Atlas search overview in MongoDB - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a search index named 'myIndex' on the 'products' collection.

MongoDB

db.products.createIndex({ [1]: "text" }, { name: "myIndex" })

Drag options to blanks, or click blank then click option'

Adescription

Bname

Cprice

Dcategory

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing a numeric field like 'price' for a text index causes errors.

Using a field not present in the collection.

The 'name' field is commonly indexed for text search in Atlas Search. This command creates a text index on the 'name' field.

2fill in blank

medium

Complete the code to perform a text search for the word 'coffee' using the '$search' stage in an aggregation pipeline.

MongoDB

db.products.aggregate([{ $search: { text: { query: [1], path: "name" } } }])

Drag options to blanks, or click blank then click option'

A"coffee"

B"tea"

C"milk"

D"juice"

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting quotes around the search term.

Using a different word than 'coffee' which changes the search.

The query value must be the string 'coffee' to search for that word in the 'name' field.

3fill in blank

hard

Fix the error in the aggregation pipeline to correctly search for 'espresso' in the 'description' field.

MongoDB

db.products.aggregate([{ $search: { text: { query: [1], path: "description" } } }])

Drag options to blanks, or click blank then click option'

A"espresso"

Bespresso

C'espresso'

Despresso"

Attempts:

3 left

💡 Hint

Common Mistakes

Using unquoted words causes syntax errors.

Using mismatched quotes causes errors.

The query value must be a string literal, so it needs to be enclosed in double quotes.

4fill in blank

hard

Fill both blanks to create a compound search index on 'name' and 'category' fields.

MongoDB

db.products.createIndex({ [1]: "text", [2]: "text" })

Drag options to blanks, or click blank then click option'

Aname

Bprice

Ccategory

Ddescription

Attempts:

3 left

💡 Hint

Common Mistakes

Including numeric fields like 'price' in a text index causes errors.

Using the same field twice.

Compound text indexes can include multiple fields like 'name' and 'category' to improve search coverage.

5fill in blank

hard

Fill all three blanks to perform a search for 'latte' in the 'name' field, sort results by 'price' ascending, and limit to 5 results.

MongoDB

db.products.aggregate([{ $search: { text: { query: [1], path: [2] } } }, { $sort: { [3]: 1 } }, { $limit: 5 }])

Drag options to blanks, or click blank then click option'

A"latte"

B"name"

Cprice

Dcategory

Attempts:

3 left

💡 Hint

Common Mistakes

Not quoting the query or path strings.

Sorting by a field not in the collection.

Using -1 instead of 1 for ascending sort.

The query searches for 'latte' in the 'name' field, sorts by 'price' ascending (1), and limits results to 5.

Practice

1. What is the primary purpose of the $search stage in MongoDB Atlas Search?

easy

A. To update documents in a collection

B. To perform text search queries on collections

C. To delete documents based on a condition

D. To create indexes on collections

Solution

1. Step 1: Understand the role of $search

   The $search stage is used in aggregation pipelines to perform text search queries on MongoDB collections.

2. Step 2: Differentiate from other operations

   Updating, deleting, or creating indexes are not functions of $search. It is specifically for searching text.

3. Final Answer:

   To perform text search queries on collections -> Option B

4. Quick Check:

   $search = text search [OK]

Hint: Remember: $search is for finding text, not modifying data [OK]

Common Mistakes:

• Confusing $search with update or delete operations
• Thinking $search creates indexes
• Assuming $search works outside aggregation

2. Which of the following is the correct syntax to use the $search stage in an aggregation pipeline?

easy

A. { $search: { find: { query: "apple", field: "name" } } }

B. { $search: { text: { search: "apple", field: "name" } } }

C. { $search: { query: "apple", path: "name" } }

D. { $search: { text: { query: "apple", path: "name" } } }

Solution

1. Step 1: Recall the correct $search syntax

   The $search stage uses a text operator with query and path fields to specify the search term and field.

2. Step 2: Compare options to syntax

   { $search: { text: { query: "apple", path: "name" } } } matches the correct syntax. Other options use incorrect keys like find, missing text, or wrong field names.

