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Answer: Decreasing the number of nodes or VMs, while keeping the total storage constant, will enhance shuffle performance by minimizing network and disk I/O.
Shuffling is a critical process that involves reorganizing, grouping, or redistributing data across various nodes in a cluster. This operation is resource-intensive, requiring significant network and disk I/O. By reducing the number of nodes or VMs in a cluster, the volume of data transferred over the network during shuffles is lessened. Moreover, fewer nodes mean reduced disk I/O for reading and writing shuffled data, leading to quicker and more efficient shuffle operations due to decreased network bandwidth contention. Therefore, for operations necessitating numerous shuffles, Databricks advises using a smaller number of nodes. Additional Information: Best practices for Cluster configurations
Author: LeetQuiz Editorial Team
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What impact does decreasing the number of nodes or VMs in a cluster, while maintaining the same total storage, have on data shuffling?
A
Decreasing the number of nodes or VMs, while keeping the total storage constant, will enhance shuffle performance by minimizing network and disk I/O.
B
Decreasing the number of nodes or VMs, with the total storage unchanged, will degrade the overall cluster performance.
C
Decreasing the number of nodes or VMs, without altering the total storage, will not influence shuffle operations.
D
Decreasing the number of nodes or VMs, while the total storage remains the same, will escalate network and disk I/O for shuffle operations.
E
Decreasing the number of nodes or VMs, with the total storage constant, will solely impact CPU utilization during shuffle operations.
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