hugegraph面对大型数据时的性能问题

[mengquanrun]

Expected behavior 期望表现

正常运行
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
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？

Actual behavior 实际表现

内存占用居高不下
数据传输在后期非常缓慢，且最终报错：
Edges has been imported:#555144377

A fatal error has been detected by the Java Runtime Environment:

[thread 140403401385728 also had an error]

SIGBUS (0x7) at pc=0x00007fb22fdf64e2, pid=2670, tid=0x00007fb1f6bed700

JRE version: Java(TM) SE Runtime Environment (8.0_181-b13) (build 1.8.0_181-b13)

Java VM: Java HotSpot(TM) 64-Bit Server VM (25.181-b13 mixed mode linux-amd64 compressed oops)

Problematic frame:

C [libzip.so+0x124e2] newEntry+0x62

Failed to write core dump. Core dumps have been disabled. To enable core dumping, try "ulimit -c unlimited" before starting Java again

[ timer expired, abort... ]

这是什么缘故呢？

Status of loaded data 数据状态

Vertex/Edge summary 数据量

• loaded vertices amount: 65milion个，文件大小3G
• loaded edges amount: 0.7bilion，两种label的边分别74G和68G
• loaded time: 7h+且中途报错

Vertex/Edge example 数据示例

{“source_name”:"xxxxxxxx","target_name":"xxxxxxx","addr":"xxxxxxxxxxxx","value":xxx}

Schema(VertexLabel, EdgeLabel, IndexLabel) 元数据结构

{type something here...}

Specifications of environment 环境信息

• hugegraph version: 0.7.4
• operating system: ubuntu 16.04 64 cpu 64G ram
• hugegraph backend: rocksdb