Minwise hashing is a standard technique in the context of search for approximating set similarities. The recent work [26, 32] demon- strated a potential use of b-bit minwise hashing [23, 24] for ef- ficient search and learning on massive, high-dimensional, binary data (which are typical for many applications in Web search and text mining). In this paper, we focus on a number of critical is- sues which must be addressed before one can apply b-bit minwise hashing to the volumes of data often used industrial applications.