Amazon Exam DAS-C01 Topic 3 Question 84 Discussion

Actual exam question for Amazon's DAS-C01 exam

Question #: 84
Topic #: 3

A company is building an analytical solution that includes Amazon S3 as data lake storage and Amazon Redshift for data warehousing. The company wants to use Amazon Redshift Spectrum to query the data that is stored in Amazon S3.

Which steps should the company take to improve performance when the company uses Amazon Redshift Spectrum to query the S3 data files? (Select THREE )

Use gzip compression with individual file sizes of 1-5 GB

AUse a columnar storage file format

BPartition the data based on the most common query predicates

CSplit the data into KB-sized files.

DKeep all files about the same size.

EUse file formats that are not splittable

Show Suggested Answer

Suggested Answer: B, C, D

by Ryan at Dec 23, 2023, 02:05 PM

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Celia

24 days ago

Good point. But I'm not sure about the file size recommendation. Keeping all files about the same size, between 1-5 GB, sounds more efficient than splitting them into KB-sized files.

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Kenneth

9 days ago

D) Keep all files about the same size

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Kayleigh

10 days ago

B) Partition the data based on the most common query predicates

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Rozella

11 days ago

A) Use a columnar storage file format

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Leonida

24 days ago

Absolutely, and partitioning the data based on common query predicates is also a great idea. That way, Redshift Spectrum can quickly identify the relevant partitions and avoid scanning unnecessary data.

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Juliana

25 days ago

I agree, this is a complex issue. From what I understand, we should definitely use a columnar storage file format like Parquet or ORC. That will help with efficient data access and processing.

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Robt

27 days ago

Hmm, this is a tricky question. We need to consider a few factors to improve Redshift Spectrum performance when querying S3 data files.

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