NebulaGraph 多机集群部署及生态组件的使用

文章 NebulaGraph
,
1

NebulaGraph 多机集群部署

本文介绍通过 docker-compose部署集群的示例。

使用 Docker Compose 部署 NebulaGraph

使用 Docker Compose 可以基于准备好的配置文件快速部署 NebulaGraph 服务，仅建议在测试 NebulaGraph 功能时使用该方式。

前提条件

主机上安装如下应用程序。

应用程序 推荐版本 官方安装参考
Docker 最新版本 Install Docker Engine
Docker Compose 最新版本 Install Docker Compose
Git 最新版本 Download Git

集群规划

主机名 IP Nebula服务
spark1 192.168.2.10 graphd0, metad-0, storaged-0
spark2 192.168.2.140 graphd1, metad-1, storaged-1
spark3 192.168.2.74 graphd2, metad-2, storaged-2

部署 NebulaGraph

  1. 通过 Git 克隆nebula-docker-compose仓库的3.8.0分支到主机。

    $ git clone -b release-3.8 https://github.com/vesoft-inc/nebula-docker-compose.git

  2. 切换至目录nebula-docker-compose。

    $ cd nebula-docker-compose/

  3. 配置docker-compose文件

    version: '3.4'
services:
  metad:
    image: docker.io/vesoft/nebula-metad:v3.8.0
    environment:
      USER: root
      TZ: "${TZ}"
    command:
      - --meta_server_addrs=192.168.2.10:9559,192.168.2.140:9559,192.168.2.74:9559
      - --local_ip=${HOST_IP}
      - --ws_ip=${HOST_IP}
      - --port=9559
      - --ws_http_port=19559
      - --data_path=/data/meta
      - --log_dir=/logs
      - --v=0
      - --minloglevel=0
    healthcheck:
      test: ["CMD", "curl", "-sf", "http://${HOST_IP}:19559/status"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 20s
    ports:
      - "9559:9559"
      - "19559:19559"
      - "19560:19560"
    volumes:
      - ./data/meta:/data/meta
      - ./logs/meta:/logs
    restart: on-failure
    network_mode: host
    cap_add:
      - SYS_PTRACE

  storaged:
    image: docker.io/vesoft/nebula-storaged:v3.8.0
    environment:
      USER: root
      TZ: "${TZ}"
    command:
      - --meta_server_addrs=192.168.2.10:9559,192.168.2.140:9559,192.168.2.74:9559
      - --local_ip=${HOST_IP}
      - --ws_ip=${HOST_IP}
      - --port=9779
      - --ws_http_port=19779
      - --data_path=/data/storage
      - --log_dir=/logs
      - --v=0
      - --minloglevel=0
    depends_on:
      - metad
    healthcheck:
      test: ["CMD", "curl", "-sf", "http://${HOST_IP}:19779/status"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 20s
    ports:
      - "9779:9779"
      - "19779:19779"
      - "19780:19780"
    volumes:
      - ./data/storage:/data/storage
      - ./logs/storage:/logs
    network_mode: host
    restart: on-failure
    cap_add:
      - SYS_PTRACE

  graphd:
    image: docker.io/vesoft/nebula-graphd:v3.8.0
    environment:
      USER: root
      TZ: "${TZ}"
    command:
      - --meta_server_addrs=192.168.2.10:9559,192.168.2.140:9559,192.168.2.74:9559
      - --port=9669
      - --local_ip=${HOST_IP}
      - --ws_ip=${HOST_IP}
      - --ws_http_port=19669
      - --log_dir=/logs
      - --v=0
      - --minloglevel=0
    depends_on:
      - storaged
    healthcheck:
      test: ["CMD", "curl", "-sf", "http://${HOST_IP}:19669/status"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 20s
    ports:
      - "9669:9669"
      - "19669:19669"
      - "19670:19670"
    volumes:
      - ./logs/graph:/logs
    network_mode: host
    restart: on-failure
    cap_add:
      - SYS_PTRACE
      
