1. Single-Source
Shortest Path on
MapReduce
Shenglei Zhao

2. Social Media Recommendation

3. Motivation
 Determine the appropriate person to recommend in
Social Media (Mainly Undirected here)
 Help calculate the Betweeness Centrality of A Person
in a Social Network
 (Weighted Graph) Best Route on Google Map
3

4. Algorithms – Breath-first Search
• Determine Root Node (starting Node)
• Initial Settings for all Nodes:
EdgeList, Distance From Root(initially all
Infinite), Status(not visited, being visited,
already visited), Parent Node
• Iteration of looking for neighbors and change
settings of nodes
4

5. Iteration
• Traverse all records (node ID and node setting),
find “BEINGVISITED” nodes (for example: A)
• Find their neighbors (B, C …..), apply new settings:
for B, C, …
Parent: null  A
Status: TOBEVISITED  BEINGVISITED
Distance: null  A’s distance + 1
for A:
Status: BEINGVISITED  VISITED
• Next Traversal would apply on these neighbors
(BEINGVISITED)
5

6. 6

7. Map Reduce Structure
7
Preprocessing
Map & Reduce:
put data into
format
<nodeId,
nodeInformation>
Reduce:
Delete
old rows
of
neighbors
Map:
Create
new rows
for
neighbors
Postprocessing
Map & Reduce:
Collect all the
distances and get
the average

8. 8
Design - <k, v> evolution
1
• Preprocessing Map & Reduce:
• List<n1, n2>  <n1, [n2,n3,n4…]> <n1 ID, neighbors IDs +
Distance + Status + Parent Node ID>
2
• Recurring Working Map & Reduce (shown in next
slide)
3
• Postprocessing Map & Reduce
• <ID2, nodeInformation>  <Status, distance>  <Status,
averageDistance>

9. Working Map & Reduce Sample
9
1 2,3|0|BEINGVISITED|source
2 1,3,4,5|Inf|TOBEVISITED|null
3 1,4,2|Inf|TOBEVISITED|null
4 2,3|Inf|TOBEVISITED|null
5 2|Inf|TOBEVISITED|null
Map
1 2,3|0|BEINGVISITED|source
2 1,3,4,5|Inf|TOBEVISITED|null
3 1,4,2|Inf|TOBEVISITED|null
4 2,3|Inf|TOBEVISITED|null
5 2|Inf|TOBEVISITED|null
1 |0|BEINGVISITED|source
2 |1|BEINGVISITED|1
3 |1|BEINGVISITED|1
1 2,3|0|VISITED|source
2 1,3,4,5|1|BEINGVISITED|1
3 1,4,2|1|BEINGVISITED|1
4 2,3|Inf|TOBEVISITED|null
5 2|Inf|TOBEVISITED|null
Parent Node this turn
New record
created
without
edge list
Merged records
Will be picked as parent Node
next turn

10. Code Snippet
10

11. 11
Mapper for Core part of Algorithm

12. 12
Reducer for Core part of Algorithm

13. 13
Create an enum variable to represent counter
The counter increments by 1 when a node turns “BEINGVISITED”
Show the counter value on screen to show # of changes

14. 14
Iteration for Job

15. Result
• A list of rows containing complete information
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16. Result – distance-only
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17. Result – average distance
17
• The average distance from all nodes to source
node (0) is about 2.829
• For random person, Person 0 has to go across
about 2.8 immediate persons to find him.

18. Future Work
• Calculate all the average distance to each nodes
• Determine betweeness centrality based on
results of all nodes
• Visualization of Network (lower average distance
nodes have bigger radius)
18