1 / 10

StormRider: Harnessing “Storm” for Social Networks

StormRider: Harnessing “Storm” for Social Networks. Social Network Applications. CHANGE IS A CONSTANT !!. How do you keep up with the current trends and important nodes in an ever-changing network??. How do you lookup previous versions of a network?.

ashley
Download Presentation

StormRider: Harnessing “Storm” for Social Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. StormRider: Harnessing “Storm” for Social Networks

  2. Social Network Applications CHANGE IS A CONSTANT !! How do you keep up with the current trends and important nodes in an ever-changing network?? How do you lookup previous versions of a network? How do you track changes for a certain node??

  3. 9/11 Terrorist Network How do you track what changes in his neighborhood ??

  4. Querying Evolving Networks

  5. Motivation • No current tools available for dynamic network analysis • Almost all current work focuses on a snapshot of a network at a time • No support for continuous queries on a dynamic network • No specific language to query a social network • Can we build a cloud infrastructure to tackle these two problems??

  6. Architecture Application Model-SN Interface Model-SN Storm Interface Add-Topology Query-Topology Analysis-Topology Jena-HBase Interface HBase View Interface Storm Storage Layer View Layer HBase Views HDFS Files Jena-HBase Store HDFS Files

  7. View Layer

  8. Sample Add Topology for Twitter Storage Twitter-API-Spout Jena-HBase-Bolt Node-centric View Update-Nodes-View-Bolt Count-User-Degree-Bolt Update-Landmarks-View-Bolt Rank-Users-Bolt Merge-Users-Bolt Landmark-Selection Landmark-centric View

  9. Sample Query Topologies for Twitter O/p to Client I/P SPARQL-Query-Spout • Tracking neighborhoods: Use a topology that runs a continuous query on RDF triples in Jena-HBase using a regular expression SPARQL query • SELECT ?x WHERE { ex:John gleen:onPath( “[twitter:Has_Friend]/[twitter:Has_Friend]” ?x ) } • Version Management: Use the concept of RDF reification to add version information for every triple added to the triple store. Then a SPARQL query of the form: • SELECT ?z WHERE { ?x twitter:Timestamp ?y . ?x rdf:subject <ex:John> . ?x rdf:predicate <twitter:Has_Friend> . <ex:John> <twitter:Has_Friend> ?z . FILTER( ?y <= “2012-01-25T21:00:00”^^xsd:dateTime ) } can be used to find all friends of “John” before 9pm 01-25-2012

  10. Sample Analyze Topologies for Twitter Degree-C-Bolt Twitter-User-Spout Closeness-C-Bolt Betweenness-C-Bolt

More Related