Taking Advantage of Parallel Scans https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/bp-query-scan.html An application developer finds that a scan operation on a large DynamoDB table is taking a long time to execute.
What can be used to decrease the execution time of the scan operation?
Click on the arrows to vote for the correct answer
A. B. C. D.Answer: A.
Option A is CORRECT because parallel scans can be used by multiple worker threads in an application to perform a scan of a DynamoDB table much faster.
Option B is incorrect because filter expression in a scan operation only filters the results.
Scan operation still performs the same amount of read operations.
Option C is incorrect because pagination is used to separate the results of scan operation into “pages”.
Option D is incorrect because a projection expression is used to limit the attributes returned by the scan operation.
It does not affect the speed of the scan operation.
Reference:
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Scan.html#Scan.ParallelScanWhen performing a scan operation on a large DynamoDB table, it may take a long time to execute. To decrease the execution time of the scan operation, the application developer can use parallel scans.
A parallel scan divides a large table into smaller segments, which are scanned concurrently. This can significantly reduce the time required to complete the scan operation. The number of segments can be controlled by the application developer, and the optimal value will depend on the size of the table, the amount of data to be scanned, and the capacity of the system.
To use parallel scans in DynamoDB, the developer can specify the TotalSegments parameter, which determines the number of segments to use. The scan operation then returns only the items that match the specified conditions, reducing the amount of data that needs to be transferred and processed.
In addition to parallel scans, there are other techniques that can be used to improve the performance of scan operations in DynamoDB. For example, a filter expression can be used to narrow down the results of the scan to only the items that match certain criteria. This can reduce the amount of data that needs to be scanned and processed.
Pagination can also be used to limit the number of items returned in each response, reducing the amount of data that needs to be transferred and processed at once. Finally, a projection expression can be used to specify which attributes of the items to return, further reducing the amount of data that needs to be transferred and processed.
In summary, when a scan operation on a large DynamoDB table is taking a long time to execute, the application developer can use parallel scans to divide the table into smaller segments, along with other techniques such as filter expressions, pagination, and projection expressions, to reduce the amount of data that needs to be scanned and processed, and improve the performance of the operation.