{"title":"从单节点图数据库安装中构建分布式图处理引擎","authors":"Vasilis Spyropoulos, Y. Kotidis","doi":"10.1145/3186549.3186555","DOIUrl":null,"url":null,"abstract":"In this work we present Digree, a system prototype that enables distributed execution of graph pattern matching queries in a cloud of interconnected graph databases. We explain how a graph query can be decomposed into independent sub-patterns that are processed in parallel by the distributed independent graph database systems and how the results are finally synthesized at a master node. We experimentally compare a prototype of our system against a popular big data engine and show that Digree provides significantly faster query execution.","PeriodicalId":21740,"journal":{"name":"SIGMOD Rec.","volume":"16 1","pages":"22-27"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Digree: Building A Distributed Graph Processing Engine out of Single-node Graph Database Installations\",\"authors\":\"Vasilis Spyropoulos, Y. Kotidis\",\"doi\":\"10.1145/3186549.3186555\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work we present Digree, a system prototype that enables distributed execution of graph pattern matching queries in a cloud of interconnected graph databases. We explain how a graph query can be decomposed into independent sub-patterns that are processed in parallel by the distributed independent graph database systems and how the results are finally synthesized at a master node. We experimentally compare a prototype of our system against a popular big data engine and show that Digree provides significantly faster query execution.\",\"PeriodicalId\":21740,\"journal\":{\"name\":\"SIGMOD Rec.\",\"volume\":\"16 1\",\"pages\":\"22-27\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIGMOD Rec.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3186549.3186555\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIGMOD Rec.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3186549.3186555","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Digree: Building A Distributed Graph Processing Engine out of Single-node Graph Database Installations
In this work we present Digree, a system prototype that enables distributed execution of graph pattern matching queries in a cloud of interconnected graph databases. We explain how a graph query can be decomposed into independent sub-patterns that are processed in parallel by the distributed independent graph database systems and how the results are finally synthesized at a master node. We experimentally compare a prototype of our system against a popular big data engine and show that Digree provides significantly faster query execution.