Text indexes for search in MongoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

Find documents matching a text search

Given a MongoDB collection articles with a text index on the content field, what will be the output of this query?

db.articles.find({ $text: { $search: "coffee" } })

Assume the collection has these documents:

[{ _id: 1, content: "I love coffee and tea." }, { _id: 2, content: "Tea is great." }, { _id: 3, content: "Coffee is energizing." }]

MongoDB

db.articles.find({ $text: { $search: "coffee" } })

A [{ _id: 2, content: "Tea is great." }]

B [{ _id: 1, content: "I love coffee and tea." }, { _id: 3, content: "Coffee is energizing." }]

C [{ _id: 1, content: "I love coffee and tea." }, { _id: 2, content: "Tea is great." }, { _id: 3, content: "Coffee is energizing." }]

D []

💡 Hint

Text search matches documents containing the search word in the indexed fields.

The text search for "coffee" matches documents where the content field contains the word "coffee" (case-insensitive). Documents 1 and 3 contain "coffee", document 2 does not.

🧠 Conceptual

intermediate

Understanding text index weights

In MongoDB, when creating a text index on multiple fields with different weights, what effect do the weights have on text search results?

A Weights specify the maximum length of words indexed in each field.

B Weights determine how many times a word must appear in a field to be indexed.

C Weights limit the number of documents returned by the text search query.

D Fields with higher weights contribute more to the relevance score, making documents with matches in those fields rank higher.

💡 Hint

Think about how search results are ranked by relevance.

Weights assign importance to fields so that matches in higher weighted fields increase the document's relevance score, affecting the order of results.

📝 Syntax

advanced

Correct syntax for creating a text index on multiple fields

Which of the following commands correctly creates a text index on the fields title and description in a MongoDB collection products?

A db.products.createIndex({ title: text, description: text })

B db.products.createIndex({ title: 'text', description: 'text' })

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

D db.products.createIndex({ title: text(), description: text() })

💡 Hint

Text index type must be a string.

The correct syntax uses strings "text" to specify the index type for each field. Option C uses double quotes correctly. Option C uses single quotes which is valid in JavaScript but double quotes are preferred for consistency.

❓ optimization

advanced

Improving text search performance with index filters

You have a large MongoDB collection with a text index on the comments field. You want to speed up text searches by limiting the index to documents where status is "active". Which approach achieves this?

A Create a partial text index with a filter: db.collection.createIndex({ comments: "text" }, { partialFilterExpression: { status: "active" } })

B Add a regular index on the status field only.

C Use a text index on comments and filter status in the query without index changes.

D Create a compound index on { status: 1, comments: "text" }.

💡 Hint

Partial indexes index only documents matching a filter.

Partial text indexes index only documents matching the filter, reducing index size and improving search speed for queries filtering on status.

🔧 Debug

expert

Why does this text search query return no results?

You created a text index on the summary field of a MongoDB collection. You run this query:

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

But it returns no documents. Why?

A The $search string is empty, so no terms to match; the query returns no results.

B Text indexes require the $search string to be at least 3 characters long.

C The text index was not created properly and is missing.

D MongoDB does not support text search on the summary field.

💡 Hint

Think about what an empty search string means for matching.

An empty $search string means no search terms are provided, so no documents match the query.

Practice

1. What is the main purpose of creating a text index in MongoDB?

easy

A. To encrypt text data for security

B. To enable fast searching of text within string fields

C. To store large text files inside the database

D. To sort documents by text fields alphabetically

Solution

1. Step 1: Understand what a text index does

   A text index allows MongoDB to quickly search text inside string fields of documents.

2. Step 2: Compare options with the purpose

   Sorting, storing files, or encrypting are not functions of text indexes.

3. Final Answer:

   To enable fast searching of text within string fields -> Option B

4. Quick Check:

   Text index = fast text search [OK]

Hint: Text index = fast search inside text fields [OK]

Common Mistakes:

• Confusing text index with sorting index
• Thinking text index stores files
• Assuming text index encrypts data

2. Which of the following is the correct syntax to create a text index on the description field in a MongoDB collection named products?

easy

A. db.products.createTextIndex({ description: 1 })

B. db.products.createIndex({ description: 'string' })

C. db.products.createIndex({ description: 'text' })

D. db.products.createIndex({ description: 1 })

Solution

1. Step 1: Recall the syntax for creating a text index

   The correct method is createIndex with the field set to 'text' type.

