Which solution will meet these requirements?
Create a global secondary index (GSI) with productFamily as the partition key and productType as the sort key.
Create a local secondary index (LSI) with productFamily as the partition key and productType as the sort key.
Recreate the table. Add partNumber as the partition key and vendor as the sort key. During table creation, add a local secondary index (LSI) with productFamily as the partition key and productType as the sort key.
Update the queries to use Scan operations with productFamily as the partition key and productType as the sort key.
Explanations:
Creating a global secondary index (GSI) with productFamily as the partition key and productType as the sort key will allow efficient queries based on these attributes. GSIs enable queries on non-key attributes and can significantly improve read performance by allowing access patterns that are not supported by the original table’s keys.
A local secondary index (LSI) can only be created at the same time as the table and uses the same partition key as the base table. Since the partition key in the existing table is partNumber, using productFamily as the partition key in an LSI is not possible. Thus, this option does not meet the requirements.
Recreating the table with partNumber as the partition key and vendor as the sort key does not address the need for querying based on productFamily and productType. While adding an LSI during the recreation may allow queries on productType, it still cannot use productFamily as a partition key, making this approach incorrect for the desired query patterns.
Using Scan operations is not an efficient solution for querying DynamoDB tables, especially when looking for specific attributes like productFamily and productType. Scans read every item in the table, leading to increased latency and costs, and do not leverage the indexed attributes for faster lookups. This approach does not improve performance and is therefore not suitable.