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Answer: Consider data locality to minimize network traffic and use local computations.
Considering data locality helps in minimizing network traffic and leveraging local computations, which is crucial for efficient data processing in a distributed environment. Ignoring these factors can lead to increased network congestion and inefficient use of computational resources.
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In a distributed computing environment, describe the challenges you might face when splitting a large dataset using Spark ML and how you would address these challenges to ensure an effective and representative split. Discuss the considerations for data locality, network bandwidth, and computational resources.
A
Ignore data locality and rely solely on random splits.
B
Consider data locality to minimize network traffic and use local computations.
C
Split data without considering computational resources.
D
Use only a subset of the data for splitting to reduce network bandwidth.