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Large graph mining systems: различия между версиями
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Mining large graphs can be done with custom software developed for each task. However, there are now a number of '''large graph mining systems'''(''[[Системы обработки больших графов]]'') (and there continue to be more that are being developed) that hope to make the process easier. These systems abstract standard details away and provide a higher-level interface to manipulate algorithms running on a graph. Three relevant properties of such systems are as follows. | Mining large graphs can be done with custom software developed for each task. However, there are now a number of '''large graph mining systems'''(''[[Системы обработки больших графов]]'') (and there continue to be more that are being developed) that hope to make the process easier. These systems abstract standard details away and provide a higher-level interface to manipulate algorithms running on a graph. Three relevant properties of such systems are as follows. | ||
''Batch or online systems''. A batch system must process the entire graph for any task, whereas an online system provides access to arbitrary regions of the graph more quickly. | ''[[Batch or online systems]]''. A batch system must process the entire graph for any task, whereas an online system provides access to arbitrary regions of the graph more quickly. | ||
''Systems with adjacency or edge list''. A system that allows adjacency access enables us to get all neighbors of a given node. A system that allows edge list access only gives us a set of edges. | ''[[Systems with adjacency or edge list]]''. A system that allows adjacency access enables us to get all neighbors of a given node. A system that allows edge list access only gives us a set of edges. | ||
''Distributed or centralized systems''. If the graph mining system is distributed, then systems can only access local regions of the graph that are stored on a given machine, and the data that are needed to understand the remainder of the graph may be remote and difficult to access; a centralized system has a more holistic view of the graph. | ''[[Distributed or centralized systems]]''. If the graph mining system is distributed, then systems can only access local regions of the graph that are stored on a given machine, and the data that are needed to understand the remainder of the graph may be remote and difficult to access; a centralized system has a more holistic view of the graph. | ||
For instance, a MapReduce graph processing system is a batch, distributed system that provides either edge list or adjacency access; GraphLab is a distributed, online, adjacency system; and Ligra is an online, adjacency list, centralized system. | For instance, a MapReduce graph processing system is a batch, distributed system that provides either edge list or adjacency access; GraphLab is a distributed, online, adjacency system; and Ligra is an online, adjacency list, centralized system. | ||
