{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T11:17:16Z","timestamp":1790335036610,"version":"4.1.0"},"reference-count":23,"publisher":"Association for Computing Machinery (ACM)","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2014,12]]},"abstract":"<jats:p>\n            Existing distributed graph processing frameworks,\n            <jats:italic>e.g.<\/jats:italic>\n            , Pregel, Giraph, GPS and GraphLab, mainly exploit main memory to support flexible graph operations for efficiency. Due to the complexity of graph analytics, huge memory space is required especially for those graph analytics that spawn large intermediate results. Existing frameworks may terminate abnormally or degrade performance seriously when the memory is exhausted or the external storage has to be used.\n          <\/jats:p>\n          <jats:p>In this paper, we propose MOCgraph, a scalable distributed graph processing framework to reduce the memory footprint and improve the scalability, based on message online computing. MOCgraph consumes incoming messages in a streaming manner, so as to handle larger graphs or more complex analytics with the same memory capacity. MOCgraph also exploits message online computing with external storage to provide an efficient out-of-core support. We implement MOCgraph on top of Apache Giraph, and test it against several representative graph algorithms on large graph datasets. Experiments illustrate that MOCgraph is efficient and memory-saving, especially for graph analytics with large intermediate results.<\/jats:p>","DOI":"10.14778\/2735496.2735501","type":"journal-article","created":{"date-parts":[[2015,5,12]],"date-time":"2015-05-12T15:37:52Z","timestamp":1431445072000},"page":"377-388","source":"Crossref","is-referenced-by-count":32,"title":["MOCgraph"],"prefix":"10.14778","volume":"8","author":[{"given":"Chang","family":"Zhou","sequence":"first","affiliation":[{"name":"Peking University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Gao","sequence":"additional","affiliation":[{"name":"Peking University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Binbin","family":"Sun","sequence":"additional","affiliation":[{"name":"Huawei Technologies Co., Ltd."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeffrey Xu","family":"Yu","sequence":"additional","affiliation":[{"name":"Chinese University of Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2014,12]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Apache Giraph. http:\/\/incubator.apache.org\/giraph\/. Apache Giraph. http:\/\/incubator.apache.org\/giraph\/."},{"key":"e_1_2_1_2_1","volume-title":"Parallel and dis-tributed computation: numerical methods","author":"Bertsekas D. P.","year":"1989","unstructured":"D. P. Bertsekas and J. N. Tsitsiklis . Parallel and dis-tributed computation: numerical methods . In Prentice-Hall , 1989 . D. P. Bertsekas and J. N. Tsitsiklis. Parallel and dis-tributed computation: numerical methods. In Prentice-Hall, 1989."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2213836.2213907"},{"key":"e_1_2_1_4_1","unstructured":"A. Ching. Scaling apache giraph to a trillion edges. http:\/\/tinyurl.com\/ktf6d25 2013.  A. Ching. Scaling apache giraph to a trillion edges. http:\/\/tinyurl.com\/ktf6d25 2013."},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1327452.1327492"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0377-0427(00)00409-X"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/1807167.1807184"},{"key":"e_1_2_1_8_1","first-page":"17","volume-title":"OSDI","author":"Gonzalez J. E.","year":"2012","unstructured":"J. E. Gonzalez , Y. Low , H. Gu , D. Bickson , and C. Guestrin . Powergraph: Distributed graph-parallel computation on natural graphs . In OSDI , pages 17 -- 30 , 2012 . J. E. Gonzalez, Y. Low, H. Gu, D. Bickson, and C. Guestrin. Powergraph: Distributed graph-parallel computation on natural graphs. In OSDI, pages 17--30, 2012."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.14778\/2732977.2732980"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2487581"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1137\/S1064827595287997"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772751"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2465351.2465369"},{"key":"e_1_2_1_14_1","first-page":"31","volume-title":"OSDI","volume":"8","author":"Kyrola A.","year":"2012","unstructured":"A. Kyrola , G. Blelloch , and C. Guestrin . Graphchi: Large-scale graph computation on just a pc . In OSDI , volume 8 , pages 31 -- 46 , 2012 . A. Kyrola, G. Blelloch, and C. Guestrin. Graphchi: Large-scale graph computation on just a pc. In OSDI, volume 8, pages 31--46, 2012."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1480506.1480511"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPS.2013.76"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/2517349.2522740"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/2484838.2484843"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339722"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/2213836.2213895"},{"key":"e_1_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Y. Tian A. Balmin S. A. Corsten S. Tatikonda and J. McPherson. From\" think like a vertex\" to\" think like a graph. PVLDB 7(3) 2013.   Y. Tian A. Balmin S. A. Corsten S. Tatikonda and J. McPherson. From\" think like a vertex\" to\" think like a graph. PVLDB 7(3) 2013.","DOI":"10.14778\/2732232.2732238"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/79173.79181"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.14778\/2212351.2212354"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/2735496.2735501","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T09:31:41Z","timestamp":1672219901000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/2735496.2735501"}},"subtitle":["scalable distributed graph processing using message online computing"],"short-title":[],"issued":{"date-parts":[[2014,12]]},"references-count":23,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2014,12]]}},"alternative-id":["10.14778\/2735496.2735501"],"URL":"https:\/\/doi.org\/10.14778\/2735496.2735501","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2014,12]]}}}