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Databricks Exam Databricks-Certified-Data-Analyst-Associate Topic 2 Question 23 Discussion

Actual exam question for Databricks's Databricks-Certified-Data-Analyst-Associate exam
Question #: 23
Topic #: 2
[All Databricks-Certified-Data-Analyst-Associate Questions]

In which of the following situations should a data analyst use higher-order functions?

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Suggested Answer: C

Higher-order functions are a simple extension to SQL to manipulate nested data such as arrays. A higher-order function takes an array, implements how the array is processed, and what the result of the computation will be. It delegates to a lambda function how to process each item in the array. This allows you to define functions that manipulate arrays in SQL, without having to unpack and repack them, use UDFs, or rely on limited built-in functions. Higher-order functions provide a performance benefit over user defined functions.Reference:Higher-order functions | Databricks on AWS,Working with Nested Data Using Higher Order Functions in SQL on Databricks | Databricks Blog,Higher-order functions - Azure Databricks | Microsoft Learn,Optimization recommendations on Databricks | Databricks on AWS


by Cherelle at Sep 16, 2024, 06:09 AM

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Mitsue
6 months ago
Higher-order functions? Is that like when you order a burger and they ask if you want fries with that?
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Latanya
6 months ago
This question is making my brain hurt. I'll just pick C and hope the Catalyst Optimizer can handle it.
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Barbra
6 months ago
B, for sure. Converting custom logic to Python-native code is the whole point of using higher-order functions, isn't it?
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Lavera
5 months ago
B, for sure. Converting custom logic to Python-native code is the whole point of using higher-order functions, isn't it?
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Casandra
5 months ago
E) When built-in functions need to run through the Catalyst Optimizer
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Antonette
5 months ago
D) When built-in functions are taking too long to perform tasks
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Patrick
5 months ago
C) When custom logic needs to be applied at scale to array data objects
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Azalee
5 months ago
B) When custom logic needs to be converted to Python-native code
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Kati
5 months ago
A) When custom logic needs to be applied to simple, unnested data
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Eun
6 months ago
D is the way to go! If built-in functions are taking too long, higher-order functions can really speed things up.
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Joni
6 months ago
I think C is the correct answer here. Higher-order functions are great for applying custom logic at scale to array data objects.
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Lelia
5 months ago
Yes, that's correct. Higher-order functions are perfect for handling array data objects efficiently.
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Charlena
5 months ago
C) When custom logic needs to be applied at scale to array data objects
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Arletta
5 months ago
A) When custom logic needs to be applied to simple, unnested data
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Carmen
6 months ago
E, obviously. The Catalyst Optimizer is the secret sauce for any data analyst worth their salt. Higher-order functions are the way to unlock its power!
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Theron
7 months ago
But what about when built-in functions are taking too long to perform tasks? Wouldn't using higher-order functions help speed up the process?
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Flo
7 months ago
Higher-order functions? That's just fancy talk for 'doing math with functions'. I'll go with A, keep it simple, you know?
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Rashad
6 months ago
User 3: Agreed, A is the way to go for that situation.
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Louvenia
6 months ago
User 2: Yeah, higher-order functions are just about applying custom logic to simple data.
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Jeannine
6 months ago
I think A is the right choice, keep it simple.
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Kristofer
7 months ago
I agree with Haydee. Using higher-order functions can make it easier to apply custom logic to large datasets efficiently.
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Lenna
7 months ago
Hmm, I'm not sure about this one. I guess I'll go with B since converting custom logic to Python-native code seems like a good use case for higher-order functions.
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Haydee
7 months ago
I think a data analyst should use higher-order functions when custom logic needs to be applied at scale to array data objects.
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Lonny
7 months ago
D seems like the obvious choice here. If built-in functions are taking too long, higher-order functions can optimize the process.
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Shaun
6 months ago
E) When built-in functions need to run through the Catalyst Optimizer
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Marleen
6 months ago
D) When built-in functions are taking too long to perform tasks
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Kimi
6 months ago
D) When built-in functions are taking too long to perform tasks
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Cammy
6 months ago
C) When custom logic needs to be applied at scale to array data objects
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Stanford
6 months ago
C) When custom logic needs to be applied at scale to array data objects
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Reita
6 months ago
A) When custom logic needs to be applied to simple, unnested data
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Vi
6 months ago
A) When custom logic needs to be applied to simple, unnested data
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Cassandra
7 months ago
I think the correct answer is C. Higher-order functions are great for applying custom logic at scale to array data objects.
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Juan
7 months ago
I think it's C too. It makes sense to use higher-order functions for array data objects.
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Juan
7 months ago
I agree, higher-order functions are perfect for applying custom logic at scale to array data objects.
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