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Snowflake Exam ARA-C01 Topic 3 Question 45 Discussion

Actual exam question for Snowflake's ARA-C01 exam
Question #: 45
Topic #: 3
[All ARA-C01 Questions]

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?

Show Suggested Answer Hide 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 Trinidad at Jan 26, 2025, 09:42 PM

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Teresita
17 days ago
Hmm, I wonder if they could also try partitioning the reporting tables based on the clustering keys. That might help with pruning too.
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Vi
18 days ago
A is a strange suggestion. Eliminating Snowpipe and using PUT commands instead doesn't seem relevant to the question.
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King
19 days ago
B doesn't seem like the right solution. Increasing the warehouse size won't directly address the pruning problem.
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Kristal
20 days ago
D sounds like a good option too. Increasing the file size and frequency for Snowpipe could potentially help with the pruning issue.
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Glory
9 days ago
D sounds like a good option. It could help with the pruning issue.
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Bernardo
1 months ago
That's a good point, Teddy. Maybe we should consider both options C) and D) for better pruning.
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Teddy
1 months ago
But what about option D) Create larger files for Snowpipe to ingest? Wouldn't that also help?
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Ryan
1 months ago
I agree with Bernardo, using ORDER BY can help improve pruning.
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Pauline
1 months ago
I think the answer is C. Using an ORDER BY clause on the clustering key(s) will help improve the pruning of the reporting tables.
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Val
7 days ago
We should definitely try using the ORDER BY clause to see if it helps with the pruning efficiency.
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Shantay
15 days ago
I agree, that sounds like the right approach to optimize the pruning process.
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Aliza
17 days ago
I think the answer is C. Using an ORDER BY clause on the clustering key(s) will help improve the pruning of the reporting tables.
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Loreta
25 days ago
That makes sense, it will optimize the data storage and retrieval process.
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Kristin
1 months ago
I agree, using an ORDER BY clause on the clustering key(s) will definitely help with pruning.
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Bernardo
2 months ago
I think we should try option C) Use an ORDER BY command to load the reporting tables.
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