Discuss Databricks Databricks Machine Learning Professional Exam Topic 2 Question 22

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

AThe inference of batch processed records as soon as a trigger is hit

BThe inference of all types of records in real-time

CThe inference of batch processed records as soon as a Spark job is run

DThe inference of incrementally processed records as soon as trigger is hit

EThe inference of incrementally processed records as soon as a Spark job is run

Suggested Answer: B

Get Premium Databricks Machine Learning Professional Questions as Interactive Web-Based Practice Test or PDF Real Exam Format Detailed Explanations Instant Access Get Your Practice Test

33 comments · newest first

Elina 10 months ago

E sounds plausible, but isn't it a bit slow?

Evangelina 11 months ago

A is just batch processing, not streaming!

Ellsworth 11 months ago

Wait, so C is wrong? That seems odd.

Chauncey 11 months ago

I thought it was B, real-time is the way to go.

Wynell 11 months ago

Definitely D, that's how streaming works!

Glennis 12 months 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.

Dorothea 12 months ago

I feel like option D sounds right, but I keep mixing up the terms "incrementally processed" and "batch processed."

Kayleigh 12 months 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.

Ty 1 year 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.

Alishia 1 year 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.

Aleta 1 year 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.

Eleni 1 year 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.

Kent 1 year 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.

Dorathy 1 year 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.

Van 1 year 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.

Olga 1 year ago

I practiced a similar question earlier, and I think the correct answer is 14 days. That sounds familiar.

Gladis 1 year 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...

Desiree 1 year ago

↳ replying to Gladis

Katie: Exactly, Spark can handle both batch processing and streaming.

Katie 1 year ago

↳ replying to Gladis

User 2: So, the answer would be D) The inference of incrementally processed records as soon as trigger is hit.

Leonardo 1 year ago

↳ replying to Gladis

User 1: Spark does support streaming, it can process data in real-time.

Pansy 1 year 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.

Miles 1 year ago

↳ replying to Pansy

Definitely, that's the best strategy for streaming with Spark.

Roselle 1 year ago

↳ replying to Pansy

Yeah, it makes sense to infer incrementally processed records when a trigger is hit.

Huey 1 year ago

↳ replying to Pansy

I agree, option D seems like the most accurate choice.

Elizabeth 1 year 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.

Josephine 1 year ago

↳ replying to Elizabeth

So, I think option D is the correct choice for streaming with Spark.

Isadora 1 year ago

↳ replying to Elizabeth

True, Spark is more about processing data in batches.

Armanda 1 year ago

↳ replying to Elizabeth

But the question mentions Spark, so maybe option D is more accurate.

Josephine 1 year ago

↳ replying to Elizabeth

Option B seems like the best fit for real-time inference.

Ciara 1 year 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.

Oretha 2 years ago

That makes sense, E does sound like a better option for streaming with Spark.

Ariel 2 years ago

I disagree, I believe the answer is E because it mentions Spark job being run.

Oretha 2 years ago

I think the answer is D, because it mentions incrementally processed records.

Databricks Machine Learning Professional Exam - Topic 2 Question 22 Discussion