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Salesforce Certified Platform Data Architect (Plat-Arch-201) Exam - Topic 1 Question 50 Discussion

Actual exam question for Salesforce's Salesforce Certified Platform Data Architect (Plat-Arch-201) exam
Question #: 50
Topic #: 1
[All Salesforce Certified Platform Data Architect (Plat-Arch-201) Questions]

DreamHouse Realty has 15 million records in the Order_c custom object. When running a bulk query, the query times out.

What should be considered to address this issue?

Show Suggested Answer Hide Answer
Suggested Answer: B

single-select restricted picklist with defined choices can be a way to configure customer type. The article states that picklists are fields that allow users to select one or more predefined values from a list, and restricted picklists ensure that users can only select from the defined values. This can help to limit the choices for customer type and ensure data quality.


by Glory at Sep 18, 2024, 05:36 AM

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Ty
3 months ago
Metadata API won't help with performance issues like this.
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Maryanne
3 months ago
15 million records? That sounds like a nightmare for any query!
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Rana
3 months ago
I thought the Streaming API would be better for this?
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Thurman
4 months ago
Definitely agree, PK Chunking can help with timeouts!
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Eura
4 months ago
PK Chunking is a solid option for large datasets.
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Verdell
4 months ago
The Streaming API seems like it’s for real-time data, not bulk queries, right? I’m a bit confused about which one to pick.
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Carin
4 months ago
I practiced a similar question where PK Chunking helped with timeouts, so I feel like that might be the right choice here.
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Deangelo
4 months ago
I think the Metadata API is more about managing metadata rather than handling bulk queries, so I’m leaning away from that option.
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Helene
5 months ago
I remember something about PK Chunking being useful for large data sets, but I'm not entirely sure how it works in this context.
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Felicitas
5 months ago
I think the key here is that we're dealing with a large dataset. B. PK Chunking is probably the way to go - it allows you to break the query into smaller, more manageable chunks based on the primary key. That should help avoid the timeout issue.
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Gene
5 months ago
Okay, let's see. If the query is timing out, that suggests we need a more efficient way to retrieve the data. The Tooling API and Metadata API options don't seem directly relevant to that. The Streaming API could work, but PK Chunking sounds like the most straightforward solution here.
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Yasuko
5 months ago
Hmm, I'm not totally sure about this one. The options seem a bit technical, and I'm not super familiar with all the different Salesforce APIs. I'll have to think this through carefully.
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Nana
5 months ago
I'm pretty sure the answer is B. PK Chunking, since the question mentions the query timing out with a large number of records. That's a common issue that can be solved by breaking the query into smaller chunks.
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Na
5 months ago
I think I've seen similar questions where output was expected, but I can't recall if it included duplicates or not.
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Elmira
10 months ago
I'm not too familiar with the Tooling API, but the Metadata API and Streaming API don't seem quite right for this use case.
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Kaitlyn
10 months ago
B) PK Chunking might also be a good option to consider for handling large data volumes.
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Svetlana
10 months ago
A) Tooling API could help with optimizing the query performance.
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Candra
11 months ago
PK Chunking seems like the way to go here. It's designed to handle large data sets without timing out.
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Tawna
9 months ago
PK Chunking seems like the way to go here. It's designed to handle large data sets without timing out.
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Dianne
10 months ago
C) Metadata API
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Cheryll
10 months ago
B) PK Chunking
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Rosalind
10 months ago
A) Tooling API
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Dell
11 months ago
I'm not sure about PK Chunking. Maybe we should also look into using the Tooling API for this issue.
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Malcom
11 months ago
I agree with Malcombye. PK Chunking can help improve performance when dealing with large datasets.
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Bobbye
11 months ago
I think we should consider using PK Chunking to address the query timeout issue.
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