What's wrong with MapReduce? Literally Map then Reduce and thats it Reducers write to replicated storage Complex jobs pipeline multiple stages No fault tolerance between stages Map assumes its data is always available: simple Output of Reduce: 2 network copies 3 disks In Dryad this collapses inside a single process Big jobs can be more efficient with DryadWhat’s wrong with MapReduce? • Literally Map then Reduce and that’s it… – Reducers write to replicated storage • Complex jobs pipeline multiple stages – No fault tolerance between stages • Map assumes its data is always available: simple! • Output of Reduce: 2 network copies, 3 disks – In Dryad this collapses inside a single process – Big jobs can be more efficient with Dryad