services:
NebulaGraphDD:
image: ${DESKTOP_PLUGIN_IMAGE}
metad0:
profiles: ["core"]
labels:
- "com.vesoft.scope=core"
image: vesoft/nebula-metad:v3.3.0
environment:
Extract Code
generated by OpenAI ChatGPT, data fetched from https://en.wikipedia.org/wiki/2022_FIFA_World_Cup_squads
import requests
from bs4 import BeautifulSoup
import csv
# Define the URL of the Wikipedia page
- install things needed
brew install node_exporter
deploy dashboard in docker-compose ...
- configuration on dashboard:
Add gh action:
name: release
on:
release:
types:
- published
docker-compose.yaml
Create a mkdir nebulagraph_docker
cd nebulagraph_docker
vim docker-compose.yaml
It could be like this:
For k8s deployment, see https://gist.github.com/wey-gu/699b9a2ef5dff5f0fb5f288d692ddfd5
Create extral interfaces for host
If not leveraging multiple interfaces, we have to use TLS instead to leverage SNI routing
ip address add 10.1.1.157/24 dev eth0
ip address add 10.1.1.156/24 dev eth0
ip address add 10.1.1.155/24 dev eth0
前言
像一般的 Web 应用之于数据库一样,一个典型的基于 NebulaGraph 的传统线上应用可以又三部分组成:
- 前端,作为人机交互界面,调用后端 API
- 后端,处理基于 Web 的 API,生成 NebulaGraph 图数据库的查询语句,请求 NebulaGraph,处理结果返回 API 调用方
- 图数据库:NebulaGraph
今天,我们给大家简单演示如何开发一个基于 NebulaGraph 的智能机器人应用。本节课旨在快速将我们在 NebulaGraph 入门课程所学与实践开发落地场景连接起来,不会拘泥所有的开发细节, 然而所有的细节在这个示例项目作者的博客中(地址 https://www.siwei.io/siwi/ )都有更详细介绍,如果同学们感兴趣,欢迎访问博客和它的 Github 代码仓库了解。
- Fraud Detection https://siwei.io/fraud-detection-with-nebulagraph/
- 思路是把我这个文章的方式藉由 GraphXR 的能力呈现出来,未来甚至可以用 iframe 来 embed 结果,像这个文章这种 https://distill.pub/2021/gnn-intro/
- Graph Pattern based 方法,章节 1.2.1
- 数据集 https://github.com/wey-gu/fraud-detection-datagen
- 介绍风控专家提供的图模式,展示可视化
MATCH (n) WHERE id(n) == "200000010265"
Let's setup Nebula Graph with a graph, Spark, Hadoop, run Nebula Algoritm Node2vec to read Graph from Nebula and Sink result data into a file.
Reference:
- https://stackoverflow.com/questions/13305290/is-there-a-pure-python-implementation-of-murmurhash
- https://github.com/vesoft-inc/nebula/blob/master/src/common/base/MurmurHash2.h
- https://github.com/jievince/rdf-converter/blob/master/murmur2.go
def bytes_to_long(bytes):
assert len(bytes) == 8
return sum((b << (k * 8) for k, b in enumerate(bytes)))