When Scan is acceptable in DynamoDB - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to perform a Scan operation on a DynamoDB table named 'Products'.

DynamoDB

response = dynamodb_client.[1](TableName='Products')

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

Ascan

Bget_item

Cquery

Dupdate_item

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'query' instead of 'scan' when you want all items.

Using 'get_item' which retrieves only one item by key.

The scan method reads every item in the table, which is useful when you need to retrieve all data without filtering by key.

2fill in blank

medium

Complete the code to add a filter expression to the Scan operation to only get items where 'Category' equals 'Books'.

DynamoDB

response = dynamodb_client.scan(TableName='Products', FilterExpression='[1] = :cat', ExpressionAttributeValues={':cat': {'S': 'Books'}})

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AcategoryName

Bcategory

CCategory

DProductCategory

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase 'category' which does not match the attribute name.

Using a different attribute name not present in the table.

The attribute name must match exactly the DynamoDB attribute, which is 'Category' with uppercase 'C'.

3fill in blank

hard

Fix the error in the Scan operation that tries to filter items by 'Price' less than 20.

DynamoDB

response = dynamodb_client.scan(TableName='Products', FilterExpression='Price [1] :val', ExpressionAttributeValues={':val': {'N': '20'}})

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

A!=

B<

C=

D==

Attempts:

3 left

💡 Hint

Common Mistakes

Using '=' which is invalid for comparison in FilterExpression.

Using '==' which is not supported in DynamoDB expressions.

The correct operator for 'less than' in DynamoDB FilterExpression is '<'.

4fill in blank

hard

Fill both blanks to complete the Scan operation that retrieves items with 'Stock' greater than 0 and projects only 'ProductId' and 'Stock'.

DynamoDB

response = dynamodb_client.scan(TableName='Products', FilterExpression='Stock [1] :min', ExpressionAttributeValues={':min': {'N': '0'}}, ProjectionExpression='[2], Stock')

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A>

B<

CProductId

DCategory

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' for the filter.

Projecting wrong attribute names.

The filter uses '>' to get items with Stock greater than 0, and the projection includes 'ProductId' and 'Stock'.

5fill in blank

hard

Fill all three blanks to complete the Scan operation that paginates results using 'LastEvaluatedKey', filters items with 'Status' equal to 'Active', and projects 'UserId' and 'Status'.

DynamoDB

response = dynamodb_client.scan(TableName='Users', FilterExpression='Status = :stat', ExpressionAttributeValues={':stat': {'S': 'Active'}}, ProjectionExpression='[1], Status', ExclusiveStartKey=[2])

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

AUserId

Blast_key

C{}

DLastEvaluatedKey

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong attribute names in projection.

Passing wrong type or variable for ExclusiveStartKey.

'UserId' is projected, 'last_key' is the variable holding the last evaluated key, and '{}' is used when there is no last key to start from.

Practice

1. Which situation is best suited for using a Scan operation in DynamoDB?

easy

A. When you want to update an item quickly.

B. When you want to retrieve a single item by its primary key.

C. When you need to read all items from a small table.

D. When you want to delete an item by its key.

Solution

1. Step 1: Understand Scan operation purpose

   Scan reads every item in the table, which is simple but slow for large tables.

2. Step 2: Match Scan use case

   Scan is acceptable when the table is small and you need all data, not a specific item by key.

3. Final Answer:

   When you need to read all items from a small table. -> Option C

4. Quick Check:

   Scan = small table full read [OK]

Hint: Use Scan only for small tables or full data needs [OK]

Common Mistakes:

• Using Scan to get a single item by key
• Using Scan for updates or deletes
• Ignoring performance impact on large tables

2. Which of the following is the correct syntax to perform a Scan operation with a filter expression in DynamoDB?

easy

A. Scan(TableName='Users', ConditionExpression='Age > :age')

B. Scan(TableName='Users', KeyConditionExpression='Age > :age', ExpressionAttributeValues={':age': 30})

C. Scan(TableName='Users', Filter='Age > 30')

D. Scan(TableName='Users', FilterExpression='Age > :age', ExpressionAttributeValues={':age': 30})

Solution

1. Step 1: Identify correct Scan parameters

   Scan uses FilterExpression to filter results after scanning all items.

