Scan vs Query performance comparison in DynamoDB - Quick Revision & Key Differences

Recall & Review

beginner

What is a Scan operation in DynamoDB?

A Scan operation reads every item in a table or a secondary index. It examines all data and returns matching results, which can be slow for large tables.

beginner

What is a Query operation in DynamoDB?

A Query operation finds items based on primary key values. It is efficient because it looks only at items with matching partition keys, not the whole table.

beginner

Why is Query generally faster than Scan in DynamoDB?

Query targets specific partition keys, so it reads fewer items. Scan reads the entire table, which takes more time and resources.

intermediate

When might you use Scan instead of Query?

Use Scan when you need to retrieve data without knowing the partition key or when filtering on non-key attributes, but expect slower performance.

intermediate

How can you improve Scan performance in DynamoDB?

You can improve Scan by using filters to reduce returned data, paginating results, or using parallel scans to read data faster.

Which DynamoDB operation reads the entire table?

A Scan

B Query

C GetItem

D UpdateItem

Scan reads every item in the table, while Query targets specific partition keys.

Which operation is more efficient for retrieving items by partition key?

A Scan

B DeleteItem

C PutItem

D Query

Query uses the partition key to quickly find matching items.

What is a downside of using Scan in DynamoDB?

A It only works with primary keys

B It can be slow and consume more read capacity

C It cannot filter results

D It updates items automatically

Scan reads the whole table, which can be slow and costly.

How can you reduce the amount of data returned by a Scan?

A Use filters

B Use Query instead

C Use GetItem

D Use UpdateItem

Filters limit the data returned after scanning all items.

Which operation should you use if you know the partition key of the item?

A Scan

B DescribeTable

C Query

D BatchWriteItem

Query efficiently retrieves items by partition key.

Explain the main differences between Scan and Query operations in DynamoDB and their impact on performance.

Think about how much data each operation reads.

Describe scenarios where you would choose Scan over Query in DynamoDB despite performance costs.

Consider cases where you can't use the primary key.

Practice

1. Which DynamoDB operation is generally faster when you know the partition key of the item you want to retrieve?

easy

A. Scan

B. UpdateItem

C. Query

D. DeleteItem

Solution

1. Step 1: Understand Query operation

   Query uses the partition key to directly find matching items, making it efficient.

2. Step 2: Compare with Scan operation

   Scan reads the entire table, which is slower and less efficient.

3. Final Answer:

   Query -> Option C

4. Quick Check:

   Query is faster for known keys [OK]

Hint: Use Query when you know the partition key for speed [OK]

Common Mistakes:

• Thinking Scan is faster because it reads all data
• Confusing Query with Scan
• Assuming UpdateItem is for reading data

2. Which of the following is the correct syntax to perform a Query operation in DynamoDB using AWS SDK for JavaScript?

easy

A. dynamoDbClient.query({ TableName: 'MyTable', KeyConditionExpression: '#pk = :pkval', ExpressionAttributeNames: { '#pk': 'PartitionKey' }, ExpressionAttributeValues: { ':pkval': '123' } })

B. dynamoDbClient.scan({ TableName: 'MyTable', KeyConditionExpression: 'PartitionKey = 123' })

C. dynamoDbClient.query({ TableName: 'MyTable', FilterExpression: 'PartitionKey = 123' })

D. dynamoDbClient.getItem({ TableName: 'MyTable', Key: { PartitionKey: '123' } })

Solution

1. Step 1: Identify correct Query syntax

   Query requires KeyConditionExpression with placeholders and attribute names/values.

2. Step 2: Check options for correct usage

   dynamoDbClient.query({ TableName: 'MyTable', KeyConditionExpression: '#pk = :pkval', ExpressionAttributeNames: { '#pk': 'PartitionKey' }, ExpressionAttributeValues: { ':pkval': '123' } }) uses KeyConditionExpression and ExpressionAttributeNames/Values correctly.

