{"action":"closed","issue":{"url":"https://api.github.com/repos/hugegraph/hugegraph/issues/121","repository_url":"https://api.github.com/repos/hugegraph/hugegraph","labels_url":"https://api.github.com/repos/hugegraph/hugegraph/issues/121/labels{/name}","comments_url":"https://api.github.com/repos/hugegraph/hugegraph/issues/121/comments","events_url":"https://api.github.com/repos/hugegraph/hugegraph/issues/121/events","html_url":"https://github.com/hugegraph/hugegraph/issues/121","id":372466862,"node_id":"MDU6SXNzdWUzNzI0NjY4NjI=","number":121,"title":"hugegraph面对大型数据时的性能问题","user":{"login":"mengquanrun","id":26666284,"node_id":"MDQ6VXNlcjI2NjY2Mjg0","avatar_url":"https://avatars2.githubusercontent.com/u/26666284?v=4","gravatar_id":"","url":"https://api.github.com/users/mengquanrun","html_url":"https://github.com/mengquanrun","followers_url":"https://api.github.com/users/mengquanrun/followers","following_url":"https://api.github.com/users/mengquanrun/following{/other_user}","gists_url":"https://api.github.com/users/mengquanrun/gists{/gist_id}","starred_url":"https://api.github.com/users/mengquanrun/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mengquanrun/subscriptions","organizations_url":"https://api.github.com/users/mengquanrun/orgs","repos_url":"https://api.github.com/users/mengquanrun/repos","events_url":"https://api.github.com/users/mengquanrun/events{/privacy}","received_events_url":"https://api.github.com/users/mengquanrun/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-10-22T10:25:10Z","updated_at":"2018-10-22T11:29:00Z","closed_at":"2018-10-22T11:29:00Z","author_association":"NONE","body":"### Expected behavior 期望表现\r\n正常运行\r\n并且请问indexlabel在大型数据下是否是必选项，否则可能会引起问题\r\n请问贵团队在为大型数据建图时，会采用什么策略来进行优化？\r\n\r\n### Actual behavior 实际表现\r\n内存占用居高不下\r\n数据传输在后期非常缓慢，且最终报错：\r\nEdges has been imported:#555144377\r\n# A fatal error has been detected by the Java Runtime Environment:\r\n#\r\n#  [thread 140403401385728 also had an error]\r\nSIGBUS (0x7) at pc=0x00007fb22fdf64e2, pid=2670, tid=0x00007fb1f6bed700\r\n#\r\n# JRE version: Java(TM) SE Runtime Environment (8.0_181-b13) (build 1.8.0_181-b13)\r\n# Java VM: Java HotSpot(TM) 64-Bit Server VM (25.181-b13 mixed mode linux-amd64 compressed oops)\r\n# Problematic frame:\r\n# C  [libzip.so+0x124e2]  newEntry+0x62\r\n#\r\n# Failed to write core dump. Core dumps have been disabled. To enable core dumping, try \"ulimit -c unlimited\" before starting Java again\r\n#\r\n# [ timer expired, abort... ]\r\n这是什么缘故呢？\r\n\r\n### Status of loaded data 数据状态\r\n\r\n#### Vertex/Edge summary 数据量\r\n- loaded vertices amount: 65milion个，文件大小3G\r\n- loaded edges amount: 0.7bilion，两种label的边分别74G和68G\r\n- loaded time: 7h+且中途报错\r\n\r\n#### Vertex/Edge example 数据示例\r\n{“source_name”:\"xxxxxxxx\",\"target_name\":\"xxxxxxx\",\"addr\":\"xxxxxxxxxxxx\",\"value\":xxx}\r\n\r\n\r\n#### Schema(VertexLabel, EdgeLabel, IndexLabel) 元数据结构\r\n{type something here...}\r\n\r\n\r\n### Specifications of environment 环境信息\r\n- hugegraph version: 0.7.4\r\n- operating system: ubuntu 16.04 64 cpu 64G ram\r\n- hugegraph backend: rocksdb"}}
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