2. Step 2: Check syntax correctness

   Scan(TableName='Users', FilterExpression='Age > :age', ExpressionAttributeValues={':age': 30}) uses FilterExpression and ExpressionAttributeValues correctly for filtering.

3. Final Answer:

   Scan(TableName='Users', FilterExpression='Age > :age', ExpressionAttributeValues={':age': 30}) -> Option D

4. Quick Check:

   FilterExpression syntax = Scan(TableName='Users', FilterExpression='Age > :age', ExpressionAttributeValues={':age': 30}) [OK]

Hint: FilterExpression filters after Scan, not KeyConditionExpression [OK]

Common Mistakes:

• Using KeyConditionExpression with Scan
• Using wrong parameter names like Filter or ConditionExpression
• Not providing ExpressionAttributeValues for placeholders

3. Given a DynamoDB table 'Products' with 3 items: {"ID":1, "Category":"Book"}, {"ID":2, "Category":"Toy"}, {"ID":3, "Category":"Book"}, what will be the result of this Scan operation?

Scan(TableName='Products', FilterExpression='Category = :cat', ExpressionAttributeValues={':cat': 'Book'})

medium

A. [{"ID":1, "Category":"Book"}, {"ID":3, "Category":"Book"}]

B. [{"ID":2, "Category":"Toy"}]

C. [{"ID":1, "Category":"Book"}, {"ID":2, "Category":"Toy"}, {"ID":3, "Category":"Book"}]

D. []

Solution

1. Step 1: Understand Scan with FilterExpression

   Scan reads all items, then returns only those matching the filter Category = 'Book'.

2. Step 2: Apply filter to items

   Items with Category 'Book' are ID 1 and ID 3, so only these are returned.

3. Final Answer:

   [{"ID":1, "Category":"Book"}, {"ID":3, "Category":"Book"}] -> Option A

4. Quick Check:

   Filter returns matching items only [OK]

Hint: Scan returns all, filter narrows results after [OK]

Common Mistakes:

• Expecting Scan to return only filtered items without FilterExpression
• Confusing Scan with Query operation
• Ignoring that Scan reads all items first

4. You wrote this Scan code but it returns all items without filtering:

Scan(TableName='Orders', FilterExpression='Status = :s')

What is the most likely error?

medium

A. Missing ExpressionAttributeValues for ':s'.

B. Using FilterExpression instead of KeyConditionExpression.

C. Scan does not support FilterExpression.

D. Table name is incorrect.

Solution

1. Step 1: Check FilterExpression usage

   FilterExpression uses placeholders like ':s' which must be defined in ExpressionAttributeValues.

2. Step 2: Identify missing ExpressionAttributeValues

   Code lacks ExpressionAttributeValues, so filter cannot apply and returns all items.

3. Final Answer:

   Missing ExpressionAttributeValues for ':s'. -> Option A

4. Quick Check:

   Filter needs ExpressionAttributeValues [OK]

Hint: Always provide ExpressionAttributeValues for FilterExpression [OK]

Common Mistakes:

• Confusing FilterExpression with KeyConditionExpression
• Forgetting ExpressionAttributeValues
• Assuming Scan ignores missing values silently

5. You have a large DynamoDB table with millions of items but no suitable key for your query. You need to find all items where Status = 'Active'. Which approach is best?

hard

A. Use Scan with FilterExpression 'Status = :status' and paginate results.

B. Create a Global Secondary Index on 'Status' and use Query.

C. Use Query with KeyConditionExpression on 'Status'.

D. Use Scan without any filter to get all items.

Solution

1. Step 1: Understand limitations of Scan on large tables

   Scan reads all items and is slow and costly on large tables, even with filters.

2. Step 2: Use Global Secondary Index (GSI) for efficient queries

   Creating a GSI on 'Status' allows Query operation, which is fast and efficient for filtering by 'Status'.

3. Final Answer:

   Create a Global Secondary Index on 'Status' and use Query. -> Option B

4. Quick Check:

   GSI + Query = efficient large table filter [OK]

Hint: Use GSI for filtering large tables, not Scan [OK]

Common Mistakes:

• Using Scan on large tables causing slow performance
• Trying Query without suitable key or index
• Ignoring cost and speed implications