error instead of widening index types in sparse (#33083)

Followup to https://github.com/JuliaLang/julia/pull/31724/files#r317686891; instead of widening the index type dynamically based upon the index vector length, just throw an error in the case where the index type cannot hold all the indices in a CSC format. This previously was an OOB access (and likely segfault) in 1.2, so throwing an error here is not a breaking change -- and throwing an error restores type stability, addressing the performance regression flagged in #32985.

(cherry picked from commit 9725fb4)

Author: mbauman

stdlib/SparseArrays/src/sparsematrix.jl

@@ -630,9 +630,8 @@ function sparse(I::AbstractVector{Ti}, J::AbstractVector{Ti}, V::AbstractVector{
               "length(I) (=$(length(I))) == length(J) (= $(length(J))) == length(V) (= ",
               "$(length(V)))")))
     end
-    Tj = Ti
-    while isbitstype(Tj) && coolen >= typemax(Tj)
-        Tj = widen(Tj)
+    if Base.hastypemax(Ti) && coolen >= typemax(Ti)
+        throw(ArgumentError("the index type $Ti cannot hold $coolen elements; use a larger index type"))
     end
     if m == 0 || n == 0 || coolen == 0
         if coolen != 0
@@ -645,13 +644,13 @@ function sparse(I::AbstractVector{Ti}, J::AbstractVector{Ti}, V::AbstractVector{
         SparseMatrixCSC(m, n, fill(one(Ti), n+1), Vector{Ti}(), Vector{Tv}())
     else
         # Allocate storage for CSR form
-        csrrowptr = Vector{Tj}(undef, m+1)
+        csrrowptr = Vector{Ti}(undef, m+1)
         csrcolval = Vector{Ti}(undef, coolen)
         csrnzval = Vector{Tv}(undef, coolen)
 
         # Allocate storage for the CSC form's column pointers and a necessary workspace
         csccolptr = Vector{Ti}(undef, n+1)
-        klasttouch = Vector{Tj}(undef, n)
+        klasttouch = Vector{Ti}(undef, n)
 
         # Allocate empty arrays for the CSC form's row and nonzero value arrays
         # The parent method called below automagically resizes these arrays

stdlib/SparseArrays/test/sparse.jl

@@ -2662,14 +2662,14 @@ end
     J1 = Int8.(rand(1:10, 500))
     V1 = ones(500)
     # m * n < typemax(Ti) and length(I) >= typemax(Ti) - combining values
-    @test sparse(I1, J1, V1, 10, 10) !== nothing
+    @test_throws ArgumentError sparse(I1, J1, V1, 10, 10)
     # m * n >= typemax(Ti) and length(I) >= typemax(Ti)
-    @test sparse(I1, J1, V1, 12, 13) !== nothing
+    @test_throws ArgumentError sparse(I1, J1, V1, 12, 13)
     I1 = Int8.(rand(1:10, 126))
     J1 = Int8.(rand(1:10, 126))
     V1 = ones(126)
     # m * n >= typemax(Ti) and length(I) < typemax(Ti)
-    @test sparse(I1, J1, V1, 100, 100) !== nothing
+    @test size(sparse(I1, J1, V1, 100, 100)) == (100,100)
 end
 
 @testset "Typecheck too strict #31435" begin