[BUG] `*(block sparse, dense)` (and vice versa) is slow

I found that even with an empty BlockSparseArray, doing a matrix vector mul is slow and causes large allocations. Is this expected behavior?

julia> using BlockArrays, BlockSparseArrays

julia> using BenchmarkTools

julia> cnt = fill(16, 128);

julia> bsa = BlockSparseArray{T}(undef, cnt, cnt);

julia> o = ones(2048);

julia> @benchmark $(bsa) * $(o)
BenchmarkTools.Trial: 4 samples with 1 evaluation per sample.
 Range (min … max):  1.603 s …   1.627 s  ┊ GC (min … max): 21.85% … 21.13%
 Time  (median):     1.613 s              ┊ GC (median):    21.64%
 Time  (mean ± σ):   1.614 s ± 10.349 ms  ┊ GC (mean ± σ):  21.63% ±  0.36%

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  1.6 s          Histogram: frequency by time        1.63 s <

 Memory estimate: 17.06 GiB, allocs estimate: 29376515.

Start by reproducing the provided BenchmarkTools case for an empty BlockSparseArray multiplied by a dense vector. Trace the matrix-vector multiplication entry point and allocation-heavy path; done means the empty case no longer incurs the reported large allocations and multi-second runtime, with benchmark coverage for the regression.