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Exam AWS Certified Data Engineer - Associate DEA-C01 topic 1 question 35 discussion

Exam question from Amazon's AWS Certified Data Engineer - Associate DEA-C01
Question #: 35
Topic #: 1
[All AWS Certified Data Engineer - Associate DEA-C01 Questions]

A company uses Amazon S3 to store semi-structured data in a transactional data lake. Some of the data files are small, but other data files are tens of terabytes.
A data engineer must perform a change data capture (CDC) operation to identify changed data from the data source. The data source sends a full snapshot as a JSON file every day and ingests the changed data into the data lake.
Which solution will capture the changed data MOST cost-effectively?

  • A. Create an AWS Lambda function to identify the changes between the previous data and the current data. Configure the Lambda function to ingest the changes into the data lake.
  • B. Ingest the data into Amazon RDS for MySQL. Use AWS Database Migration Service (AWS DMS) to write the changed data to the data lake.
  • C. Use an open source data lake format to merge the data source with the S3 data lake to insert the new data and update the existing data.
  • D. Ingest the data into an Amazon Aurora MySQL DB instance that runs Aurora Serverless. Use AWS Database Migration Service (AWS DMS) to write the changed data to the data lake.
Show Suggested Answer Hide Answer
Suggested Answer: C 🗳️
by [deleted] at Jan. 21, 2024, 2:13 a.m.
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GiorgioGss
Highly Voted 1 year, 1 month ago
Selected Answer: C
https://aws.amazon.com/blogs/big-data/implement-a-cdc-based-upsert-in-a-data-lake-using-apache-iceberg-and-aws-glue/
upvoted 7 times
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plutonash
Most Recent 3 months, 2 weeks ago
Selected Answer: A
Generally, AWS questions never give preference to the others solution than an AWS service so even if C could be better the answer is A
upvoted 1 times
Juan_pc
1 week, 1 day ago
But some files are tens of terabytes, and Lamda has a time windows of 15 minutes, that could not be enougth time to process big data
upvoted 1 times
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influxy
8 months, 3 weeks ago
https://aws.amazon.com/blogs/big-data/choosing-an-open-table-format-for-your-transactional-data-lake-on-aws/
upvoted 1 times
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FunkyFresco
11 months, 1 week ago
Selected Answer: C
Ill go with Delta or something like that. is C
upvoted 2 times
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certplan
1 year, 1 month ago
Relative to cost, here are docs for the reason for option C: https://docs.aws.amazon.com/AmazonS3/latest/dev/Welcome.html https://aws.amazon.com/blogs/big-data/ https://docs.aws.amazon.com/glue/latest/dg/welcome.html https://docs.aws.amazon.com/emr/ Here are docs for reasons the others are not correct: https://aws.amazon.com/lambda/pricing/ https://aws.amazon.com/rds/pricing/ https://aws.amazon.com/dms/pricing/
upvoted 2 times
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damaldon
1 year, 2 months ago
Answ. D You can migrate data from any MySQL-compatible database (MySQL, MariaDB, or Amazon Aurora MySQL) using AWS Database Migration Service. https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Source.MySQL.html
upvoted 1 times
Juan_pc
1 week, 1 day ago
D is not the best cost effectively solution
upvoted 1 times
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GiorgioGss
1 year, 1 month ago
"other data files are tens of terabytes" - good luck with DMS on that :) I think it's C
upvoted 6 times
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[Removed]
1 year, 3 months ago
Selected Answer: C
This is a tricky one. Although option A seems like the best choice since it uses an AWS service, I believe using Delta/Iceberg APIs would be easier than writing custom code on Lambda
upvoted 4 times
Houyon
1 year, 2 months ago
If all files were small I believe it would be a great idea. However, you wouldn't be able to compare heavy files with lambda due to its memory/capacity and runtime constraints
upvoted 4 times
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