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Databricks Exam Databricks Machine Learning Professional Topic 2 Question 22 Discussion

Actual exam question for Databricks's Databricks Machine Learning Professional exam
Question #: 22
Topic #: 2
[All Databricks Machine Learning Professional Questions]

Which of the following statements describes streaming with Spark as a model deployment strategy?

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Suggested Answer: B

Contribute your Thoughts:

Chauncey
2 days ago
I thought it was B, real-time is the way to go.
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Wynell
8 days ago
Definitely D, that's how streaming works!
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Glennis
14 days ago
I’m leaning towards option A, but I’m not confident. I thought streaming was more about real-time processing rather than waiting for a job to run.
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Dorothea
19 days ago
I feel like option D sounds right, but I keep mixing up the terms "incrementally processed" and "batch processed."
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Kayleigh
24 days ago
I remember practicing a question similar to this, and I think the key is that it processes records as soon as a trigger is hit.
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Ty
1 month ago
I think streaming with Spark is about processing data in real-time, but I'm not sure if it's all types of records or just incremental ones.
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Alishia
1 month ago
I feel pretty confident about this one. Streaming with Spark is all about processing data incrementally as it arrives, so option D is the right answer. The key is that it's not waiting for a full batch to be processed.
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Aleta
1 month ago
Okay, I've got this. Streaming with Spark is all about processing data in real-time, so option B is the correct answer. The inference happens as soon as the data comes in, not in batches.
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Eleni
1 month ago
Hmm, this is a tricky one. I'm trying to remember the details about Spark's streaming capabilities. I think option D might be the right answer, but I'll need to double-check my notes to be sure.
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Kent
1 month ago
I think the key here is understanding the difference between batch and streaming processing. Option A sounds like it could be correct, but I'm not 100% sure.
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Dorathy
1 month ago
I'm a bit confused by the wording of these options. Can streaming really process "all types of records in real-time"? That sounds a bit broad to me. I'm leaning towards option A, but I'll need to think this through a bit more.
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Van
1 month ago
This is a good practice question. I'll carefully analyze the XML, the query options, and the expected output to determine the correct answer. Applying the XQuery concepts I've learned should help me solve this.
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Olga
1 month ago
I practiced a similar question earlier, and I think the correct answer is 14 days. That sounds familiar.
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Gladis
6 months ago
Wait, are we sure Spark even does streaming? I thought it was all about batch processing. Hmm, maybe I should have paid more attention in class...
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Desiree
5 months ago
Katie: Exactly, Spark can handle both batch processing and streaming.
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Katie
5 months ago
User 2: So, the answer would be D) The inference of incrementally processed records as soon as trigger is hit.
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Leonardo
5 months ago
User 1: Spark does support streaming, it can process data in real-time.
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Pansy
6 months ago
Haha, I bet the exam writer was having a real 'spark' of inspiration when they came up with these answer choices! But in all seriousness, I'm going with option D as well.
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Miles
5 months ago
Definitely, that's the best strategy for streaming with Spark.
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Roselle
6 months ago
Yeah, it makes sense to infer incrementally processed records when a trigger is hit.
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Huey
6 months ago
I agree, option D seems like the most accurate choice.
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Elizabeth
7 months ago
I'm torn between options B and D. Streaming should be about real-time inference, but the question specifically mentions Spark, so I'm not sure if option B is the best fit.
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Josephine
5 months ago
So, I think option D is the correct choice for streaming with Spark.
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Isadora
5 months ago
True, Spark is more about processing data in batches.
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Armanda
6 months ago
But the question mentions Spark, so maybe option D is more accurate.
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Josephine
6 months ago
Option B seems like the best fit for real-time inference.
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Ciara
7 months ago
I think option D is the correct answer, as it describes the inference of incrementally processed records as soon as a trigger is hit. Streaming with Spark is all about processing data in real-time, not in batches.
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Oretha
7 months ago
That makes sense, E does sound like a better option for streaming with Spark.
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Ariel
7 months ago
I disagree, I believe the answer is E because it mentions Spark job being run.
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Oretha
7 months ago
I think the answer is D, because it mentions incrementally processed records.
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