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Snowflake ADA-C01 Exam - Topic 1 Question 4 Discussion

Actual exam question for Snowflake's ADA-C01 exam
Question #: 4
Topic #: 1
[All ADA-C01 Questions]

A Snowflake Administrator has a multi-cluster virtual warehouse and is using the Snowflake Business Critical edition. The minimum number of clusters is set to 2 and the

maximum number of clusters is set to 10. This configuration works well for the standard workload, rarely exceeding 5 running clusters. However, once a month the

Administrator notes that there are a few complex long-running queries that are causing increased queue time and the warehouse reaches its maximum limit at 10 clusters.

Which solutions will address the issues happening once a month? (Select TWO).

Show Suggested Answer Hide Answer
Suggested Answer: A, B

According to the Snowflake documentation1, a multi-cluster warehouse is a virtual warehouse that consists of multiple clusters of compute resources that can scale up or down automatically to handle the concurrency and performance needs of the queries submitted to the warehouse. A multi-cluster warehouse has a minimum and maximum number of clusters that can be specified by the administrator. Option A is a possible solution to address the issues happening once a month, as it allows the administrator to use a task to increase the cluster size for the time period that the more complex queries are running and another task to reduce the size of the cluster once the complex queries complete. This way, the warehouse can have more resources available to handle the complex queries without reaching the maximum limit of 10 clusters, and then return to the normal cluster size to save costs. Option B is another possible solution to address the issues happening once a month, as it allows the administrator to have the group running the complex monthly queries use a separate appropriately-sized warehouse to support their workload. This way, the warehouse can isolate the complex queries from the standard workload and avoid queue time and resource contention. Option C is not a recommended solution to address the issues happening once a month, as it would increase the costs and complexity of managing the multi-cluster warehouse, and may not solve the underlying problem of inefficient queries. Option D is a good practice to improve the performance of the queries, but it is not a direct solution to address the issues happening once a month, as it requires analyzing and optimizing the complex queries using clustering keys or materialized views, which may not be feasible or effective in all cases. Option E is not a recommended solution to address the issues happening once a month, as it would increase the costs and waste resources by starting more clusters than needed for the standard workload.


Contribute your Thoughts:

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Casie
3 months ago
C might just be overkill, 10 should be enough if managed right.
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Glenna
3 months ago
A is a bit risky, managing tasks for scaling could get messy.
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Hassie
3 months ago
Wait, can you really increase the max to 20? That seems excessive.
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Devorah
4 months ago
I think D is also a good idea, optimizing those queries could help a lot!
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Kallie
4 months ago
Option B seems like a solid choice for handling those complex queries.
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Cherri
4 months ago
I think using a task to adjust the cluster size sounds like a viable solution, but I'm not confident if it's the best approach for this scenario.
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Ilona
4 months ago
I feel like we practiced a question about optimizing queries with clustering keys. Maybe that's a good option to consider here?
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Allene
4 months ago
I'm not entirely sure, but I think increasing the maximum number of clusters could be a quick fix for those peak times.
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Laquita
5 months ago
I remember we discussed using a separate warehouse for specific workloads in class. That might help with the monthly queries.
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Erasmo
5 months ago
I'm leaning towards the query optimization approach. If we can make those complex queries more efficient, we might be able to avoid the need for all the cluster scaling and separate warehouses. Worth a shot, right?
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Krystal
5 months ago
I'm not sure about the task solution. Wouldn't that require a lot of manual intervention? I think the separate warehouse option is the way to go, as long as we can make sure it's sized appropriately.
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Harrison
5 months ago
Okay, I've got this. The key is using a task to dynamically scale the cluster size. That way, we can handle the peak load without wasting resources the rest of the time. And using a separate warehouse for the complex queries is a great idea too.
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Julieta
5 months ago
Hmm, I'm a bit confused by the options here. Increasing the maximum clusters seems like it could work, but I'm not sure if that's the most efficient solution. Maybe I should focus on optimizing the complex queries first.
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Chery
5 months ago
This looks like a tricky one. I'm thinking a combination of increasing the cluster size temporarily and using a separate warehouse for the complex queries might be the best approach.
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Cheryll
5 months ago
Setting the interface to passive and configuring the access control policy with the right policies seems like the logical approach to meet the requirement. I'm feeling confident about this one.
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Cherri
5 months ago
This question seems straightforward, I think the answer is A - the Federal Data Protection Act in Germany is known for its focus on "Data Handlers".
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Jordan
5 months ago
Okay, let me go through the options step-by-step to figure this out.
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