Secondary indexes (GSI, LSI) in AWS - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Difference between GSI and LSI in DynamoDB

Which statement correctly describes a key difference between a Global Secondary Index (GSI) and a Local Secondary Index (LSI) in DynamoDB?

A A GSI can only be created at table creation, while an LSI can be added anytime after table creation.

B A GSI can have a different partition key than the base table, while an LSI shares the same partition key but has a different sort key.

C Both GSI and LSI must share the same partition and sort keys as the base table.

D An LSI can have a different partition key than the base table, while a GSI shares the same partition key but has a different sort key.

💡 Hint

Think about which index type allows a different partition key from the main table.

A Global Secondary Index (GSI) allows a different partition key and sort key from the base table, enabling queries on different attributes. A Local Secondary Index (LSI) shares the same partition key but uses a different sort key. LSIs must be created when the table is created.

❓ Architecture

intermediate

Choosing index type for query flexibility

You have a DynamoDB table with a partition key 'UserID' and sort key 'OrderDate'. You want to query orders by 'ProductCategory' regardless of user. Which index type should you create?

A Create a Global Secondary Index with 'ProductCategory' as partition key.

B Create a Local Secondary Index with 'ProductCategory' as sort key.

C Create a Local Secondary Index with 'ProductCategory' as partition key.

D Create a Global Secondary Index with 'UserID' as partition key and 'ProductCategory' as sort key.

💡 Hint

Remember that LSIs share the same partition key as the base table.

To query by 'ProductCategory' regardless of 'UserID', you need an index with 'ProductCategory' as partition key. Only a Global Secondary Index (GSI) allows a different partition key. LSIs must share the base table's partition key.

❓ service_behavior

advanced

Impact of LSI size limit on table design

Your DynamoDB table uses an LSI. What happens if the total size of all items with the same partition key exceeds 10 GB?

A DynamoDB rejects writes that cause the size to exceed 10 GB for that partition key.

B DynamoDB automatically creates a new partition to handle the extra data.

C DynamoDB deletes the oldest items to keep size under 10 GB.

D DynamoDB converts the LSI to a GSI automatically.

💡 Hint

Consider DynamoDB's hard limits on LSI size per partition key.

LSIs have a strict limit of 10 GB per partition key. If a write causes this limit to be exceeded, DynamoDB rejects the write with a validation error. It does not automatically repartition or delete data.

❓ security

advanced

Access control for GSIs in IAM policies

You want to restrict a user to only query a specific Global Secondary Index (GSI) on a DynamoDB table. Which IAM policy condition is required?

A Use the 'dynamodb:PartitionKey' condition key to specify the GSI partition key.

B Use the 'dynamodb:TableName' condition key to specify the GSI name.

C Use the 'dynamodb:Attributes' condition key to specify GSI attributes.

D Use the 'dynamodb:IndexName' condition key to specify the allowed GSI name.

💡 Hint

Think about which IAM condition key controls access to indexes.

The IAM condition key 'dynamodb:IndexName' allows you to restrict actions to a specific index name, including GSIs. 'dynamodb:TableName' controls table access, but not specific indexes.

✅ Best Practice

expert

Optimizing cost and performance with GSIs

You have a DynamoDB table with a GSI that is rarely queried but has high write traffic. What is the best practice to optimize cost and performance?

A Remove the GSI and perform full table scans instead.

B Increase the provisioned write capacity on the GSI to handle all writes.

C Use sparse indexes by including a GSI partition key attribute only on items that need to be indexed.

D Duplicate the table and use the duplicate for GSI queries.

💡 Hint

Think about how to reduce unnecessary writes to the GSI.

Sparse indexes reduce write costs and improve performance by only indexing items that have the GSI partition key attribute. This avoids writing all items to the GSI when not needed.