Graph Processing & Bulk Synchronous Parallel Model

iMapReduce
• Reduce output is directly sent to mappers, instead of wriFng to
distributed file system.
• Loop invariant is loaded onto the maps only once.
cted Components, we
propagate their comodes
do the propagaessary
propagation of
Map 1
nce those small comith
larger ones in the
omponents algorithm
programming model
id c v to its neighboramong
node w’s cury
w, and update c w
Graph
Partition (1)
Reduce 1
K V
Graph
Partition (2)
Map 2
Reduce 2
Shuffle
...
3. The framework needs to support prioritized execution.
Lecture 14 : 590.02 Spring 13
8
That is, an e cient selection of the high priority data
K V
Graph
Partition (n)
Map n
Reduce n
Figure 2: Iterative processing structure.
K V