Why this scales serving
More replicas of a hot table’s data, across more plan executors, means more of the fleet can serve that table’s queries in parallel — the same reasoning as adding query-serving capacity generally (see Architecture), applied per table rather than cluster-wide. Replication also gives a table fault tolerance: losing one plan executor does not take its data offline if another replica still holds it. A single query that reads several tables routes every read to the same replica group — the intersection of the tables’ assigned groups, trying a lead group first and falling back through the rest of the order if it has no healthy plan executor. Keeping one query’s reads co-located protects the locality of whichever group’s cache is already warm for it, rather than letting each table’s read drift to a different group. This table is assigned to two replica groups, each at replication factor 2: four plan executors in total, each holding a full copy of the table’s data. Adding a third group, or raising RF within a group, adds more plan executors that can serve this table’s reads in parallel — scaling throughput for this one table without touching any other table’s placement.Scaling interfaces
- Distributed Search for how a query divides across query nodes and plan executors generally.
- Architecture for the components a replica group is made of.