GraphX is the Apache Spark library for handling graph data. I was able to find a list of 'graph-parallel' algorithms on these slides (see slide 23). However, I am curious what characteristics of these algorithms make them parallelizable.
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Two words: associative and commutative
In other words, the operations that the algorithm does need to be independent of how you order or group your data...this minimizes the need for cross-talk in the algorithm and leads to more efficiency.
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Can you elaborate on these terms? – sheldonkreger Jul 29 '15 at 01:06
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1@sheldonkreger the operations that the algorithm does need to be independent of how you order or group your data...this minimizes the need for cross-talk in the algorithm and leads to more efficiency. – Jul 29 '15 at 02:05