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Graph Systems

Graph Systems. Howles. Graph Representations. Sometimes the data naturally fits the structure of a graph Nodes (vertices) Edges (links). Advantages of Graphs. Usually well understood – a typical topic in even introductory data structure and algorithms courses Some good APIs exist

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Graph Systems

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  1. Graph Systems Howles

  2. Graph Representations • Sometimes the data naturally fits the structure of a graph • Nodes (vertices) • Edges (links)

  3. Advantages of Graphs • Usually well understood – a typical topic in even introductory data structure and algorithms courses • Some good APIs exist • Clear understanding of the model

  4. Types • Directed Graph (DiGraph) • Undirected Graph • The link/edges carry data about relationships between the nodes (vertices)

  5. Typical Measures • Indegree – possible relevance if high (links in a network structure) • Outdegree – possible relevance (shows relationships • Either may have different relevance depending on whether the graph is directed or undirected

  6. Measures • Number of paths to a given node (vertex) • Shortest path between two nodes • Coloring algorithms • Minimal spanning tree • .. And others, depending on the application

  7. Graph Database System • Increasing applications and interest in graph-based structures (Internet, social networking interactions) have produced specialized database support • Data is modeled as nodes and edges • Nodes may have properties • An edge may have a label or role • Credit: Jennifer Widom

  8. Examples • A graph of people (nodes) may represent one or more role (parents, friends) • Neo4j (implemented in Java) , FlockDB(Twitter), Pregel (Google)

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