How does data partitioning in Hadoop affect the performance of data transformation processes?
- Decreases Parallelism
- Improves Sorting
- Increases Parallelism
- Reduces Disk I/O
Data partitioning in Hadoop increases parallelism by distributing data across nodes. This enhances the efficiency of data transformation processes as multiple nodes can work on different partitions concurrently, speeding up overall processing.
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