hugegraph是什么

hugegraph是百度开源的一个图数据库，支持gremlin语言。支持多种后端存储引擎；对查询有所优化，图检索毫秒级响应；具备批量导入，图备份等周边工具，使用简单。本次我是通过hugegraph-tools联网一键部署；无法连接外网的情况下可以手工下载hugegraph-server和hugegraph-studio进行安装，配置方法跟一键部署一致。话不多说，直接开干。
官方文档链接

下载HugeGraph-Tools安装包

在服务器上创建一个目录，然后下载安装包并解压,如果你安装的版本跟我的不一样可以到官方下载页面找到对应版本号，右键然后复制链接地址

mkdir -p /opt/graph
cd /opt/graph
wget https://github.com/hugegraph/hugegraph-tools/releases/download/v1.4.0/hugegraph-tools-1.4.0.tar.gz
tar -zxvf  hugegraph-tools-1.4.0.tar.gz

使用一键部署命令下载hugegraph-server和hugegraph-studio

执行命令进行一键部署，-v指定hugegraph-server的版本号，-p指定hugegraph-server和hugegraph-studio下载到哪个路径

cd hugegraph-tools-1.4.0
bin/hugegraph deploy -v 0.10 -p /opt/graph

执行完上面这条命令会自动下载、解压hugegraph-0.10.4.tar.gz和hugegraph-studio-0.10.0.tar.gz

image.png

修改配置文件

进入hugegraph-0.10.4进行配置

cd hugegraph-0.10.4/conf
vim hugegraph.properties

backend=hbase
serializer=hbase
hbase.hosts=cscdh1,cscdh2,cscdh4
hbase.port=2181

修改之后保存退出
vim rest-server.properties
restserver.url是我们程序远程访问的地址，此处必须指定IP否则访问不到

restserver.url=http://101.141.177.70:8099

到此hugegraph-server配置完成，接下来配置hugegraph-studio

cd hugegraph-studio-0.10.0/conf
vim hugegraph-studio.properties

studio.server.port=8097
studio.server.host=101.141.177.70

graph.server.host=101.141.177.70
graph.server.port=8099

至此配置完成

初始化存储引擎

由于我们的后端是hbase库，因此需要进行初始化，本质上就是在hbase 中创建一系列表。

cd  /opt/graph/hugegraph-0.10.4
bin/init-store.sh

使用hugegraph-tools一键启动

cd /opt/graph/hugegraph-tools-1.4.0
bin/hugegraph start-all -v 0.10 -p /opt/graph

然后可以在浏览器通过上面配置的地址访问图库
http://101.141.177.70:8097/

通过页面创建我们的第一张图

graph.schema().propertyKey("name").asText().ifNotExist().create()
graph.schema().propertyKey("age").asInt().ifNotExist().create()
graph.schema().propertyKey("city").asText().ifNotExist().create()
graph.schema().propertyKey("lang").asText().ifNotExist().create()
graph.schema().propertyKey("date").asText().ifNotExist().create()
graph.schema().propertyKey("price").asInt().ifNotExist().create()

person = graph.schema().vertexLabel("person").properties("name", "age", "city").primaryKeys("name").ifNotExist().create()
software = graph.schema().vertexLabel("software").properties("name", "lang", "price").primaryKeys("name").ifNotExist().create()

knows = graph.schema().edgeLabel("knows").sourceLabel("person").targetLabel("person").properties("date").ifNotExist().create()
created = graph.schema().edgeLabel("created").sourceLabel("person").targetLabel("software").properties("date", "city").ifNotExist().create()

marko = graph.addVertex(T.label, "person", "name", "marko", "age", 29, "city", "Beijing")
vadas = graph.addVertex(T.label, "person", "name", "vadas", "age", 27, "city", "Hongkong")
lop = graph.addVertex(T.label, "software", "name", "lop", "lang", "java", "price", 328)
josh = graph.addVertex(T.label, "person", "name", "josh", "age", 32, "city", "Beijing")
ripple = graph.addVertex(T.label, "software", "name", "ripple", "lang", "java", "price", 199)
peter = graph.addVertex(T.label, "person","name", "peter", "age", 29, "city", "Shanghai")

marko.addEdge("knows", vadas, "date", "20160110")
marko.addEdge("knows", josh, "date", "20130220")
marko.addEdge("created", lop, "date", "20171210", "city", "Shanghai")
josh.addEdge("created", ripple, "date", "20151010", "city", "Beijing")
josh.addEdge("created", lop, "date", "20171210", "city", "Beijing")
peter.addEdge("created", lop, "date", "20171210", "city", "Beijing")

查询我们创建的图