3. Final Answer:

   dynamoDbClient.query({ TableName: 'MyTable', KeyConditionExpression: '#pk = :pkval', ExpressionAttributeNames: { '#pk': 'PartitionKey' }, ExpressionAttributeValues: { ':pkval': '123' } }) -> Option A

4. Quick Check:

   Query needs KeyConditionExpression [OK]

Hint: Query needs KeyConditionExpression, not FilterExpression [OK]

Common Mistakes:

• Using FilterExpression instead of KeyConditionExpression for Query
• Using scan method with KeyConditionExpression
• Confusing getItem with query syntax

3. Given a DynamoDB table with 1000 items, what will be the main difference in performance between these two operations?
dynamoDbClient.scan({ TableName: 'MyTable' })
and
dynamoDbClient.query({ TableName: 'MyTable', KeyConditionExpression: '#pk = :pk', ExpressionAttributeNames: { '#pk': 'PartitionKey' }, ExpressionAttributeValues: { ':pk': '123' } })

medium

A. Scan reads all 1000 items; Query reads only matching items, so Query is faster.

B. Scan is faster because it reads all items at once; Query is slower due to filtering.

C. Both operations have the same speed because they access the same table.

D. Query reads all items; Scan reads only matching items.

Solution

1. Step 1: Understand Scan operation

   Scan reads every item in the table, so it processes all 1000 items.

2. Step 2: Understand Query operation

   Query uses the partition key to read only matching items, which is faster.

3. Final Answer:

   Scan reads all items; Query reads only matching items, so Query is faster. -> Option A

4. Quick Check:

   Scan reads all; Query reads matching [OK]

Hint: Scan reads whole table; Query reads only matching keys [OK]

Common Mistakes:

• Thinking Scan is faster because it reads all data at once
• Confusing Query reading all items
• Assuming both have same speed

4. You wrote this DynamoDB Query code but it returns no results:

const params = { TableName: 'MyTable', KeyConditionExpression: 'PartitionKey = :pk', ExpressionAttributeValues: { ':pk': '123' } };
const data = await dynamoDbClient.query(params);

What is the most likely error?

medium

A. Missing ExpressionAttributeNames for reserved word PartitionKey

B. Using Scan instead of Query

C. TableName is misspelled

D. Incorrect KeyConditionExpression syntax; should use #pk = :pk

Solution

1. Step 1: Check KeyConditionExpression syntax

   KeyConditionExpression requires placeholders for attribute names like #pk defined in ExpressionAttributeNames.

2. Step 2: Identify missing ExpressionAttributeNames

   The code uses 'PartitionKey' directly without ExpressionAttributeNames, causing no matches.

3. Final Answer:

   Incorrect KeyConditionExpression syntax; should use #pk = :pk -> Option D

4. Quick Check:

   Reserved words need placeholders in KeyConditionExpression [OK]

Hint: Use placeholders for reserved words in KeyConditionExpression [OK]

Common Mistakes:

• Not using ExpressionAttributeNames for reserved words
• Confusing Scan and Query methods
• Misspelling TableName

5. You want to retrieve all items where the attribute 'Status' equals 'Active' from a large DynamoDB table. The table's partition key is 'UserId'. Which approach is best for performance and cost?

hard

A. Use Query with KeyConditionExpression on 'UserId' and FilterExpression on 'Status' = 'Active'.

B. Create a Global Secondary Index (GSI) on 'Status' and Query the GSI for 'Active' items.

C. Use Scan with a FilterExpression on 'Status' = 'Active' to get all matching items.

D. Use Scan without any filters to get all items and then filter in application code.

Solution

1. Step 1: Understand limitations of Scan and Query

   Scan reads entire table and is costly; Query requires partition key, but 'Status' is not the partition key.

2. Step 2: Use GSI for efficient querying

   Creating a GSI on 'Status' allows Query on 'Status' attribute efficiently without scanning.

3. Final Answer:

   Create a Global Secondary Index (GSI) on 'Status' and Query the GSI for 'Active' items. -> Option B

4. Quick Check:

   GSI enables efficient queries on non-key attributes [OK]

Hint: Use GSI to query non-key attributes efficiently [OK]

Common Mistakes:

• Using Scan with filters on large tables
• Trying to Query without partition key
• Filtering in application instead of database