A company runs an application on AWS. The application stores data in an Amazon DynamoDB table. Some queries are taking a long time to run. These slow queries involve an attribute that is not the table's partition key or sort key.
The amount of data that the application stores in the DynamoDB table is expected to increase significantly. A developer must increase the performance of the queries.
Which solution will meet these requirements?
When queries involve an attribute that is not part of the original table's partition key or sort key, creating a global secondary index (GSI) is the best solution. A GSI allows for querying based on different attributes, effectively enhancing performance especially as the data volume increases. Increasing the page size or performing a parallel scan does not specifically address the inefficiency caused by the lack of indexing on the queried attribute. Auto scaling read capacity units will only help if the issue is purely throughput-related, but it will not solve the fundamental problem of not having an efficient way to retrieve data based on the specific attribute.
Creating a GSI would be more cost efficient than increasing the RCU in this case.
GSI :)
B Parallel scan operations can be useful for scanning large tables, but they may not necessarily improve performance for specific queries involving non-key attributes.
B is the correct answer.
To improve the performance of queries that involve an attribute that is neither the table's partition key nor sort key, and anticipating an increase in data volume, the most effective solution is to utilize a global secondary index (GSI). This allows for efficient querying based on different attributes that are critical for performance but not originally designed as keys in the main table structure.