# Sparse vectors with Int128 indices

**URL:** <https://discourse.julialang.org/t/sparse-vectors-with-int128-indices/41833>\
**Category:** New to Julia\
**Created:** [June 22, 2020, 1:56am UTC](https://discourse.julialang.org/t/sparse-vectors-with-int128-indices/41833 "2020-06-22T01:56:19Z")\
**Posts on this page:** 1\
**Showing post:** 11

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**Author:** ![Bernard\_GODARD](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/bernard_godard/32/4155_2.png) [@Bernard\_GODARD](https://discourse.julialang.org/u/Bernard_GODARD)\
**Post date:** [March 11, 2021, 9:12pm UTC](https://discourse.julialang.org/t/sparse-vectors-with-int128-indices/41833/11 "2021-03-11T21:12:36Z")

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This seems related to the issue discussed here:

> [@UniformScaling with SparseMatrixCSC{T,Int32} loses integer type](https://discourse.julialang.org/t/uniformscaling-with-sparsematrixcsc-t-int32-loses-integer-type/19371/7):
>
> Yes, - as well. And I + A also. All three are together in the code.

Why allow custom integers type to store the indices of sparse arrays but have length fixed to Int64?  
Could length(AbstractArray) return T\<:Integer with type T dependent of concrete type of array? Is there really much code which work with that assumption? Generally indices and length types are derived (eachindex, length…)

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