Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

Databricks Machine Learning Professional Exam - 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?

Show Suggested Answer Hide Answer
Suggested Answer: B

by Casie at Aug 06, 2024, 04:19 PM

Limited Time Offer

25%

Off

Get Premium Databricks Machine Learning Professional Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

0/2000 characters
Submit Cancel
Elina
4 months ago
E sounds plausible, but isn't it a bit slow?
upvoted 0 times
...
Evangelina
5 months ago
A is just batch processing, not streaming!
upvoted 0 times
...
Ellsworth
5 months ago
Wait, so C is wrong? That seems odd.
upvoted 0 times
...
Chauncey
5 months ago
I thought it was B, real-time is the way to go.
upvoted 0 times
...
Wynell
5 months ago
Definitely D, that's how streaming works!
upvoted 0 times
...
Glennis
6 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.
upvoted 0 times
...
Dorothea
6 months ago
I feel like option D sounds right, but I keep mixing up the terms "incrementally processed" and "batch processed."
upvoted 0 times
...
Kayleigh
6 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.
upvoted 0 times
...
Ty
6 months 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.
upvoted 0 times
...
Alishia
6 months 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.
upvoted 0 times
...
Aleta
6 months 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.
upvoted 0 times
...
Eleni
6 months 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.
upvoted 0 times
...
Kent
6 months 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.
upvoted 0 times
...
Dorathy
6 months 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.
upvoted 0 times
...
Van
6 months 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.
upvoted 0 times
...
Olga
6 months ago
I practiced a similar question earlier, and I think the correct answer is 14 days. That sounds familiar.
upvoted 0 times
...
Gladis
11 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...
upvoted 0 times
Desiree
10 months ago
Katie: Exactly, Spark can handle both batch processing and streaming.
upvoted 0 times
...
Katie
10 months ago
User 2: So, the answer would be D) The inference of incrementally processed records as soon as trigger is hit.
upvoted 0 times
...
Leonardo
10 months ago
User 1: Spark does support streaming, it can process data in real-time.
upvoted 0 times
...
...
Pansy
11 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.
upvoted 0 times
Miles
10 months ago
Definitely, that's the best strategy for streaming with Spark.
upvoted 0 times
...
Roselle
11 months ago
Yeah, it makes sense to infer incrementally processed records when a trigger is hit.
upvoted 0 times
...
Huey
11 months ago
I agree, option D seems like the most accurate choice.
upvoted 0 times
...
...
Elizabeth
12 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.
upvoted 0 times
Josephine
10 months ago
So, I think option D is the correct choice for streaming with Spark.
upvoted 0 times
...
Isadora
11 months ago
True, Spark is more about processing data in batches.
upvoted 0 times
...
Armanda
11 months ago
But the question mentions Spark, so maybe option D is more accurate.
upvoted 0 times
...
Josephine
11 months ago
Option B seems like the best fit for real-time inference.
upvoted 0 times
...
...
Ciara
12 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.
upvoted 0 times
...
Oretha
12 months ago
That makes sense, E does sound like a better option for streaming with Spark.
upvoted 0 times
...
Ariel
1 year ago
I disagree, I believe the answer is E because it mentions Spark job being run.
upvoted 0 times
...
Oretha
1 year ago
I think the answer is D, because it mentions incrementally processed records.
upvoted 0 times
...

Save Cancel