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fix(data-placement): normalize peer recovery traffic constraints #419

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5 changes: 3 additions & 2 deletions deploy/data_placement/src/model/data_placement.py
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Original file line number Diff line number Diff line change
Expand Up @@ -252,9 +252,10 @@ def enough_disks_assigned_to_each_group(model, group):

def calc_peer_recovery_traffic(model, disk, peer):
if self.qlinearize:
return po.quicksum(model.disk_in_same_group[disk,peer,group] for group in model.groups)
traffic = po.quicksum(model.disk_in_same_group[disk,peer,group] for group in model.groups)
else:
return po.quicksum(calc_disk_in_same_group(model, disk, peer, group) for group in model.groups)
traffic = po.quicksum(calc_disk_in_same_group(model, disk, peer, group) for group in model.groups)
return traffic * self.recovery_traffic_factor / (self.group_size - 1)

def peer_recovery_traffic_upper_bound(model, disk, peer):
if self.balanced_incomplete_block_design:
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13 changes: 13 additions & 0 deletions deploy/data_placement/test/test_model.py
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Expand Up @@ -71,6 +71,19 @@ def test_solve_placement_model_v25(chain_table_type, num_nodes, group_size):
)
model.run(pyomo_solver="appsi_highs", max_timelimit=30, auto_relax=True)

@pytest.mark.skipif(importlib.util.find_spec("highspy") is None, reason="cannot find solver")
def test_solve_chain_replication_bibd_with_highs(tmp_path):
model = DataPlacementModel(
chain_table_type="CR",
num_nodes=4,
num_targets_per_disk=3,
group_size=3,
bibd_only=True,
qlinearize=True,
relax_lb=0,
)
model.solve(pyomo_solver="appsi_highs", output_path=str(tmp_path))

@pytest.mark.parametrize('placement_params', placement_params)
@pytest.mark.skipif(importlib.util.find_spec("highspy") is None, reason="cannot find solver")
def test_solve_rebalance_model(placement_params):
Expand Down