  console:
    image: docker.io/vesoft/nebula-console:v3.8
    entrypoint: ""
    command: 
      - sh
      - -c
      - |
        for i in `seq 1 60`;do
          var=`nebula-console -addr graphd -port 9669 -u root -p nebula -e 'ADD HOSTS "192.168.2.10":9779,"192.168.2.140":9779,"192.168.2.74":9779'`;
          if [[ $$? == 0 ]];then
            break;
          fi;
          sleep 1;
          echo "retry to add hosts.";
        done && tail -f /dev/null;

    depends_on:
      - graphd
    network_mode: host

    对应的在每个spark节点都拷贝一份docker-compose.yaml

  4. 每个spark节点执行如下命令启动 NebulaGraph 服务。

    [nebula-docker-compose]$ HOST_IP=$(hostname -I | awk '{print $1}') docker-compose up -d

连接 NebulaGraph

连接 NebulaGraph 有两种方式：

  • 在容器外通过 Nebula Console 连接。因为容器的配置文件中将 Graph 服务的外部映射端口也固定为 9669，因此可以直接通过默认端口连接。

  • 登录安装了 NebulaGraph Console 的容器，然后再连接 Graph 服务。本小节介绍这种方式。

  1. 使用docker-compose ps命令查看 NebulaGraph Console 容器名称。

    [root@stmt-k8s-node02 nebula-docker-compose]# HOST_IP=$(hostname -I | awk '{print $1}') docker-compose ps
NAME                               COMMAND                  SERVICE             STATUS              PORTS
nebula-docker-compose-console-1    "sh -c 'for i in `se…"   console             running             
nebula-docker-compose-graphd-1     "/usr/local/nebula/b…"   graphd              running (healthy)   
nebula-docker-compose-metad-1      "/usr/local/nebula/b…"   metad               running (healthy)   
nebula-docker-compose-storaged-1   "/usr/local/nebula/b…"   storaged            running (healthy)   
[root@stmt-k8s-node02 nebula-docker-compose]#

    Note

    nebula-docker-compose_console_1和nebula-docker-compose_graphd1_1为容器的名称。

  2. 进入 NebulaGraph Console 容器中。

    $ docker exec -it nebula-docker-compose_console_1 /bin/sh
/ #

  3. 通过 NebulaGraph Console 连接 NebulaGraph 。

    / # ./usr/local/bin/nebula-console -u <user_name> -p <password> --address=graphd --port=9669

    Note

    默认情况下，身份认证功能是关闭的，只能使用已存在的用户名（默认为root）和任意密码登录。

  4. 查看集群状态。

    nebula> SHOW HOSTS;
+-----------------+------+----------+--------------+---------------------+------------------------+---------+
| Host            | Port | Status   | Leader count | Leader distribution | Partition distribution | Version |
+-----------------+------+----------+--------------+---------------------+------------------------+---------+
| "192.168.2.10"  | 9779 | "ONLINE" | 2            | "sf01:1, sf10:1"    | "sf01:1, sf10:1"       | "3.8.0" |
| "192.168.2.74"  | 9779 | "ONLINE" | 2            | "sf01:1, sf10:1"    | "sf01:1, sf10:1"       | "3.8.0" |
| "192.168.2.140" | 9779 | "ONLINE" | 2            | "sf01:1, sf10:1"    | "sf01:1, sf10:1"       | "3.8.0" |
+-----------------+------+----------+--------------+---------------------+------------------------+---------+

执行两次exit可以退出容器。

部署 Studio

  1. 配置docker-compose文件

    version: '3.4'
services:
  web:
    image: vesoft/nebula-graph-studio:v3.10
    environment:
      USER: root
    ports:
      - 57008:7001

