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A data engineer needs to optimize the performance of a data pipeline that handles retail...

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A data engineer needs to optimize the performance of a data pipeline that handles retail orders. Data about the orders is ingested daily into an Amazon S3 bucket.

The data engineer runs queries once each week to extract metrics from the orders data based on the order date for multiple date ranges. The data engineer needs an optimization solution that ensures the query performance will not degrade when the volume of data increases.

A.

Partition the data based on order date. Use Amazon Athena to query the data.

B.

Partition the data based on order date. Use Amazon Redshift to query the data.

C.

Partition the data based on load date. Use Amazon EMR to query the data.

D.

Partition the data based on load date. Use Amazon Aurora to query the data.

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