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HugeGraph Distributed (pd‐store) Version Deployment Guide
YangJiaqi edited this page Mar 10, 2025
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Note: 可以参考仓库 Docker-Compose 的分布式集群/配置进行类似的配置
- Linux, MacOS (Windows 环境下尚未进行过测试)
- Java version ≥ 11
- Maven version ≥ 3.5.0
- clone 源码 master 分支
git clone https://github.com/apache/hugegraph.git
- 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/apache-hugegraph-pd-incubating-1.5.0 - Store:
hugegraph-store/apache-hugegraph-store-incubating-1.5.0 - Server:
hugegraph-server/apache-hugegraph-server-incubating-1.5.0
.
├── hugegraph-pd
│ ├── apache-hugegraph-pd-incubating-1.5.0
│ └── apache-hugegraph-pd-incubating-1.5.0.tar.gz
├── hugegraph-server
│ ├── apache-hugegraph-server-incubating-1.5.0
│ └── apache-hugegraph-server-incubating-1.5.0.tar.gz
└─── hugegraph-store
├── apache-hugegraph-store-incubating-1.5.0
└── apache-hugegraph-store-incubating-1.5.0.tar.gz在运行 pd, store, server 时,上述路径即工作路径
- 运行 pd
cd hugegraph-pd/apache-hugegraph-pd-incubating-1.5.0
./bin/start-hugegraph-pd.sh若启动正常,可以在 hugegraph-pd/apache-hugegraph-pd-incubating-1.5.0/logs/hugegraph-pd-stdout.log 找到下述日志
2024年04月08日 15:15:45 [main] [INFO] o.a.h.p.b.HugePDServer - Started HugePDServer in 3.879 seconds (JVM running for 5.149)
- 运行 store
cd hugegraph-store/apache-hugegraph-store-incubating-1.5.0
./bin/start-hugegraph-store.sh若启动正常,可以在 hugegraph-store/apache-hugegraph-store-incubating-1.5.0/logs/hugegraph-store-server.log 找到下述日志
2024年04月08日 15:16:29 [main] [INFO] o.a.h.s.n.StoreNodeApplication - Started StoreNodeApplication in 4.794 seconds (JVM running for 6.21)
- 运行 server
cd hugegraph-server/apache-hugegraph-server-incubating-1.5.0 ./bin/start-hugegraph.sh -p true
传入 -p true 导入示例图,参考
简单的验证
> curl http://localhost:8080/graphs {"graphs":["hugegraph"]}
- 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
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
apache-hugegraph-pd-incubating-1.5.0apache-hugegraph-store-incubating-1.5.0apache-hugegraph-server-incubating-1.5.0
之后流程与上述一致
- 3 PD
- raft ports: 8610, 8611, 8612
- rpc ports: 8686, 8687, 8688
- rest ports: 8620, 8621, 8622
- 3 Store
- raft ports: 8510, 8511, 8512
- rpc ports: 8500, 8501, 8502
- rest ports: 8520, 8521, 8522
- 3 Server (disable auth + use distributed scheduler)
- rest ports: 8081, 8082, 8083
- rpc ports: 8091, 8092, 8093
- gremlin ports: 8181, 8182, 8183
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
将 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
仅以 PD 节点 A 为例
修改配置文件 hugegraph-pd/apache-hugegraph-pd-incubating-1.5.0/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
仅以 Store 节点 A 为例
修改配置文件 hugegraph-store/apache-hugegraph-store-incubating-1.5.0/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