    57008:9669表示内部的 7001 映射到外部的端口也是 57008。

  2. 构建并启动 Studio 服务。其中，-d 表示在后台运行服务容器。

    docker-compose up -d

    当屏幕返回以下信息时，表示 Docker 版 Studio 已经成功启动。

Importer Docker 方式运行

需要拉取 NebulaGraph Importer 的镜像，并将本地配置文件和 CSV 数据文件挂载到容器中。命令如下：

$ docker pull vesoft/nebula-importer:<version>
$ docker run --rm -ti \
      --network=host \
      -v <config_file>:<config_file> \
      -v <data_dir>:<data_dir> \
      vesoft/nebula-importer:<version> \
      --config <config_file>
  • <config_file>：填写 YAML 配置文件的绝对路径。
  • <data_dir>：填写 CSV 数据文件的绝对路径。如果文件不在本地，请忽略该参数。
  • <version>：填写 Importer 的版本号。

例如：

docker run --rm -ti \
      --network=host \
	  -v /data/logs:/home/logs \  
      -v /data/tanwei/nebula-importer.yaml-sf01:/home/nebula-importer-sf01.yaml \
      -v /data/tanwei/0.1/dynamic/person_0_0.csv:/home/0.1/dynamic/person_0_0.csv \
      -v /data/tanwei/0.1/dynamic/comment_0_0.csv:/home/0.1/dynamic/comment_0_0.csv \
      -v /data/tanwei/0.1/dynamic/post_0_0.csv:/home/0.1/dynamic/post_0_0.csv \
      -v /data/tanwei/0.1/dynamic/forum_0_0.csv:/home/0.1/dynamic/forum_0_0.csv \
      -v /data/tanwei/0.1/static/organisation_0_0.csv:/home/0.1/static/organisation_0_0.csv \
      -v /data/tanwei/0.1/static/place_0_0.csv:/home/0.1/static/place_0_0.csv \
      -v /data/tanwei/0.1/static/tag_0_0.csv:/home/0.1/static/tag_0_0.csv \
      -v /data/tanwei/0.1/static/tagclass_0_0.csv:/home/0.1/static/tagclass_0_0.csv \
      -v /data/tanwei/0.1/dynamic/person_knows_person_0_0.csv:/home/0.1/dynamic/person_knows_person_0_0.csv \
      -v /data/tanwei/0.1/dynamic/person_likes_comment_0_0.csv:/home/0.1/dynamic/person_likes_comment_0_0.csv \
      -v /data/tanwei/0.1/dynamic/person_likes_post_0_0.csv:/home/0.1/dynamic/person_likes_post_0_0.csv \
      -v /data/tanwei/0.1/dynamic/post_hasCreator_person_0_0.csv:/home/0.1/dynamic/post_hasCreator_person_0_0.csv \
      -v /data/tanwei/0.1/dynamic/comment_hasCreator_person_0_0.csv:/home/0.1/dynamic/comment_hasCreator_person_0_0.csv \
      -v /data/tanwei/0.1/dynamic/comment_hasTag_tag_0_0.csv:/home/0.1/dynamic/comment_hasTag_tag_0_0.csv \
