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HugeGraph Distributed (pd‐store) Version Deployment Guide

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V_Galaxy edited this page Apr 8, 2024 · 9 revisions

前置条件

  • Linux, MacOS (Windows 环境下尚未进行过测试)
  • Java version ≥ 11
  • Maven version ≥ 3.5.0

从源码构建并启动

  1. clone 源码 pd-store 分支
git clone -b pd-store https://github.com/apache/hugegraph.git
  1. 在项目根目录下构建
cd hugegraph
mvn clean install -DskipTests=true

若构建成功，PD, Store, Server 三个模块的构建产物将依次存放在

  • PD: hugegraph-pd/dist/hugegraph-pd-1.5.0.1
  • Store: hugegraph-store/dist/hugegraph-store-1.5.0.1
  • Server: hugegraph-server/apache-hugegraph-incubating-1.5.0.1 
.
├── hugegraph-pd
│  └── dist
      ├── hugegraph-pd-1.5.0.1
      └── hugegraph-pd-1.5.0.1.tar.gz
├── hugegraph-server
│  ├── apache-hugegraph-incubating-1.5.0.1
│  └── apache-hugegraph-incubating-1.5.0.1.tar.gz
└─── hugegraph-store
   └── dist
      ├── hugegraph-store-1.5.0.1
      └── hugegraph-store-1.5.0.1.tar.gz

在运行 pd, store, server 时，上述路径即工作路径

  1. 运行 pd
cd hugegraph-pd/dist/hugegraph-pd-1.5.0.1
./bin/start-hugegraph-pd.sh

若启动正常，可以在 hugegraph-pd/dist/hugegraph-pd-1.5.0.1/logs/hugegraph-pd.log 找到下述日志

2024-04-08 15:15:45 [main] [INFO] o.a.h.p.b.HugePDServer - Started HugePDServer in 3.879 seconds (JVM running for 5.149)
  1. 运行 store
cd hugegraph-store/dist/hugegraph-store-1.5.0.1
./bin/start-hugegraph-store.sh

若启动正常，可以在 hugegraph-store/dist/hugegraph-store-1.5.0.1/logs/hugegraph-store.log 找到下述日志

2024-04-08 15:16:29 [main] [INFO] o.a.h.s.n.StoreNodeApplication - Started StoreNodeApplication in 4.794 seconds (JVM running for 6.21)
  1. 运行 server
cd hugegraph-server/apache-hugegraph-incubating-1.5.0.1
./bin/start-hugegraph.sh -p true

传入 -p true 导入示例图，参考 https://hugegraph.apache.org/docs/quickstart/hugegraph-server/#517-create-an-example-graph-when-startup

简单的验证

> curl http://localhost:8080/graphs
{"graphs":["hugegraph"]}
  1. 停止 server, store, pd

按顺序在上述各目录下执行

./bin/stop-hugegraph.sh
./bin/stop-hugegraph-store.sh
./bin/stop-hugegraph-pd.sh

下载 tar 包启动

在这个页面下载 pd, store, server tar 包并解压，解压之后将得到下述文件夹

  • hugegraph-pd-1.5.0.1
  • hugegraph-store-1.5.0.1
  • apache-hugegraph-incubating-1.5.0.1

之后流程与上述一致

多节点配置参考

  • 3 PD
    • raft ports 8610, 8611, 8612
    • rpc ports 8686, 8687, 8688
    • rest ports 8620, 8621, 8622
  • 3 Store
    • raft ports 8610, 8611, 8612
    • rpc ports 8686, 8687, 8688
    • rest ports 8620, 8621, 8622
  • 3 Server (disable auth + distributed scheduler)
    • rest ports 8081, 8082, 8083
    • rpc ports 8091, 8092, 8093
    • gremlin ports 8181, 8182, 8183

server

hugegraph.properties 均为

backend=hstore
serializer=binary
task.scheduler_type=distributed

# pd 服务地址，多个 pd 地址用逗号分割 ⚠️配置 pd 的 rpc 端口
pd.peers=127.0.0.1:8686,127.0.0.1:8687,127.0.0.1:8688

rest-server.properties 分别为

restserver.url=http://127.0.0.1:8081
gremlinserver.url=http://127.0.0.1:8181

rpc.server_host=127.0.0.1
rpc.server_port=8091

server.id=server-1
server.role=master
restserver.url=http://127.0.0.1:8082
gremlinserver.url=http://127.0.0.1:8182

