Snowflake ARA-R01 Exam - Topic 4 Question 17 Discussion

Actual exam question for Snowflake's ARA-R01 exam

Question #: 17
Topic #: 4

A company has built a data pipeline using Snowpipe to ingest files from an Amazon S3 bucket. Snowpipe is configured to load data into staging database tables. Then a task runs to load the data from the staging database tables into the reporting database tables.

The company is satisfied with the availability of the data in the reporting database tables, but the reporting tables are not pruning effectively. Currently, a size 4X-Large virtual warehouse is being used to query all of the tables in the reporting database.

What step can be taken to improve the pruning of the reporting tables?

AEliminate the use of Snowpipe and load the files into internal stages using PUT commands.

BIncrease the size of the virtual warehouse to a size 5X-Large.

CUse an ORDER BY <cluster_key (s) > command to load the reporting tables.

DCreate larger files for Snowpipe to ingest and ensure the staging frequency does not exceed 1 minute.

Show Suggested Answer

Suggested Answer: C

Effective pruning in Snowflake relies on the organization of data within micro-partitions. By using an ORDER BY clause with clustering keys when loading data into the reporting tables, Snowflake can better organize the data within micro-partitions. This organization allows Snowflake to skip over irrelevant micro-partitions during a query, thus improving query performance and reducing the amount of data scanned12.

Reference =

* Snowflake Documentation on micro-partitions and data clustering2

* Community article on recognizing unsatisfactory pruning and improving it1

by Janet at Sep 09, 2024, 12:11 AM

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Chandra

3 months ago

Eliminating Snowpipe seems like a step backward, not a solution.

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Latrice

3 months ago

Definitely go with option C, it makes the most sense for pruning!

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Krystina

3 months ago

Wait, can larger files really improve Snowpipe performance?

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Salena

4 months ago

I don't think increasing the warehouse size will help with pruning.

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Becky

4 months ago

Using ORDER BY with cluster keys sounds like a solid plan!

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Barrett

4 months ago

I thought Snowpipe was supposed to handle everything efficiently, so eliminating it seems counterintuitive.

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Hubert

4 months ago

I feel like we practiced a question similar to this, and I think creating larger files could help with ingestion efficiency.

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Melissa

4 months ago

I'm not entirely sure, but I think increasing the warehouse size might not really solve the pruning issue.

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Alisha

5 months ago

I remember we discussed how clustering can help with pruning, so maybe option C is the way to go?

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Reita

5 months ago

I'm a bit unsure about the implications of eliminating Snowpipe and using PUT commands instead, as mentioned in option A. That seems like a pretty drastic change to the data pipeline, so I'll need to think carefully about the potential trade-offs before choosing that approach.

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Charisse

5 months ago

I'm pretty confident that the solution here is to use a cluster key to load the reporting tables, as suggested in option C. That should help with the pruning issue by organizing the data in a way that makes it more efficient to query.

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Man

5 months ago

Okay, let's see. The question is asking about improving the pruning of the reporting tables, and it looks like the current setup is using a 4X-Large virtual warehouse to query all the tables. I'm thinking option B, increasing the warehouse size, might be a good place to start.

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Audry

5 months ago

This seems like a pretty straightforward question about improving the pruning of reporting tables. I think I'll focus on understanding the key details about the current setup and then evaluate the options provided.

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Zona

5 months ago

Hmm, I'm a bit confused about the relationship between Snowpipe, the staging tables, and the reporting tables. I'll need to make sure I understand the data pipeline before I can decide on the best approach.

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Dominga

5 months ago

Hmm, I'm a bit confused on this one. It could be the backup policy, since monitoring the hard disks could be related to backups.

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Polly

1 year ago

That could also work, larger files might help with pruning efficiency.

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Sina

1 year ago

I'm not sure about that, maybe we should consider option D) Create larger files for Snowpipe to ingest.

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Yolando

1 year ago

I dunno, have they tried turning it off and on again? Seems like a classic IT problem to me.

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Carissa

1 year ago

Yeah, that might be a good solution to improve performance.

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Gladys

1 year ago

That could help with the pruning issue in the reporting tables.

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Annalee

1 year ago

Maybe they should try increasing the size of the virtual warehouse to a size 5X-Large.

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Casey

1 year ago

I agree with Polly, using ORDER BY can help improve pruning.

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Denna

1 year ago

You know, if they're really struggling with pruning, maybe they should just throw the whole reporting database away and start over. That's the *real* solution, right?

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Vivan

1 year ago

Option D sounds interesting. Bigger files and less frequent staging could help optimize the Snowpipe process. It's worth a shot!

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Emile

1 year ago

Let's give it a try and see if it improves the performance of the data pipeline.

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Rozella

1 year ago

I agree. Creating larger files for Snowpipe to ingest and adjusting the staging frequency could make a difference.

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Rolande

1 year ago

Yes, that could definitely help with the pruning issue in the reporting tables.

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Myong

1 year ago

Option D sounds interesting. Bigger files and less frequent staging could help optimize the Snowpipe process. It's worth a shot!

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Staci

1 year ago

Hmm, I'm not sure about that. Increasing the warehouse size seems like it might just be throwing more resources at the problem instead of addressing the root cause.

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Margurite

1 year ago

B: Yeah, that could definitely improve the performance without just increasing the warehouse size.

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Oliva

1 year ago

A: I think using an ORDER BY command might help with pruning the reporting tables more effectively.

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Polly

1 year ago

I think we should try option C) Use an ORDER BY command to load the reporting tables.

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Jessenia

1 year ago

I think option C is the way to go. Sorting the data in the reporting tables will definitely help with the pruning process.

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Alica

1 year ago

I think we should try creating larger files for Snowpipe to ingest and ensure the staging frequency does not exceed 1 minute.

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Mohammad

1 year ago

I agree, using an ORDER BY command will definitely help with pruning the reporting tables.

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Mitsue

1 year ago

I think we should try increasing the size of the virtual warehouse to see if that improves the pruning process.

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Wei

1 year ago

I agree, sorting the data using ORDER BY will definitely help with pruning.

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