      -v /data/tanwei/0.1/dynamic/comment_isLocatedIn_place_0_0.csv:/home/0.1/dynamic/comment_isLocatedIn_place_0_0.csv \
      -v /data/tanwei/0.1/dynamic/comment_replyOf_comment_0_0.csv:/home/0.1/dynamic/comment_replyOf_comment_0_0.csv \
      -v /data/tanwei/0.1/dynamic/comment_replyOf_post_0_0.csv:/home/0.1/dynamic/comment_replyOf_post_0_0.csv \
      -v /data/tanwei/0.1/dynamic/forum_containerOf_post_0_0.csv:/home/0.1/dynamic/forum_containerOf_post_0_0.csv \
      -v /data/tanwei/0.1/dynamic/forum_hasMember_person_0_0.csv:/home/0.1/dynamic/forum_hasMember_person_0_0.csv \
      -v /data/tanwei/0.1/dynamic/forum_hasModerator_person_0_0.csv:/home/0.1/dynamic/forum_hasModerator_person_0_0.csv \
      -v /data/tanwei/0.1/dynamic/forum_hasTag_tag_0_0.csv:/home/0.1/dynamic/forum_hasTag_tag_0_0.csv \
      -v /data/tanwei/0.1/dynamic/person_hasInterest_tag_0_0.csv:/home/0.1/dynamic/person_hasInterest_tag_0_0.csv \
      -v /data/tanwei/0.1/dynamic/person_isLocatedIn_place_0_0.csv:/home/0.1/dynamic/person_isLocatedIn_place_0_0.csv \
      -v /data/tanwei/0.1/dynamic/person_studyAt_organisation_0_0.csv:/home/0.1/dynamic/person_studyAt_organisation_0_0.csv \
      -v /data/tanwei/0.1/dynamic/person_workAt_organisation_0_0.csv:/home/0.1/dynamic/person_workAt_organisation_0_0.csv \
      -v /data/tanwei/0.1/dynamic/post_hasTag_tag_0_0.csv:/home/0.1/dynamic/post_hasTag_tag_0_0.csv \
      -v /data/tanwei/0.1/dynamic/post_isLocatedIn_place_0_0.csv:/home/0.1/dynamic/post_isLocatedIn_place_0_0.csv \
      -v /data/tanwei/0.1/static/organisation_isLocatedIn_place_0_0.csv:/home/0.1/static/organisation_isLocatedIn_place_0_0.csv \
      -v /data/tanwei/0.1/static/place_isPartOf_place_0_0.csv:/home/0.1/static/place_isPartOf_place_0_0.csv \
      -v /data/tanwei/0.1/static/tag_hasType_tagclass_0_0.csv:/home/0.1/static/tag_hasType_tagclass_0_0.csv \
      -v /data/tanwei/0.1/static/tagclass_isSubclassOf_tagclass_0_0.csv:/home/0.1/static/tagclass_isSubclassOf_tagclass_0_0.csv \
      vesoft/nebula-importer:v4.1 \
      --config /home/nebula-importer-sf01.yaml

