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Amazon BDS-C00 Exam - Topic 1 Question 73 Discussion

An organization uses Amazon Elastic MapReduce (EMR) to process a series of extract-transform-load (ETL) steps that run in sequence. The output of each step must be fully processed in subsequent steps but will not be retained.Which of the following techniques will meet this requirement most efficiently?
C) Define the ETL steps as separate AWS Data Pipeline activities.
A) Use the EMR File System (EMRFS) to store the outputs from each step as objects in Amazon Simple Storage Service (S3).
B) Use the s3n URI to story the data to be processes as objects in Amazon S3.
D) Load the data to be processed into HDFS and then write the final output to Amazon S3.

Amazon BDS-C00 Exam - Topic 1 Question 73 Discussion

Actual exam question for Amazon's BDS-C00 exam
Question #: 73
Topic #: 1
[All BDS-C00 Questions]

An organization uses Amazon Elastic MapReduce (EMR) to process a series of extract-transform-load (ETL) steps that run in sequence. The output of each step must be fully processed in subsequent steps but will not be retained.

Which of the following techniques will meet this requirement most efficiently?

Show Suggested Answer Hide Answer
Suggested Answer: C

by Jesusa at Apr 03, 2023, 01:45 AM

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Elenor
7 months ago
Isn't s3n outdated? I thought we moved on from that.
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Doug
7 months ago
Definitely agree with EMRFS for this scenario!
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Antione
7 months ago
Wait, why wouldn't we just use S3 directly?
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Jettie
8 months ago
I think using HDFS is more efficient for processing.
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Mose
8 months ago
EMRFS is great for handling S3 data!
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Karrie
8 months ago
I’m leaning towards option C with AWS Data Pipeline, but I’m uncertain if it’s necessary for just sequential ETL steps.
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Lang
8 months ago
I practiced a similar question where we had to choose between S3 and HDFS, and I think S3 might be better for temporary outputs since it’s easier to manage.
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Sommer
8 months ago
I think using HDFS could be more efficient for processing, but I’m not clear on how it compares to using S3 directly.
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Merilyn
8 months ago
I remember studying EMRFS and how it integrates with S3, but I'm not sure if it's the best choice for this scenario since the outputs aren't retained.
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Lenita
8 months ago
Based on the information provided, I think increasing the number of shards and the memory allocation are the two actions that would be most likely to improve the processing speed.
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Freeman
8 months ago
Hmm, this is a tricky one. I'm not super familiar with the specifics of Automation Studio and Journey Builder, so I'll need to think it through carefully. I'm leaning towards the File Drop Entry Source in Journey Builder, since that seems like it would be a good fit for handling the file drop and triggering the email notifications. But I'll want to double-check the details on each option.
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Ronald
8 months ago
Hmm, I'm not totally sure about this one. The options seem a bit similar, and I'm not super familiar with the OWS platform. I'll have to think this through carefully.
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Brynn
1 year ago
Using EMRFS to store the outputs in S3 is definitely the way to go. I mean, who wants to be the one to tell the boss they used the 's3n' URI? That's like pulling a Betamax in the age of Netflix.
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Stephaine
1 year ago
Loading the data into HDFS and then writing the final output to S3 seems like overkill for this use case, where we don't need to retain the intermediate data.
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Weldon
11 months ago
Loading data into HDFS and then writing to S3 is definitely overkill for this scenario.
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Ernest
11 months ago
B) Use the s3n URI to store the data to be processed as objects in Amazon S3.
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Iraida
12 months ago
Loading the data into HDFS and then writing the final output to S3 seems like overkill for this use case, where we don't need to retain the intermediate data.
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Maxima
12 months ago
A) Use the EMR File System (EMRFS) to store the outputs from each step as objects in Amazon Simple Storage Service (S3).
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Mertie
1 year ago
B) Use the s3n URI to store the data to be processed as objects in Amazon S3.
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Bettye
1 year ago
A) Use the EMR File System (EMRFS) to store the outputs from each step as objects in Amazon Simple Storage Service (S3).
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Kristeen
1 year ago
Defining the ETL steps as separate AWS Data Pipeline activities could work, but it might add unnecessary complexity compared to the EMRFS approach.
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Lauran
1 year ago
D) Load the data to be processed into HDFS and then write the final output to Amazon S3.
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Jeniffer
1 year ago
B) Use the s3n URI to store the data to be processed as objects in Amazon S3.
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Billye
1 year ago
A) Use the EMR File System (EMRFS) to store the outputs from each step as objects in Amazon Simple Storage Service (S3).
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Vi
1 year ago
That's a valid point, but I still think storing outputs in S3 using EMRFS is more efficient.
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Domingo
1 year ago
I'm not sure s3n URI is the right choice here, as it doesn't seem to address the requirement of not retaining the data locally.
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Cyndy
1 year ago
C) Define the ETL steps as separate AWS Data Pipeline activities.
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Richelle
1 year ago
A) Use the EMR File System (EMRFS) to store the outputs from each step as objects in Amazon Simple Storage Service (S3).
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Thomasena
1 year ago
I disagree, I believe option D is better because it involves loading data into HDFS first.
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Rasheeda
1 year ago
Using EMRFS to store the output in S3 seems the most efficient option since it allows us to process the data without having to retain it locally.
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Vi
1 year ago
I think option A is the most efficient.
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