初识Dgraph

1.Dgraph介绍　关键字：快速，支持事务，分布式图数据库２.安装，启动Dgraph

docker pull dgraph/dgraph:v0.7.7

mkdir -p ~/dgraph
docker run -it -p 127.0.0.1:8080:8080 -p 127.0.0.1:9080:9080 -v ~/dgraph:/dgraph --name dgraph dgraph/dgraph dgraph --bindall=true

3.访问http://127.0.0.1:8080/ 4.在输入框中，分别输入如下数据，点击run

mutation {
  set {
   _:luke <name> "Luke Skywalker" .
   _:leia <name> "Princess Leia" .
   _:han <name> "Han Solo" .
   _:lucas <name> "George Lucas" .
   _:irvin <name> "Irvin Kernshner" .
   _:richard <name> "Richard Marquand" .

   _:sw1 <name> "Star Wars: Episode IV - A New Hope" .
   _:sw1 <release_date> "1977-05-25" .
   _:sw1 <revenue> "775000000" .
   _:sw1 <running_time> "121" .
   _:sw1 <starring> _:luke .
   _:sw1 <starring> _:leia .
   _:sw1 <starring> _:han .
   _:sw1 <director> _:lucas .

   _:sw2 <name> "Star Wars: Episode V - The Empire Strikes Back" .
   _:sw2 <release_date> "1980-05-21" .
   _:sw2 <revenue> "534000000" .
   _:sw2 <running_time> "124" .
   _:sw2 <starring> _:luke .
   _:sw2 <starring> _:leia .
   _:sw2 <starring> _:han .
   _:sw2 <director> _:irvin .

   _:sw3 <name> "Star Wars: Episode VI - Return of the Jedi" .
   _:sw3 <release_date> "1983-05-25" .
   _:sw3 <revenue> "572000000" .
   _:sw3 <running_time> "131" .
   _:sw3 <starring> _:luke .
   _:sw3 <starring> _:leia .
   _:sw3 <starring> _:han .
   _:sw3 <director> _:richard .

   _:st1 <name> "Star Trek: The Motion Picture" .
   _:st1 <release_date> "1979-12-07" .
   _:st1 <revenue> "139000000" .
   _:st1 <running_time> "132" .
  }
}


mutation {
  schema {
    name: string @index .
    release_date: date @index .
    revenue: float .
    running_time: int .
  }
}

5.查询数据,

{
  me(func:allofterms(name, "Star Wars")) @filter(ge(release_date, "1980")) {
    name
    release_date
    revenue
    running_time
    director {
     name
    }
    starring {
     name
    }
  }
}
点击RUN

总结：刚开始是安装的dgraph/dgraph:v1.0.12,但是启动后访问浏览器显示disconneted，为了快速看到浏览器中节点和关系的效果所以安装了dgraph/dgraph:v0.7.7。后续继续了解。

Ref：
1.https://yq.aliyun.com/articles/237205 2.https://docs.dgraph.io/get-started/#dataset