配置nebula-importer.yaml文件

client:
  version: v3
  address: "192.168.2.10:9669,192.168.2.140:9669,192.168.2.74:9669"
  user: root
  password: nebula
  ssl:
    enable: false
    certPath: "/home/xxx/cert/importer.crt"
    keyPath: "/home/xxx/cert/importer.key"
    caPath: "/home/xxx/cert/root.crt"
    insecureSkipVerify: false
  concurrencyPerAddress: 10
  reconnectInitialInterval: 1s
  retry: 3
  retryInitialInterval: 1s
manager:
  spaceName: sf01
  batch: 1024
  readerConcurrency: 50
  importerConcurrency: 50
  statsInterval: 10s
  hooks:
    before:
      - statements:
        - |
            DROP SPACE IF EXISTS sf01;
            CREATE SPACE IF NOT EXISTS sf01(partition_num=3, replica_factor=1, vid_type=FIXED_STRING(64));
            USE sf01;
            CREATE TAG Person(firstName string,lastName string,gender string,birthday string,creationDate string,locationIP string,browserUsed string,language string,email string);
            CREATE TAG `Comment`(creationDate string,locationIP string,browserUsed string,content string,length string);
            CREATE TAG Post(imageFile string,creationDate string,locationIP string,browserUsed string,language string,content string,length string);
            CREATE TAG Forum(title string,creationDate string);
            CREATE TAG Organisation(type string,name string,url string);
            CREATE TAG Place(name string,url string,type string);
            CREATE TAG `Tag`(name string,url string);
            CREATE TAG TagClass(name string,url string);
            CREATE EDGE PersonKnowsPerson(creationDate string);
            CREATE EDGE PersonLikesComment(creationDate string);
            CREATE EDGE PersonLikesPost(creationDate string);
            CREATE EDGE PostHasCreatorPerson();
            CREATE EDGE CommentHasCreatorPerson();
            CREATE EDGE CommentHasTagTag();
            CREATE EDGE CommentIsLocatedInPlace();
            CREATE EDGE CommentReplyOfComment();
            CREATE EDGE CommentReplyOfPost();
            CREATE EDGE ForumContainerOfPost();
            CREATE EDGE ForumHasMemberPerson(joinDate string);
            CREATE EDGE ForumHasModeratorPerson();
            CREATE EDGE ForumHasTagTag();
            CREATE EDGE PersonHasInterestTag();
            CREATE EDGE PersonIsLocatedInPlace();
            CREATE EDGE PersonStudyAtOrganisation(classYear string);
            CREATE EDGE PersonWorkAtOrganisation(workFrom string);
            CREATE EDGE PostHasTagTag();
            CREATE EDGE PostIsLocatedInPlace();
            CREATE EDGE OrganisationIsLocatedInPlace();
            CREATE EDGE PlaceIsPartOfPlace();
            CREATE EDGE TagHasTypeTagClass();
            CREATE EDGE TagClassIsSubclassOfTagClass();
        wait: 10s
    after:
      - statements:
          - |
            SHOW SPACES;
log:
  level: INFO
  console: true
  files:
    - /home/logs/nebula-importer.log   
sources:
  - path: /home/0.1/dynamic/person_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    tags:
    - name: Person
      mode: INSERT
      id:
        type: "STRING"
        index: 0
      props:
        - name: "firstName"
          type: "STRING"
          index: 1
        - name: "lastName"
          type: "STRING"
          index: 2
        - name: "gender"
          type: "STRING"
          index: 3
        - name: "birthday"
          type: "STRING"
          index: 4
        - name: "creationDate"
          type: "STRING"
          index: 5
        - name: "locationIP"
          type: "STRING"
          index: 6
        - name: "browserUsed"
          type: "STRING"
          index: 7
        - name: "language"
          type: "STRING"
          index: 8
        - name: "email"
          type: "STRING"
          index: 9
  - path: /home/0.1/dynamic/comment_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    tags:
    - name: Comment
      mode: INSERT
      id:
        type: "STRING"
        index: 0
      props:
        - name: "creationDate"
          type: "STRING"
          index: 1
        - name: "locationIP"
          type: "STRING"
          index: 2
        - name: "browserUsed"
          type: "STRING"
          index: 3
        - name: "content"
          type: "STRING"
          index: 4
        - name: "length"
          type: "STRING"
          index: 5
  - path: /home/0.1/dynamic/post_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    tags:
    - name: Post
      mode: INSERT
      id:
        type: "STRING"
        index: 0
      props:
        - name: "imageFile"
          type: "STRING"
          index: 1
        - name: "creationDate"
          type: "STRING"
          index: 2
        - name: "locationIP"
          type: "STRING"
          index: 3
        - name: "browserUsed"
          type: "STRING"
          index: 4
        - name: "language"
          type: "STRING"
          index: 5
        - name: "content"
          type: "STRING"
          index: 6
        - name: "length"
          type: "STRING"
          index: 7
  - path: /home/0.1/dynamic/forum_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    tags:
    - name: Forum
      mode: INSERT
      id:
        type: "STRING"
        index: 0
      props:
        - name: "title"
          type: "STRING"
          index: 1
        - name: "creationDate"
          type: "STRING"
          index: 2
  - path: /home/0.1/static/organisation_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    tags:
    - name: Organisation
      mode: INSERT
      id:
        type: "STRING"
        index: 0
      props:
        - name: "type"
          type: "STRING"
          index: 1
        - name: "name"
          type: "STRING"
