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2239474a87
Greatly improves performance of plan making, because we don't consider candidates in other racks, most of which will fail to be selected due to replication constraints (no rack overload). Also (but minor) reduces the overhead of candidate evaluation, as we don't have to evaluate rack load. Enabled only for rf_rack_valid_keyspaces because such setups guarantee that we will not need (because we must not) move tablets across racks, and we don't need to execute the general algorithm for the whole DC. Tested with perf-load-balancing, which performs a single scale-out operation on a cluster which initially has 10 nodes 88 shards each, 2 racks, RF=2, 70 tables, 256 tablets per table. Scale out adds 6 new nodes (same shard count). Time to reballance the cluster (plan making only, sum of all iterations, no streaming): Before: 16 min 25 s After: 0 min 25 s Before, plan making cost (single incremental iteration) alternated between fast (0.1 [s]) and slow (14.1 [s]): testlog - Rebalance iteration 7 took 14.156 [s]: mig=88, bad=88, first_bad=17741, eval=93874484, skiplist=0, skip: (load=0, rack=17653, node=0) testlog - Rebalance iteration 8 took 0.143 [s]: mig=88, bad=88, first_bad=88, eval=865407, skiplist=0, skip: (load=0, rack=0, node=0) The slow run chose min and max nodes in different racks, hence the fast path failed to find any candidates and we switched to exhaustive search of candidates in other nodes. After, all iterations are fast (0.1 [s] per rack, 0.2 [s] per plan-making). The plan is twice as large because it combines the output of two subsequent (pre-patch) plan-making calls. Fixes #26016 Closes scylladb/scylladb#26017 * github.com:scylladb/scylladb: test: perf: perf-load-balancing: Add parallel-scaleout scenario test: perf: perf-load-balancing: Convert to tool_app_template tablets: scheduler: Balance racks separately when rf_rack_valid_keyspaces is true