For a cluster experiencing uneven data distribution, what optimization strategy should be implemented?
- Data Compression
- Data Locality
- Data Replication
- Data Shuffling
In a scenario of uneven data distribution, implementing the optimization strategy of Data Shuffling is essential. Data Shuffling redistributes data across the cluster to achieve a more balanced workload, preventing hotspots and ensuring efficient parallel processing in a Hadoop cluster.
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