          index: 2
        - name: "url"
          type: "STRING"
          index: 3
  - path: /home/0.1/static/place_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    tags:
    - name: Place
      mode: INSERT
      id:
        type: "STRING"
        index: 0
      props:
        - name: "name"
          type: "STRING"
          index: 1
        - name: "url"
          type: "STRING"
          index: 2
        - name: "type"
          type: "STRING"
          index: 3
  - path: /home/0.1/static/tag_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    tags:
    - name: Tag
      mode: INSERT
      id:
        type: "STRING"
        index: 0
      props:
        - name: "name"
          type: "STRING"
          index: 1
        - name: "url"
          type: "STRING"
          index: 2
  - path: /home/0.1/static/tagclass_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    tags:
    - name: TagClass
      mode: INSERT
      id:
        type: "STRING"
        index: 0
      props:
        - name: "name"
          type: "STRING"
          index: 1
        - name: "url"
          type: "STRING"
          index: 2
  - path: /home/0.1/dynamic/person_knows_person_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: PersonKnowsPerson
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
      props:
        - name: "creationDate"
          type: "STRING"
          index: 2
  - path: /home/0.1/dynamic/person_likes_comment_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: PersonLikesComment
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
      props:
        - name: "creationDate"
          type: "STRING"
          index: 2
  - path: /home/0.1/dynamic/person_likes_post_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: PersonLikesPost
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
      props:
        - name: "creationDate"
          type: "STRING"
          index: 2
  - path: /home/0.1/dynamic/post_hasCreator_person_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: PostHasCreatorPerson
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/dynamic/comment_hasCreator_person_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: CommentHasCreatorPerson
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/dynamic/comment_hasTag_tag_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: CommentHasTagTag
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/dynamic/comment_isLocatedIn_place_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: CommentIsLocatedInPlace
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/dynamic/comment_replyOf_comment_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: CommentReplyOfComment
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/dynamic/comment_replyOf_post_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: CommentReplyOfPost
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/dynamic/forum_containerOf_post_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: ForumContainerOfPost
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/dynamic/forum_hasMember_person_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: ForumHasMemberPerson
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
      props:
        - name: "joinDate"
          type: "STRING"
          index: 2
  - path: /home/0.1/dynamic/forum_hasModerator_person_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: ForumHasModeratorPerson
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/dynamic/forum_hasTag_tag_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: ForumHasTagTag
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/dynamic/person_hasInterest_tag_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: PersonHasInterestTag
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/dynamic/person_isLocatedIn_place_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: PersonIsLocatedInPlace
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/dynamic/person_studyAt_organisation_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: PersonStudyAtOrganisation
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
      props:
        - name: "classYear"
          type: "STRING"
          index: 2
  - path: /home/0.1/dynamic/person_workAt_organisation_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: PersonWorkAtOrganisation
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
      props:
        - name: "workFrom"
          type: "STRING"
          index: 2
  - path: /home/0.1/dynamic/post_hasTag_tag_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: PostHasTagTag
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/dynamic/post_isLocatedIn_place_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: PostIsLocatedInPlace
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/static/organisation_isLocatedIn_place_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: OrganisationIsLocatedInPlace
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/static/place_isPartOf_place_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: PlaceIsPartOfPlace
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/static/tag_hasType_tagclass_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: TagHasTypeTagClass
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1
  - path: /home/0.1/static/tagclass_isSubclassOf_tagclass_0_0.csv
    batch: 1024
    csv:
      delimiter: "|"
      withHeader: true
      lazyQuotes: false
    edges:
    - name: TagClassIsSubclassOfTagClass
      mode: INSERT
      src:
        id:
          type: "STRING"
          index: 0
      dst:
        id:
          type: "STRING"
          index: 1

