Snowflake ARA-C01 Exam - Topic 2 Question 22 Discussion

Actual exam question for Snowflake's ARA-C01 exam

Question #: 22
Topic #: 2

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.

* Snowflake Documentation on micro-partitions and data clustering2

* Community article on recognizing unsatisfactory pruning and improving it1

by Lorrie at Mar 17, 2024, 12:58 AM

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Tamra

3 months ago

Wait, larger files for Snowpipe? That sounds counterintuitive!

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Lenny

3 months ago

Increasing the warehouse size doesn't really solve the pruning issue.

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Rana

3 months ago

Not sure about eliminating Snowpipe, seems risky.

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Dierdre

4 months ago

Agree, clustering is key for performance!

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Phung

4 months ago

I think using an ORDER BY command can really help with pruning.

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Xuan

4 months ago

I vaguely recall that Snowpipe is efficient for ingestion, but maybe it's not the best for pruning. I'm leaning towards option C for the ORDER BY command.

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Howard

4 months ago

I think we practiced a similar question where we had to optimize data loading. I wonder if creating larger files could help, like in option D.

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Wayne

4 months ago

I'm not entirely sure, but I feel like increasing the warehouse size won't really solve the pruning issue.

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Kenny

5 months ago

I remember discussing how clustering can help with pruning, so I think option C might be the right choice.

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Otis

5 months ago

The way I see it, the best approach would be to create larger files for Snowpipe to ingest and ensure the staging frequency doesn't exceed 1 minute, as suggested in option D. That could help improve the overall efficiency of the data pipeline and potentially address the pruning issue.

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Catarina

5 months ago

I'm leaning towards option C, which is to use an ORDER BY command to load the reporting tables. That could help with the pruning by ensuring the data is organized in a way that makes it easier to remove old or unnecessary data.

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Yen

5 months ago

Okay, I think I've got an idea. The question mentions using a 4X-Large virtual warehouse to query the reporting tables. Maybe we could try increasing the warehouse size to a 5X-Large, as suggested in option B. That might help with the pruning performance.

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Nelida

5 months ago

Hmm, I'm a bit confused by the question. It seems like the data pipeline is working well, but the reporting tables are the problem. Maybe we need to look at how the data is being loaded into those tables and see if there's a way to optimize the pruning process.

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Veta

5 months ago

I'm not entirely sure about this one, but I think the key might be to focus on the pruning of the reporting tables. The question mentions that the reporting tables are not pruning effectively, so that seems like the main issue to address.

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Clorinda

5 months ago

Hmm, I'm not totally confident on this one. I know the Messaging Metadata pattern is about separating the different types of data, but I can't quite remember which goes where. I'll have to think this through carefully.

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Diane

5 months ago

This is a tough call, but I think option B is the way to go. Relocating the class seems like the best way to minimize the disruption and keep the students engaged.

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Giuseppe

5 months ago

Hmm, I'm a bit confused on the difference between ESP and AH. I'll need to review my notes to make sure I understand the key services they each provide.

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