Colearn · Early accessDistributed data processing · F01
F01 · Parallelism and the economics of distributionWhy can more workers make a job slower?
The problemA nightly data validation job took 175 seconds on 16 workers. The team moved it to 64, expecting it to finish sooner. It took 261 seconds — 86 seconds slower, with the same code and the same data.
01LessonsThree lessons on what sets a job’s runtime, and its bill.Read
02WorkbenchBuild worker-cost-sim, the simulator every later stage runs on.75–90 min
03TicketsDiagnose and repair four production tickets with your simulator.Repair
04Decision recordSize the fulfilment feed for today and two years of growth.Decide
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01→One large jobOne process works through every record, one after another.
02→Split the workCut it into equal pieces.
03→Multiple workersEach worker takes one piece, all at the same time.
04Combine resultsCollecting each result takes a turn, and every extra worker adds another.
Splitting work can reduce processing time, but coordinating workers also has a cost.
WorkCoordination, one turn per worker