptop",
    description: "Powerful laptop for programming and data analysis"
  },
  {
    name: "Keyboard",
    description: "Mechanical keyboard for programmers"
  },
  {
    name: "Monitor",
    description: "Large monitor for coding and office work"
  },
  {
    name: "Mouse",
    description: "Wireless mouse for everyday computer use"
  }
])

Expected Output

{
  acknowledged: true,
  insertedIds: {
    "0": ObjectId("..."),
    "1": ObjectId("..."),
    "2": ObjectId("..."),
    "3": ObjectId("...")
  }
}

Explanation

These documents provide sample text that can be searched using the text index.

Q3. Search for a Single Word

Problem Statement

Find all products whose indexed text contains the word programming.

MongoDB Command / Query

db.products.find({
  $text: {
    $search: "programming"
  }
})

Expected Output

{
  name: "Laptop",
  description: "Powerful laptop for programming and data analysis"
}

Explanation

The $text operator searches the fields covered by the text index.

Q4. Search for Another Word

Problem Statement

Find products containing the word coding.

MongoDB Command / Query

db.products.find({
  $text: {
    $search: "coding"
  }
})

Expected Output

{
  name: "Monitor",
  description: "Large monitor for coding and office work"
}

Explanation

MongoDB searches the indexed text and returns documents containing the searched term.

Q5. Search for Multiple Words

Problem Statement

Find products containing either laptop or programming.

MongoDB Command / Query

db.products.find({
  $text: {
    $search: "laptop programming"
  }
})

Expected Output

{
  name: "Laptop",
  description: "Powerful laptop for programming and data analysis"
}

Explanation

When multiple terms are supplied to $search, MongoDB performs a text search for those terms. Documents matching the search expression can be returned.

Q6. Search for an Exact Phrase

Problem Statement

Find products containing the exact phrase "data analysis".

MongoDB Command / Query

db.products.find({
  $text: {
    $search: "\"data analysis\""
  }
})

Expected Output

{
  name: "Laptop",
  description: "Powerful laptop for programming and data analysis"
}

Explanation

Double quotes inside the search string are used to search for a phrase rather than treating the words independently.

Q7. Search Using a Text Index and Return Only Selected Fields

Problem Statement

Search for programmers and display only the product name and description.

MongoDB Command / Query

db.products.find(
  {
    $text: {
      $search: "programmers"
    }
  },
  {
    _id: 0,
    name: 1,
    description: 1
  }
)

Expected Output

{
  name: "Keyboard",
  description: "Mechanical keyboard for programmers"
}

Explanation

The second argument of find() is a projection. Here, _id is hidden and only name and description are displayed.

Q8. Search Text and Sort by Relevance Score

Problem Statement

Search for programming and sort the results according to MongoDB’s text relevance score.

MongoDB Command / Query

db.products.find(
  {
    $text: {
      $search: "programming"
    }
  },
  {
    score: {
      $meta: "textScore"
    },
    _id: 0,
    name: 1,
    description: 1
  }
).sort({
  score: {
    $meta: "textScore"
  }
})

Expected Output

{
  name: "Laptop",
  description: "Powerful laptop for programming and data analysis",
  score: 1.5
}

Explanation

$meta: "textScore" provides MongoDB’s text relevance score. The exact score can vary depending on the data and search terms.

Q9. Create a Text Index on Multiple Fields

Problem Statement

Create a text index on both the name and description fields of the products collection.

MongoDB Command / Query

db.products.createIndex({
  name: "text",
  description: "text"
})

Expected Output

name_text_description_text

Explanation

A single text index can cover multiple fields. MongoDB can then search the indexed text across both name and description.

Important: A collection can have only one text index, but that text index can contain multiple fields.

Q10. View and Remove the Text Index

Problem Statement

First, display the indexes on the products collection. Then remove the text index named name_text_description_text.

MongoDB Command / Query

Check the indexes:

db.products.getIndexes()

Remove the text index:

db.products.dropIndex("name_text_description_text")

Expected Output

For getIndexes():

[
  {
    name: "_id_",
    key: {
      _id: 1
    }
  },
  {
    name: "name_text_description_text",
    key: {
      _fts: "text",
      _ftsx: 1
    }
  }
]

For dropIndex():

{
  nIndexesWas: 2,
  ok: 1
}

Explanation

getIndexes() displays the indexes in the collection, while dropIndex() removes the specified text index.

Key Takeaways

  • A Text Index is used for text searching in MongoDB.
  • Create a text index using "text" with createIndex().
  • The $text operator performs a text search.
  • $search specifies the word or phrase to search for.
  • A text index can cover multiple string fields.
  • MongoDB allows only one text index per collection.
  • Exact phrases can be searched using quotation marks inside $search.
  • $meta: "textScore" can be used to obtain text relevance scores.
  • getIndexes() displays existing indexes.
  • dropIndex() removes a specific text index.
  • Text indexes are different from normal ascending (1) and descending (-1) indexes.

FAQs

1. What is a Text Index in MongoDB?

A Text Index is a special MongoDB index that allows efficient searching of words and phrases in string fields.

2. How do you create a Text Index in MongoDB?

Use createIndex() with the "text" index type:

db.products.createIndex({
  description: "text"
})

3. How do you search using a Text Index?

Use the $text query operator with $search:

db.products.find({
  $text: {
    $search: "programming"
  }
})

4. Can MongoDB search multiple fields using one Text Index?

Yes. You can create one text index covering multiple fields:

db.products.createIndex({
  name: "text",
  description: "text"
})

5. Can a MongoDB collection have multiple Text Indexes?

No. A collection can have only one text index, although that index can cover multiple fields.

6. What is textScore in MongoDB?

textScore is MongoDB’s relevance score for a text-search result. It can be accessed using:

{
  score: {
    $meta: "textScore"
  }
}

7. How do you remove a Text Index in MongoDB?

Use dropIndex() with the index name:

db.products.dropIndex("name_text_description_text")

Written by Shubhranshu Shekhar, who has trained 20000+ students in coding.

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