The fast-extract algorithm is a well-known algebraic method for factoring and decomposing Boolean expressions. Since it uses pairwise comparisons between cubes to find factors, the runtime is degraded for networks whose primary outputs are expressed in terms of primary inputs and have Boolean functions with thousands of cubes. This paper describes a new implementation of the fast-extract algorithm, fxch, having complexity linear in the number of cubes. The reduction in complexity is achieved by hashing sub-cubes and using the hash table to find good factors to extract. Experimental results on industrial benchmarks show superior runtime and scalability of the proposed algorithm, compared to the available solutions.