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What is the most common practical bottleneck when scaling a big data pipeline?

A Network shuffle and data movement between nodes
B CPU clock speed
C Disk capacity
D Number of columns

Answer

Network shuffle and data movement between nodes

Reducing shuffles through broadcast joins, better partitioning and pre-aggregation usually yields far more than adding hardware.

All Big data MCQs

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