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Exam AWS Certified Solutions Architect - Professional SAP-C02 topic 1 question 387 discussion

Exam question from Amazon's AWS Certified Solutions Architect - Professional SAP-C02
Question #: 387
Topic #: 1
[All AWS Certified Solutions Architect - Professional SAP-C02 Questions]

A company deploys a new web application. As part of the setup, the company configures AWS WAF to log to Amazon S3 through Amazon Kinesis Data Firehose. The company develops an Amazon Athena query that runs once daily to return AWS WAF log data from the previous 24 hours. The volume of daily logs is constant. However, over time, the same query is taking more time to run.

A solutions architect needs to design a solution to prevent the query time from continuing to increase. The solution must minimize operational overhead.

Which solution will meet these requirements?

  • A. Create an AWS Lambda function that consolidates each day's AWS WAF logs into one log file.
  • B. Reduce the amount of data scanned by configuring AWS WAF to send logs to a different S3 bucket each day.
  • C. Update the Kinesis Data Firehose configuration to partition the data in Amazon S3 by date and time. Create external tables for Amazon Redshift. Configure Amazon Redshift Spectrum to query the data source.
  • D. Modify the Kinesis Data Firehose configuration and Athena table definition to partition the data by date and time. Change the Athena query to view the relevant partitions.
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Suggested Answer: D 🗳️
by devalenzuela86 at Nov. 22, 2023, 6:41 p.m.
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duriselvan
10 months, 3 weeks ago
D ans :https://repost.aws/knowledge-center/athena-queries-long-processing-time
upvoted 4 times
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career360guru
11 months, 3 weeks ago
Selected Answer: D
Option D
upvoted 1 times
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vibzr2023
12 months ago
Answer: D Partitioning is a powerful technique for optimizing query performance and cost in Athena, especially for large, growing datasets.Firehose and Athena seamlessly support partitioning, making it easy to implement.
upvoted 2 times
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MegalodonBolado
1 year ago
Selected Answer: D
D. The user can split various logs into daily partitions. As daily volume is constant, the time to process will not increase over time.
upvoted 1 times
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GaryQian
1 year ago
Selected Answer: D
D is simple and easy to do
upvoted 1 times
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Russs99
1 year ago
Selected Answer: D
D, is correct. It looks like option a is viable as well.
upvoted 1 times
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George88
1 year, 1 month ago
Answer: D https://aws.amazon.com/blogs/big-data/kinesis-data-firehose-now-supports-dynamic-partitioning-to-amazon-s3/
upvoted 3 times
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devalenzuela86
1 year, 1 month ago
Selected Answer: D
D is ok
upvoted 3 times
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