This era of Big Data has been a challenge for R users. First there were issues with address spaces restrictions in R itself. Though this problem has been (mostly) solved, major issues remain in terms of performance, generalizability, convenience and possibly more than a bit of "hype." This talk will address these questions and assess the current overall status of parallel and distributed computing in R, especially the latter. We will survey existing packages, including their strengths and weaknesses, and raise questions (if not full answers) of what should be done.
