Once a month, a company receives a 100 MB .csv file compressed with gzip. The file contains 50,000 property listing records and is stored in Amazon S3 Glacier. The company needs its data analyst to…

Question

Options

• ALoad the data into Amazon S3 and query it with Amazon S3 Select.
• BQuery the data from Amazon S3 Glacier directly with Amazon Glacier Select.
• CLoad the data to Amazon S3 and query it with Amazon Athena.
• DLoad the data to Amazon S3 and query it with Amazon Redshift Spectrum.

• A
  84% (16)
• B
  5% (1)
• C
  11% (2)

Explanation

Loading the data into Amazon S3 and querying it with Amazon S3 Select (Option A) is the most cost-effective solution. S3 Select allows you to retrieve only the specific subset of data you need from a compressed CSV file using SQL expressions, minimizing both data retrieval and processing costs. For a 100 MB file queried infrequently, this is very cheap. Option B (Glacier Select) involves retrieval latency and higher costs due to Glacier's retrieval pricing tiers. Option C uses Amazon Athena, which is also a valid serverless query tool, but charges per data scanned; for a single small file and a simple filter query, S3 Select is cheaper since it is priced on bytes scanned and returned at a lower rate. Option D (Redshift Spectrum) requires a running Redshift cluster, making it overkill and far more expensive for this infrequent, small-scale use case.

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