3. Final Answer:

   { $search: { text: { query: "apple", path: "name" } } } -> Option D

4. Quick Check:

   Correct keys: text, query, path [OK]

Hint: Look for keys: text, query, and path in $search [OK]

Common Mistakes:

• Using 'find' instead of 'text' inside $search
• Omitting 'text' operator
• Using 'field' instead of 'path'

3. Given the following aggregation pipeline, what documents will be returned if the collection has documents with names: ['apple', 'banana', 'pineapple']?

[{ $search: { text: { query: "apple", path: "name" } } }]

medium

A. Only the document with name 'apple'

B. Documents with names 'apple' and 'pineapple'

C. Documents with names 'banana' and 'pineapple'

D. All documents in the collection

Solution

1. Step 1: Understand text search behavior

   The $search with text operator performs full-text search matching whole terms after tokenization. It does not perform substring matching by default.

2. Step 2: Apply to given names

   'apple' matches the query term exactly. 'pineapple' is tokenized as a single term "pineapple", which does not match "apple". 'banana' does not match.

3. Final Answer:

   Only the document with name 'apple' -> Option A

4. Quick Check:

   Whole term matches only [OK]

Hint: Text search matches whole terms, not substrings [OK]

Common Mistakes:

• Assuming substring matches like 'pineapple' for 'apple'
• Including documents without the query term
• Thinking $search returns all documents

4. Identify the error in this aggregation pipeline using Atlas Search:

[{ $search: { text: { query: "apple" } } }]

medium

A. Missing the 'path' field specifying which field to search

B. The 'query' field should be named 'search'

C. The $search stage cannot be used inside aggregation

D. The 'text' operator is invalid inside $search

Solution

1. Step 1: Check required fields in $search text operator

   The 'text' operator requires both 'query' and 'path' fields to specify the search term and the field to search.

2. Step 2: Identify missing field

   The pipeline is missing the 'path' field, so MongoDB does not know which field to search.

3. Final Answer:

   Missing the 'path' field specifying which field to search -> Option A

4. Quick Check:

   Always include 'path' with 'query' in $search text [OK]

Hint: Always specify 'path' when using $search text operator [OK]

Common Mistakes:

• Omitting 'path' field
• Renaming 'query' to 'search'
• Thinking $search can't be in aggregation

5. You want to search for documents where either the 'title' or 'description' fields contain the word 'mongodb'. Which $search operator should you use in your aggregation pipeline?

hard

A. { $search: { text: { query: "mongodb", path: "title" }, text: { query: "mongodb", path: "description" } } }

B. { $search: { compound: { must: [{ text: { query: "mongodb", path: "title" } }, { text: { query: "mongodb", path: "description" } }] } } }

C. { $search: { text: { query: "mongodb", path: ["title", "description"] } } }

D. { $search: { text: { query: "mongodb", path: "title" } }, filter: { text: { query: "mongodb", path: "description" } } }

Solution

1. Step 1: Understand searching multiple fields

   The text operator allows specifying multiple fields by passing an array to the path parameter.

2. Step 2: Evaluate options for multiple field search

   { $search: { text: { query: "mongodb", path: ["title", "description"] } } } correctly uses an array for path to search both 'title' and 'description' (OR semantics). { $search: { text: { query: "mongodb", path: "title" }, text: { query: "mongodb", path: "description" } } } has invalid syntax with duplicate text keys. { $search: { compound: { must: [{ text: { query: "mongodb", path: "title" } }, { text: { query: "mongodb", path: "description" } }] } } } uses compound with must requiring both fields to match (AND). { $search: { text: { query: "mongodb", path: "title" } }, filter: { text: { query: "mongodb", path: "description" } } } has invalid syntax.

3. Final Answer:

   { $search: { text: { query: "mongodb", path: ["title", "description"] } } } -> Option C

4. Quick Check:

   Use array in path for multiple fields [OK]

Hint: Use array in 'path' to search multiple fields [OK]

Common Mistakes:

• Using compound must instead of array for either/or
• Repeating text operator keys incorrectly
• Misusing filter stage inside $search