{"id":163869,"date":"2012-11-01T00:00:00","date_gmt":"2012-11-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/fennel-streaming-graph-partitioning-for-massive-scale-graphs\/"},"modified":"2018-11-09T01:23:41","modified_gmt":"2018-11-09T09:23:41","slug":"fennel-streaming-graph-partitioning-for-massive-scale-graphs","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/fennel-streaming-graph-partitioning-for-massive-scale-graphs\/","title":{"rendered":"Fennel: Streaming Graph Partitioning for Massive Scale Graphs"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Graph partitioning is a key problem to enable efficient solving of a wide range of computational tasks and querying over large-scale graph data, such as computing node centralities using iterative computations, and personalized recommendations. In this work, we introduce a unifying framework for graph partitioning which enables a well principled design of scalable, streaming graph partitioning algorithms that are amenable to distributed implementation. We show that many previously proposed methods are special instances of this framework, we derive a novel one-pass, streaming graph partitioning algorithm and show that it yields significant benefits over previous approaches, using a large set of real-world and synthetic graphs.<\/p>\n<p>Surprisingly, despite the fact that our algorithm is a one-pass streaming algorithm, we found its performance to be overall comparable to the de-facto standard offline software METIS, and it even outperforms it on numerous real-world graphs. For instance, for the Twitter graph with more than 1.4 billion of edges, our method partitions the graph in about 40 minutes achieving a balanced partition that cuts as few as 6.8% of edges, whereas it took more than 8.5 hours by METIS to produce a balanced partition that cuts 11.98% of edges. Furthermore, modularity&#8211;a popular measure for community detection [Girvan and Newman, 2002; Newman and Girvan, 2004; Newman, 2006]&#8211;is also a special instance of our framework. We establish the first rigorous approximation algorithm, achieving a guarantee of O(log(k)\/k) for partitioning into k clusters.<\/p>\n<p>Finally, we evaluate the performance gains by using our graph partitioner while solving standard PageRank computation in a graph processing platform, and observe significant gains in terms of the communication cost and runtime.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Graph partitioning is a key problem to enable efficient solving of a wide range of computational tasks and querying over large-scale graph data, such as computing node centralities using iterative computations, and personalized recommendations. In this work, we introduce a unifying framework for graph partitioning which enables a well principled design of scalable, streaming graph [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13547],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-163869","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"ACM","msr_edition":"","msr_affiliation":"","msr_published_date":"2014-11-1","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"ACM","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"205778","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/MSR-TR-2012-213.pdf","id":"205778","title":"MSR-TR-2012-213.pdf","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[{"id":205778,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/MSR-TR-2012-213.pdf"}],"msr-author-ordering":[{"type":"text","value":"Charalampos E. Tsourakakis","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Christos Gkantsidis","user_id":31424,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Christos Gkantsidis"},{"type":"user_nicename","value":"Bozidar Radunovic","user_id":31286,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Bozidar Radunovic"},{"type":"user_nicename","value":"Milan Vojnovic","user_id":32922,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Milan Vojnovic"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[171035],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/163869"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-research-item"}],"version-history":[{"count":2,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/163869\/revisions"}],"predecessor-version":[{"id":549435,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/163869\/revisions\/549435"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=163869"}],"wp:term":[{"taxonomy":"msr-content-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-content-type?post=163869"},{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=163869"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=163869"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=163869"},{"taxonomy":"msr-product-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-product-type?post=163869"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=163869"},{"taxonomy":"msr-platform","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-platform?post=163869"},{"taxonomy":"msr-download-source","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-download-source?post=163869"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=163869"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=163869"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=163869"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=163869"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=163869"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=163869"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}