In complex Hadoop data pipelines, how does partitioning data in HDFS impact processing efficiency?
- Accelerates Data Replication
- Enhances Data Compression
- Improves Data Locality
- Minimizes Network Traffic
Partitioning data in HDFS improves processing efficiency by enhancing data locality. This means that computation is performed on nodes where the data is already stored, reducing the need for extensive data movement across the network and thereby improving overall processing speed.
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