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Exam AI-100 topic 1 question 10 discussion

Actual exam question from Microsoft's AI-100
Question #: 10
Topic #: 1
[All AI-100 Questions]

You deploy an infrastructure for a big data workload.
You need to run Azure HDInsight and Microsoft Machine Learning Server. You plan to set the RevoScaleR compute contexts to run rx function calls in parallel.
What are three compute contexts that you can use for Machine Learning Server? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  • A. SQL
  • B. Spark
  • C. local parallel
  • D. HBase
  • E. local sequential
Show Suggested Answer Hide Answer
Suggested Answer: ABC 🗳️
Remote computing is available for specific data sources on selected platforms. The following tables document the supported combinations.
✑ RxInSqlServer, sqlserver: Remote compute context. Target server is a single database node (SQL Server 2016 R Services or SQL Server 2017 Machine
Learning Services). Computation is parallel, but not distributed.
✑ RxSpark, spark: Remote compute context. Target is a Spark cluster on Hadoop.
✑ RxLocalParallel, localpar: Compute context is often used to enable controlled, distributed computations relying on instructions you provide rather than a built-in scheduler on Hadoop. You can use compute context for manual distributed computing.
References:
https://docs.microsoft.com/en-us/machine-learning-server/r/concept-what-is-compute-context
by jikku at June 8, 2020, 6:17 a.m.

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damirbek369
Highly Voted 4 years, 10 months ago
I think A,B,C is correct. In this link https://docs.microsoft.com/en-us/machine-learning-server/r/concept-what-is-compute-context , it is indicated which RevoSvaleR compute context are available, which are local, spark, sqlserver, localpar, dopar. If you are going to run R script from an Edge, the possible values of the context are: local sequential, local parallel, Map Reduce and Spark. https://docs.microsoft.com/en-us/azure/hdinsight/r-server/r-server-compute-contexts.
upvoted 7 times
robotcop
4 years, 4 months ago
if based on your last link given https://docs.microsoft.com/en-us/azure/hdinsight/r-server/r-server-compute-contexts , the correct option should be Spark, Local Parallel & Local Sequential . Answer should be B, C, E right?
upvoted 2 times
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rveney
Most Recent 1 year, 10 months ago
the three compute contexts you can use for Machine Learning Server to run rx function calls in parallel are B. Spark, C. local parallel, and E. local sequential.
upvoted 1 times
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gameoflove
3 years, 8 months ago
The correct one is B,C and E because he is processing BIg data on HD insight. https://docs.microsoft.com/en-us/azure/hdinsight/r-server/r-server-compute-contexts
upvoted 1 times
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aitruthseeker
4 years, 3 months ago
"You plan to set the RevoScaleR compute contexts to run rx function calls in PARALLEL." Yet people Say E instead of A
upvoted 2 times
Cornholioz
4 years, 3 months ago
That's because the documentation for compute context for an edge node says Local sequential does parallelized execution. However, I found this: https://docs.microsoft.com/en-us/machine-learning-server/r-reference/revoscaler/revoscaler#7-compute-context-functions No one posted this link but I think it is the right one to refer here for RevoScaleR. It does list Spark and Parallel clearly. But doesn't say Parallel execution for SQL and LocalSeq. Since LocalSeq does say "sequential computations" so I'm going with given answer: SQL, Local parallel and Spark. A, B, C
upvoted 4 times
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nohaph
4 years, 3 months ago
The Answer is wrong. The correct one is B,C and E because he is processing BIg data on HD insight. https://docs.microsoft.com/en-us/azure/hdinsight/r-server/r-server-compute-contexts But if he was working on small data then the answer will be A, B, and C( although I am not sure about C in the small data case) https://docs.microsoft.com/en-us/machine-learning-server/r/tutorial-rxexecby
upvoted 2 times
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Anirudh2020
4 years, 5 months ago
ABC is correct
upvoted 1 times
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ammarkareem
4 years, 9 months ago
correct answer is ABC
upvoted 3 times
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jikku
4 years, 10 months ago
B,C,E seems right
upvoted 1 times
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