The ApproximateCloseness function is a highly scalable, approximate (near-accurate) algorithm for finding closeness centrality and k-degree scores for all vertices in unweighted graphs.
The ApproximateCloseness function uses a fast, memory-efficient cardinality estimation measure called HyperLogLog to achieve its superior performance. Teradata recommends using this function for large-scale graphs with up to 2 billion vertices.