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Snowflake Exam ARA-R01 Topic 1 Question 35 Discussion

Actual exam question for Snowflake's ARA-R01 exam
Question #: 35
Topic #: 1
[All ARA-R01 Questions]

A table for IOT devices that measures water usage is created. The table quickly becomes large and contains more than 2 billion rows.

The general query patterns for the table are:

1. DeviceId, lOT_timestamp and Customerld are frequently used in the filter predicate for the select statement

2. The columns City and DeviceManuf acturer are often retrieved

3. There is often a count on Uniqueld

Which field(s) should be used for the clustering key?

Show Suggested Answer Hide Answer
Suggested Answer: C

A clustering key is a subset of columns or expressions that are used to co-locate the data in the same micro-partitions, which are the units of storage in Snowflake. Clustering can improve the performance of queries that filter on the clustering key columns, as it reduces the amount of data that needs to be scanned. The best choice for a clustering key depends on the query patterns and the data distribution in the table. In this case, the columns DeviceId, IOT_timestamp, and CustomerId are frequently used in the filter predicate for the select statement, which means they are good candidates for the clustering key. The columns City and DeviceManufacturer are often retrieved, but not filtered on, so they are not as important for the clustering key. The column UniqueId is used for counting, but it is not a good choice for the clustering key, as it is likely to have a high cardinality and a uniform distribution, which means it will not help to co-locate the data. Therefore, the best option is to use DeviceId and CustomerId as the clustering key, as they can help to prune the micro-partitions and speed up the queries.Reference:Clustering Keys & Clustered Tables,Micro-partitions & Data Clustering,A Complete Guide to Snowflake Clustering


by Polly at Jul 12, 2025, 10:29 PM

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Shenika
24 hours ago
Ooh, this is a tricky one! I'm gonna have to go with C. DeviceId and CustomerID seem like the perfect combo to keep that massive table humming along.
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Alica
12 days ago
I disagree with Rozella, using lOT_timestamp seems more logical for this scenario.
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Leota
15 days ago
Haha, UniqueID as the clustering key? That's like trying to use a snowflake as a doorstop - it just doesn't make sense! Gotta go with C on this one.
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Harrison
3 days ago
Yeah, I agree. Deviceld and Customerld seem like the best choice for the clustering key.
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Elli
9 days ago
UniqueID as the clustering key? That's like trying to use a snowflake as a doorstop - it just doesn't make sense! Gotta go with C on this one.
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Rozella
16 days ago
I believe Deviceld and Customerld should be used for the clustering key.
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Maryann
17 days ago
I agree with Veronika, lOT_timestamp makes sense for efficient filtering.
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Veronika
22 days ago
I think the clustering key should be lOT_timestamp.
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Mollie
29 days ago
I'm torn between B and C. The frequent use of City and DeviceManufacturer is tempting, but the fact that DeviceId and CustomerID are used in the filter predicate makes me lean towards C.
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Gussie
1 months ago
For a table with over 2 billion rows, the clustering key should definitely include the frequently used DeviceId and CustomerID. That's a no-brainer!
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Nidia
24 hours ago
A) lOT_timestamp
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