The Hadoop Implementation. Thomas Zimmermann Philipp Berger

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1 Link Analysis goes MapReduce The Hadoop Implementation Thomas Zimmermann Philipp Berger

2 Flashback 2

3 Overview 3 1. Pre- / Postprocessing 2. Our Jobs 3. Evaluation

4 Overview 4 1. Pre- / Postprocessing 2. Our Jobs 3. Evaluation

5 Our Dataset 5 DBPedia Infobox Properties < < < < < < < < < < " "@en. Preprocessing Postprocessing 1, 2 1, 3 1, 4

6 Overview 6 1. Pre- / Postprocessing 2. Our Jobs 3. Evaluation

7 Our Jobs 7 BlockPartCreatorJob LinkExtractMapper BlockPartitionReducer BlockBuilderJob Mapper BlockConcatenateReducer PageRankComputeJob BlockComputeMapper BlockComputeCombiner BlockComputeReducer

8 Our Jobs 8 BlockPartCreatorJob LinkExtractMapper BlockPartitionReducer BlockBuilderJob Mapper BlockConcatenateReducer PageRankComputeJob BlockComputeMapper BlockComputeCombiner BlockComputeReducer

9 Our Jobs Create Block Parts (Map) 9 LinkExtractMapper Input: Key, (32 (Eiffel Tower), 122 (France) ) Output: 32 (Eiffel Tower), 122 (France)

10 Our Jobs Create Block Parts (Reduce) 10 BlockPartitionReducer 32 Eiffel Tower 33 Sushi 122 France X 123 Japan X 124 Paris X Input: 32 (Eiffel Tower), [ 122 (France), 124 (Paris) ] Output: (16, 61), (32 Eiffel Tower, 122 France, 2 #OutgoingLinks )

11 Our Jobs 11 BlockPartCreatorJob LinkExtractMapper BlockPartitionReducer BlockBuilderJob Mapper BlockConcatenateReducer PageRankComputeJob BlockComputeMapper BlockComputeCombiner BlockComputeReducer

12 Our Jobs Concatenate Block Parts 12 BlockConcatenateReducer 32 Eiffel Tower 33 Sushi 122 France X 123 Japan X 124 Paris X Input / Output: (16 Eiffel Tower,Sushi,61 France,Japan ), [(32 Eiffel Tower, 122 France, 2 #OutgoingLinks ), (33 Sushi, 123 Japan, 1 #OutgoingLinks )]

13 Our Jobs 13 BlockPartCreatorJob LinkExtractMapper BlockPartitionReducer BlockBuilderJob Mapper BlockConcatenateReducer PageRankComputeJob BlockComputeMapper BlockComputeCombiner BlockComputeReducer

14 Our Jobs Do PageRank 14 BlockComputeMapper Input: (16 Eiffel Tower,Sushi,61 France,Japan ), ((32 Eiffel Tower, 122 France, 2 #OutgoingLinks ), (33 Sushi, 123 Japan, 1 #OutgoingLinks )) Get PageRank of sources for one Block Output: 122 France, rank(eiffel Tower) * 1/2 123 Japan, rank(sushi) * 1/1 Page Distributed Cache Rank 32 Eiffel Tower Sushi Island 0.125

15 Our Jobs Do PageRank 15 BlockComputeCombiner BlockComputeMapper Input: 122 France, rank(eiffel Tower) * ½ 122 France, rank(paris)* ¼ Simply sums up incoming values Output: 122 France, rank(eiffel Tower) * ½ + rank(paris) * ¼ }

16 Our Jobs Do PageRank 16 BlockComputeCombiner BlockComputeReducer BlockComputeMapper Input: 122 France, rank(eiffel Tower) * ½ + rank(paris) * ¼ 122 France, rank(lyon) * ¼ Output: 122 France, result

17 Our Jobs Do PageRank 17 Distributed Cache Update Read the output of PageRank calculation Load the PageRank into the Distributed Cache Page Distributed Cache Rank 32 Eiffel Tower Sushi Island Start next iteration with new PageRank in Distributed Cache Until convergence is reached Until the root-mean-square-deviation < target variance

18 Overview Pre- / Postprocessing 2. Our Jobs 3. Evaluation

19 Results: Top 10 German Sites 19 Rank PageRank Site < E-4 < E-4 < E-4 < E-4 < E-4 < E-4 < E-4 < E-4 < E-4 <

20 Results: Top 10 German Sites pages link to Rheinland-Pfalz! 1242 to Piemont (Italy s largest region) Rank Site 1 < 2 < 3 < 4 < 5 < 6 < 7 < 8 < 9 < 10 <

21 Evaluation 21 Data SingleThreaded Cluster Dutch 1.9 MB 2 sec 2.53min German MB 4 min 8.25min English 2.2 GB >3 Std 14.22min Single-Threaded graph analysis library edu.uci.ics.jung.algorithms.scoring.pagerank On Cluster with 10 nodes Blocksize

22 Evaluation Runtime in minutes PageRankComputeJob 2 Cache PageRankComputeJob 1 BlockBuilderJob BlockPartCreatorJob 0 Dutch German English

23 Summary 23 BlockPartCreatorJob PageRankComputeJob BlockBuilderJob

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