Even algorithms that are considered relatively scalable (e.g., the Lanczos algorithm (Cullum and Willoughby, 2002) for computing eigenvalue decomposition of large sparse matrices) fall apart in this scenario, since the data cannot be stored in the memory of a single machine.
approximate methods are needed.