DEA-C01 Question 87

Community Discussion

Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.

• Chose A1

  https://aws.amazon.com/blogs/big-data/under-the-hood-scaling-your-kinesis-data-streams/

• Chose A2

  The correct answer is **A. Change the partition key from facility ID to a randomly generated key.** Amazon Kinesis Data Streams uses the partition key that you specify to segregate the data records in the stream into shards. If the company uses the facility ID as the partition key, and if some facilities produce more data than others, then the data will be unevenly distributed across the shards. This can lead to some shards being heavily used while others are idle, and can cause `WriteThroughputExceeded` exceptions. By changing the partition key to a randomly generated key, the data records are more likely to be evenly distributed across all the shards, which can help to avoid the issue of some shards being heavily used and others being idle. This solution requires the least operational overhead and does not involve increasing costs (as in option B), archiving data (which might not be desirable or feasible, as in option C), or changing to a partition key that might also lead to uneven distribution (as in option D).

• Chose A2

  D is not good, because you're effectively making things worse by partitioning by date. My answer is A