rpc.server_host=127.0.0.1
rpc.server_port=8092

server.id=server-2
server.role=worker
restserver.url=http://127.0.0.1:8083
gremlinserver.url=http://127.0.0.1:8183

rpc.server_host=127.0.0.1
rpc.server_port=8093

server.id=server-3
server.role=worker

gremlin-server.yaml 分别为

host: 127.0.0.1
port: 8181
host: 127.0.0.1
port: 8182
host: 127.0.0.1
port: 8183

这个压缩包包含了 Server 节点 A, B, C 完整的配置文件，用于在 IDEA 中快捷启动多节点 Server

IDEA 某个运行配置的工作路径设置为对应的配置文件路径

image

pd

仅以 PD 节点 A 为例

修改配置文件 hugegraph-pd-1.5.0.1/conf/application.yml

spring:
  application:
    name: hugegraph-pd

management:
  metrics:
    export:
      prometheus:
        enabled: true
  endpoints:
    web:
      exposure:
        include: "*"

logging:
  config: 'file:./conf/log4j2.xml'
license:
  verify-path: ./conf/verify-license.json
  license-path: ./conf/hugegraph.license
grpc:
  # 集群模式
  port: 8686 # ⚠️本地测试要配不同端口
  host: 127.0.0.1 

server:
  # rest 服务端口号
  port: 8620 # ⚠️本地测试要配不同端口

pd:
  # 存储路径
  data-path: ./pd_data # ⚠️本地测试要配不同路径
  # 自动扩容的检查周期，定时检查每个 store 的分区数量，自动进行分区数量平衡
  patrol-interval: 1800
  # 初始 store 列表，在列表内的 store 自动激活
  initial-store-count: 1
  # grpc IP:grpc port 
  # store 的配置信息
  initial-store-list: 127.0.0.1:8500,127.0.0.1:8501,127.0.0.1:8502

raft:
  # 集群模式
  address: 127.0.0.1:8610 # ⚠️本地测试要配不同端口
  peers-list: 127.0.0.1:8610,127.0.0.1:8611,127.0.0.1:8612

store:
  # store 下线时间。超过该时间，认为 store 永久不可用，分配副本到其他机器，单位秒
  max-down-time: 172800
  # 是否开启 store 监控数据存储
  monitor_data_enabled: true
  # 监控数据的间隔，minute (默认), hour, second
  # default: 1 min * 1 day = 1440
  monitor_data_interval: 1 minute
  # 监控数据的保留时间 1 天; day, month, year
  monitor_data_retention: 1 day
  initial-store-count: 1

partition:
  # 默认每个分区副本数
  default-shard-count: 1
  # 默认每机器最大副本数，初始分区数 = store-max-shard-count * store-number / default-shard-count
  store-max-shard-count: 12

这个压缩包包含了 PD 节点 A, B, C 完整的配置文件，用于在 IDEA 中快捷启动多节点 PD

store

仅以 Store 节点 A 为例

修改配置文件 hugegraph-store/dist/hugegraph-store-1.5.0.1/conf/application.yml

pdserver:
  # pd 服务地址，多个 pd 地址用逗号分割 ⚠️配置 pd 的 rpc 端口
  address: 127.0.0.1:8686,127.0.0.1:8687,127.0.0.1:8688

management:
  metrics:
    export:
      prometheus:
        enabled: true
  endpoints:
    web:
      exposure:
        include: "*"

grpc:
  # grpc 的服务地址
  host: 127.0.0.1
  port: 8500 # ⚠️本地测试要配不同端口
  netty-server:
    max-inbound-message-size: 1000MB
raft:
  # raft 缓存队列大小
  disruptorBufferSize: 1024
  address: 127.0.0.1:8510 # ⚠️本地测试要配不同端口
  max-log-file-size: 600000000000
  # 快照生成时间间隔，单位秒
  snapshotInterval: 1800
server:
  # rest 服务地址
  port: 8520 # ⚠️本地测试要配不同端口

app:
  # 存储路径，支持多个路径，逗号分割
  data-path: ./storage # ⚠️本地测试要配不同路径
  #raft-path: ./storage

spring:
  application:
    name: store-node-grpc-server
  profiles:
    active: default
    include: pd

logging:
  config: 'file:./conf/log4j2.xml'
  level:
    root: info

这个压缩包包含了 Store 节点 A, B, C 完整的配置文件，用于在 IDEA 中快捷启动多节点 Store

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