- Just like HDFS slices and distributes the chunk of data to individual nodes, each household submits the lunchbox to a Dabbawala.
- All the lunchboxes are collected at the common place for tagging them and to put them into carriages with unique codes. This is the job of the Mapper!
- Based on the code, carriages that need to go to the common destination are sorted and on-boarded to the respective trains. This is called Shuffle and Sort phase in MapReduce.
- At each railway station, the Dabbawala picks up the carriage and delivers each box in that to respective customers. This is the Reduce phase.
Just like the way each node in the cluster does its job without the knowledge of other processes, each Dabbawala participates in the workflow just by focusing on his task. This an evidence of how a parallelized environment can scale better.
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Read the complete fascination story Mumbai DabbaWala -Apache Hadoop First successful implementation
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