Graph

    For example, graph exploration could help you uncover website vulnerabilities that hackers are targeting so you can harden your website. Or, you might provide graph-based personalized recommendations to your e-commerce customers.

    The graph analytics features provide a simple, yet powerful graph exploration API, and an interactive graph visualization tool for Kibana. Both work out of the box with existing Elasticsearch indices—​you don’t need to store any additional data to use these features.

    The terms you want to include in the graph are called vertices. The relationship between any two vertices is a connection. The connection summarizes the documents that contain both vertices’ terms.

    The graph vertices are simply the terms that you’ve already indexed. The connections are derived on the fly using Elasticsearch aggregations. To identify the most meaningful connections, the graph API leverages Elasticsearch relevance scoring. The same data structures and relevance ranking tools built into Elasticsearch to support text searches enable the graph API to separate useful signals from the noise that is typical of most connected data.

    This foundation lets you easily answer questions like:

    • If users bought this type of gardening glove, what other products might they be interested in?
    • Which people on Stack Overflow have expertise in both Hadoop-related technologies and Python-related tech?