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Ryan Marcus @ryanmarcus.discuss.systems.ap.brid.gy · 08/05/2025

When modern analytic databases process `GROUP BY` queries, they tend to use a partitioning strategy for parallelism. The conventional wisdom is that partitioning has better scalability due to lower contention. But is this wisdom still true in 2025? Penn […] [Original post on discuss.systems]

A diagram showing a two-stage parallel processing system involving key-value pairs. On the left, a column labeled "K V" holds key-value pairs divided into morsels (small batches) for processing. Stage 1 is labeled "ticketing", where keys are matched against a shared hash table (middle column labeled "K T") to obtain a ticket (index). These tickets help arrange the data into a new table (right-middle column labeled "T K V"). Stage 2, labeled "update", uses the ticket to update values into a shared result vector (rightmost column labeled "V") at the index specified by the ticket. Blue and red colors distinguish different morsels processed concurrently.

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