How does the MapReduce Shuffle phase contribute to data processing efficiency?
- Data Compression
- Data Filtering
- Data Replication
- Data Sorting
The MapReduce Shuffle phase contributes to data processing efficiency by performing data sorting. During this phase, the output of the Map tasks is sorted and partitioned based on keys, ensuring that the data is grouped appropriately before reaching the Reduce tasks. Sorting facilitates faster data processing during the subsequent Reduce phase.
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