2. Step 2: Check each option

   db.products.createIndex({ description: 'text' }) uses createIndex with { description: 'text' }, which is correct. Others use wrong methods or types.

3. Final Answer:

   db.products.createIndex({ description: 'text' }) -> Option C

4. Quick Check:

   Use createIndex with 'text' type [OK]

Hint: Use createIndex({field: 'text'}) to make text index [OK]

Common Mistakes:

• Using 'string' instead of 'text' for index type
• Using createTextIndex (not a valid method)
• Creating normal ascending index (1) instead of text

3. Given a collection articles with a text index on fields title and content, what will the following query return?

db.articles.find({ $text: { $search: "mongodb tutorial" } })

medium

A. Documents containing both words 'mongodb' and 'tutorial' in title or content

B. Documents containing exactly the phrase 'mongodb tutorial' only

C. Documents containing either 'mongodb' or 'tutorial' in any field

D. Documents sorted alphabetically by title

Solution

1. Step 1: Understand $text and $search behavior

   The $search operator looks for documents containing all search words (AND behavior) in indexed text fields.

2. Step 2: Analyze the query

   The query searches for documents with both 'mongodb' and 'tutorial' in either title or content fields.

3. Final Answer:

   Documents containing both words 'mongodb' and 'tutorial' in title or content -> Option A

4. Quick Check:

   $search finds all words, not exact phrase [OK]

Hint: $search finds all words, not exact phrase [OK]

Common Mistakes:

• Thinking $search matches exact phrase only
• Assuming $search matches any single word (OR)
• Expecting sorting by title automatically

4. You tried to create two text indexes on a collection: one on title and another on description. What is the problem with this approach?

medium

A. MongoDB allows only one text index per collection

B. Text indexes must be created on numeric fields only

C. You must create text indexes using createTextIndex method

D. Text indexes cannot be created on multiple fields

Solution

1. Step 1: Recall MongoDB text index limitation

   MongoDB allows only one text index per collection, but it can cover multiple fields.

2. Step 2: Evaluate the options

   MongoDB allows only one text index per collection correctly states the limitation. Others are incorrect about field types or methods.

3. Final Answer:

   MongoDB allows only one text index per collection -> Option A

4. Quick Check:

   One text index per collection rule [OK]

Hint: Only one text index allowed per collection [OK]

Common Mistakes:

• Trying to create multiple text indexes on same collection
• Using wrong method name for creating text index
• Thinking text indexes only work on numbers

5. You want to create a text index on title and summary fields but give title twice the search weight of summary. Which is the correct way to create this weighted text index?

hard

A. db.books.createIndex({ title: 'text', summary: 'text' }, { weights: { summary: 2, title: 1 } })

B. db.books.createIndex({ title: 'text', summary: 'text' }, { weight: { title: 2, summary: 1 } })

C. db.books.createIndex({ title: 'text', summary: 'text' }, { weight: { summary: 2, title: 1 } })

D. db.books.createIndex({ title: 'text', summary: 'text' }, { weights: { title: 2, summary: 1 } })

Solution

1. Step 1: Recall syntax for weighted text indexes

   Weights option is an object named weights specifying field weights.

2. Step 2: Check options for correct spelling and values

   db.books.createIndex({ title: 'text', summary: 'text' }, { weights: { title: 2, summary: 1 } }) uses weights correctly and assigns title weight 2, summary 1 as required.

3. Final Answer:

   db.books.createIndex({ title: 'text', summary: 'text' }, { weights: { title: 2, summary: 1 } }) -> Option D

4. Quick Check:

   Use 'weights' option with correct field weights [OK]

Hint: Use 'weights' option with field weights object [OK]

Common Mistakes:

• Using 'weight' instead of 'weights' option
• Swapping weights between fields
• Not specifying weights object correctly