In NumPy, ndarray has .resize() but actually it does a whole array
copy into newly allocated larger segment which makes e.g. appending O(n).

For BigArray, we don't have that internal constraint NumPy has - to
keep the array itself contiguously _stored_ (compare to contiguously
_presented_ in memory). So we can have O(1) resize for big arrays.

NOTE having O(1) resize, here is how O(δ) append can be done:

    A                               # ZBigArray e.g. of shape   (N, 3)
    n = len(A)                      # lengh of A's major index  =N
    A.resize((n+δ, A.shape[1:]))    # add δ new entries ; now len(A) =N+δ
    A[-δ:] = <new-data>             # set data for last new δ entries

/cc @klaus