4 ms·
It sounds to me like the poster above restructured the input data to exploit locality of reference better. http://en.wikipedia.org/wiki/Locality_of_reference h
by Roboprog 13y ago
It sounds to me like the poster above restructured the input data to exploit locality of reference better.
http://en.wikipedia.org/wiki/Locality_of_reference http://en.wikipedia.org/wiki/Locality_of_reference
- alecco 13y agoIt's one of the issues, yes. But I wanted to be more general on purpose.
- collyw 13y agoSo assuming the data is one one machine (as I asked), why would an index not solve this problem? And why does Map Reduce solve it?
- virtuabhi 13y agoIndexes do not solve the locality problem (see Non-clustered indexes). Even for in-memory databases, it is non-trivial to minimize cache misses in irregular data structures like B-trees. Now why MapReduce "might" be a better fit for a problem where data fits into one disk. Consider a program which is embarrassingly parallel. It just reads a tuple and writes a new tuple back to disk. The parallel IO provided by map/reduce can offer a significant benefit in this simple case as well. Also NoSQL != parallel processing.