The Shuffle Read: Fetching Across the Network

The second half of a shuffle is the read, which happens on the reduce side, the executors that will run the stage after the shuffle. Each reduce task is responsible for one output partition, say all the rows for region EU, and to assemble it, that task has to fetch its bucket from every map executor that wrote one. So a single reduce task reaches out across the network to many machines, pulls down each one's EU bucket, and combines them into the complete EU partition. This is where the all-to-all movement from the beginner tier physically happens. With M map tasks and R reduce tasks, the network sees up to M times R fetches, every reduce task pulling from every map output. This fan-out is why a shuffle saturates the network: it is not one big transfer but a dense mesh of many transfers hap

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