查看 NebulaGraph 服务的状态和端口

执行命令docker-compose ps可以列出 NebulaGraph 服务的状态和端口。

$ docker-compose ps
NAME                COMMAND             SERVICE             STATUS              PORTS
tanwei-web-1        "./server"          web                 running             0.0.0.0:57008->7001/tcp, :::57008->7001/tcp

如果服务有异常，用户可以先确认异常的容器名称（例如nebula-docker-compose_graphd2_1），然后登录容器排查问题：

$ docker exec -it nebula-docker-compose_graphd2_1 bash

查看 NebulaGraph 服务的数据和日志

NebulaGraph 的所有数据和日志都持久化存储在nebula-docker-compose/data和nebula-docker-compose/logs目录中。

目录的结构如下：

nebula-docker-compose/
  |-- docker-compose.yaml
  ├── data
  │   ├── meta
  │   └── storage
  └── logs
      ├── graph
      ├── meta
      └── storage

修改配置

Docker Compose 配置文件位置为nebula-docker-compose/docker-compose.yaml，修改该文件内的配置并重启服务即可使新配置生效。

docker-compose.yaml文件中的配置会覆盖服务容器内的配置文件（/usr/local/nebula/etc）的配置，因此也可以通过修改docker-compose.yaml文件设置服务的配置。

重启 NebulaGraph 服务

重启所有 NebulaGraph 服务：

$ docker-compose restart
Restarting nebula-docker-compose_console_1   ... done
Restarting nebula-docker-compose_graphd_1    ... done
Restarting nebula-docker-compose_graphd1_1   ... done
Restarting nebula-docker-compose_graphd2_1   ... done
Restarting nebula-docker-compose_storaged1_1 ... done
Restarting nebula-docker-compose-storaged0_1 ... done
Restarting nebula-docker-compose_storaged2_1 ... done
Restarting nebula-docker-compose_metad1_1    ... done
Restarting nebula-docker-compose_metad2_1    ... done
Restarting nebula-docker-compose_metad0_1    ... done

重启多个服务，例如重启 graphd 和 stoarged0 服务：

$ docker-compose restart graphd storaged0
Restarting nebula-docker-compose_graphd_1    ... done
Restarting nebula-docker-compose_storaged0_1 ... done

停止并删除 NebulaGraph 服务

用户可以执行如下命令停止并删除 Docker Compose启动的所有 NebulaGraph 服务：

Danger

该命令会停止并删除所有 NebulaGraph 服务的容器，以及相关网络。如果用户在docker-compose.yaml中定义了卷（volumes），则会保留相关数据。

命令docker-compose down -v的参数-v将会删除所有本地的数据。如果使用的是 nightly 版本，并且有一些兼容性问题，请尝试这个命令。

$ docker-compose down

如果返回如下信息，表示已经成功停止服务。

sheStopping nebula-docker-compose_console_1   ... done
Stopping nebula-docker-compose_graphd1_1   ... done
Stopping nebula-docker-compose_graphd_1    ... done
Stopping nebula-docker-compose_graphd2_1   ... done
Stopping nebula-docker-compose_storaged1_1 ... done
Stopping nebula-docker-compose_storaged0_1 ... done
Stopping nebula-docker-compose_storaged2_1 ... done
Stopping nebula-docker-compose_metad2_1    ... done
Stopping nebula-docker-compose_metad0_1    ... done
Stopping nebula-docker-compose_metad1_1    ... done
Removing nebula-docker-compose_console_1   ... done
Removing nebula-docker-compose_graphd1_1   ... done
Removing nebula-docker-compose_graphd_1    ... done
Removing nebula-docker-compose_graphd2_1   ... done
Removing nebula-docker-compose_storaged1_1 ... done
Removing nebula-docker-compose_storaged0_1 ... done
Removing nebula-docker-compose_storaged2_1 ... done
Removing nebula-docker-compose_metad2_1    ... done
Removing nebula-docker-compose_metad0_1    ... done
Removing nebula-docker-compose_metad1_1    ... done
Removing network nebula-docker-compose_nebula-net
2 个赞