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.