Snowflake ARA-C01 Exam - Topic 3 Question 48 Discussion

Actual exam question for Snowflake's ARA-C01 exam

Question #: 48
Topic #: 3

A company is trying to Ingest 10 TB of CSV data into a Snowflake table using Snowpipe as part of Its migration from a legacy database platform. The records need to be ingested in the MOST performant and cost-effective way.

How can these requirements be met?

AUse ON_ERROR = continue in the copy into command.

BUse purge = TRUE in the copy into command.

CUse FURGE = FALSE in the copy into command.

DUse on error = SKIP_FILE in the copy into command.

Show Suggested Answer

Suggested Answer: D

For ingesting a large volume of CSV data into Snowflake using Snowpipe, especially for a substantial amount like 10 TB, the on error = SKIP_FILE option in the COPY INTO command can be highly effective. This approach allows Snowpipe to skip over files that cause errors during the ingestion process, thereby not halting or significantly slowing down the overall data load. It helps in maintaining performance and cost-effectiveness by avoiding the reprocessing of problematic files and continuing with the ingestion of other data.

by Reynalda at Mar 21, 2025, 05:06 AM

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Tula

3 months ago

Definitely going with D for cost-effectiveness!

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Karan

3 months ago

I think A could lead to data issues later on.

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Rene

3 months ago

Wait, does using SKIP_FILE really improve performance?

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Lavonna

4 months ago

Purge = TRUE? That sounds risky!

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Claribel

4 months ago

Option D is the best choice for error handling!

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Marvel

4 months ago

I vaguely remember that purging files after ingestion can save costs, but I’m not clear on whether it should be TRUE or FALSE in this case.

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Karl

4 months ago

I feel like using ON_ERROR = SKIP_FILE could help avoid issues with bad records, but I’m not entirely confident about its performance impact.

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Lemuel

4 months ago

I think we practiced a question about using purge options before, but I can't recall if TRUE or FALSE is more cost-effective for this scenario.

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Justine

5 months ago

I remember discussing the importance of error handling in Snowpipe, but I'm not sure if ON_ERROR = continue is the best option for large data sets.

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Kati

5 months ago

I'm feeling pretty confident about this one. The question is asking for the most performant and cost-effective approach, and based on my understanding, option D with "on error = SKIP_FILE" is the way to go. That should help us get the 10 TB of data ingested quickly and efficiently.

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Donte

5 months ago

Okay, I've got a strategy here. I think using "on error = SKIP_FILE" is the way to go. That way, if there are any issues with individual records, they'll be skipped, and the rest of the data can be ingested smoothly. Seems like the most performant and cost-effective option.

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Nilsa

5 months ago

Hmm, I'm a bit confused by the different options. I'll need to double-check the Snowflake documentation to make sure I understand the differences between "on error = continue" and "on error = SKIP_FILE". Gotta make sure I pick the right approach.

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Bettina

5 months ago

I think the key here is to focus on the most performant and cost-effective way to ingest the data. Option D looks promising with the "on error = SKIP_FILE" setting, which could help avoid issues with problematic records.

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Larae

11 months ago

Ah, the age-old debate: to continue or to skip? I say, why not both? Use 'on error = SKIP_FILE' and then go out for a nice, relaxing purge. Ah, the life of a data engineer.

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Velda

9 months ago

Great idea, let's make sure we're being cost-effective too.

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Brynn

9 months ago

Sounds like a plan. Let's get this data ingested efficiently.

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Lenna

9 months ago

Agreed, we can always purge later if needed.

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Sunshine

10 months ago

Let's go with 'on error = SKIP_FILE' for now.

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Jessenia

10 months ago

So, combining 'on error = SKIP_FILE' and 'purge = TRUE' could be the best approach for this data ingestion process.

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Ling

10 months ago

That's true, 'purge = TRUE' can help with performance by removing files after they are successfully loaded.

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Leslee

10 months ago

But what about using 'purge = TRUE' in the copy into command? Wouldn't that help with performance?

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Shayne

10 months ago

I agree, using 'on error = SKIP_FILE' is a good way to handle errors during ingestion.

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Vernell

11 months ago

I think using on error = SKIP_FILE would be the best option to skip files with errors and continue the ingestion process smoothly.

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Erick

11 months ago

Hmm, I'm not sure about these options. 'FURGE = FALSE'? Is that even a real Snowflake command? I think I'll go with option D, just to be safe.

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Geraldine

11 months ago

Yeah, I think option D is the way to go. Let's go with that.

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Jacquelyne

11 months ago

I agree, option C sounds suspicious. Option D seems like the safest choice.

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Leonor

11 months ago

Option C is definitely not a real Snowflake command. I would go with option D as well.

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Tonja

12 months ago

But wouldn't using ON_ERROR = continue help in case of any errors during ingestion?

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Julieta

12 months ago

I disagree, I believe using purge = TRUE in the copy into command would be more cost-effective.

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Valentin

12 months ago

Option B looks good to me. 'purge = TRUE' will remove the CSV files from the stage after they've been successfully ingested, so you don't have to worry about storage costs or management.

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Elise

11 months ago

Yes, 'purge = TRUE' is definitely the way to go for a performant and cost-effective data ingestion process.

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Cordie

11 months ago

I agree, using 'purge = TRUE' is the most cost-effective way to handle the ingestion of the 10 TB of CSV data into Snowflake.

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Christoper

11 months ago

Option B looks good to me. 'purge = TRUE' will remove the CSV files from the stage after they've been successfully ingested, so you don't have to worry about storage costs or management.

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Tonja

12 months ago

I think we should use ON_ERROR = continue in the copy into command for better performance.

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Thaddeus

12 months ago

I think option D is the correct answer. 'on error = SKIP_FILE' allows you to skip any files with errors during the data ingestion process, which is more performant and cost-effective than having to manually intervene or restart the entire process.

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Malika

11 months ago

Yes, it's important to minimize any interruptions during the data ingestion process.

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Caprice

11 months ago

I think so too, skipping files with errors will definitely help with performance and cost.

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Margo

11 months ago

I agree, option D seems like the best choice for this scenario.

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