Win10环境借助DockerDesktop部署大数据时序数据库Apache Druid

Win10环境借助DockerDesktop部署最新版大数据时序数据库Apache Druid32.0.0

前言

大数据分析中，有一种常见的场景，那就是时序数据，简言之，数据一旦产生绝对不会修改，随着时间流逝，每个时间点都会有个新的状态值。这种时序数据的量级往往异常夸张，例如传感器的原始监控数据：

https://lizhiyong.blog.csdn.net/article/details/114898620

一个简单的加速度传感器一年的数据量就是31e！！！制造业传感器数据如果不经底层PLC等下位机预处理，直接打到边缘计算网关，即使mqtt也会有巨大的负载！！！

类似的，还有服务器的原始监控数据，例如常见的Prometheus和Zabbix，当集群很多时，监控项同样很多，再算上虚拟化后的容器和虚拟机内都可能部署了监控，此时的数据量级就灰常可观！！！一小时几百亿条数据都是常见的事情！！！

但是很多原始的监控数据如果全部存下来，存储成本高的可怕，同时信息密度极低，更多时候我们可能只关注近期的全部热数据来做在线的模型训练，人工查看每秒钟几千条数据也是不切合实际的，事实上，做一个简单的秒级/分钟级统计就能满足大多数的分析场景，超过1天的冷数据其实已经没什么时效性。

对于此类场景，可以高吞吐、预聚合的数据库，在压测后，从Apache Druid、Clickhouse、Kylin中，选择了前者。。。专业的事情要交给专业的组件去做！！！

对于非内核和二开的业务开发人员，更多场景应该关注的是API、特性及用法，不应该在部署这种事情上花费太多精力！！！笔者之前已部署了Docker Desktop：

https://lizhiyong.blog.csdn.net/article/details/145580868

今天在Win10环境再搭建个Apache Druid最新版玩玩。

版本选择

官网：

https://druid.apache.org/

注意不是阿里数据库连接池的那个Druid！！！

截至2025-02-13，Apache Druid最新版本是32.0.0。

资源准备

参考官网：

https://druid.apache.org/docs/latest/tutorials/docker

官方给出了使用docker-compose.yml编排容器的教程，作为一个实时组件，大内存是必须的！！！但是启动8个容器【Zookeeper+PostgreSQL+6个Druid】每个最多7GB内存也不是什么大事！！！

https://raw.githubusercontent.com/apache/druid/32.0.0/distribution/docker/docker-compose.yml

获取到这个资源文件：

version: "2.2"

volumes:
  metadata_data: {}
  middle_var: {}
  historical_var: {}
  broker_var: {}
  coordinator_var: {}
  router_var: {}
  druid_shared: {}


services:
  postgres:
    container_name: postgres
    image: postgres:latest
    ports:
      - "5432:5432"
    volumes:
      - metadata_data:/var/lib/postgresql/data
    environment:
      - POSTGRES_PASSWORD=FoolishPassword
      - POSTGRES_USER=druid
      - POSTGRES_DB=druid

  # Need 3.5 or later for container nodes
  zookeeper:
    container_name: zookeeper
    image: zookeeper:3.5.10
    ports:
      - "2181:2181"
    environment:
      - ZOO_MY_ID=1

  coordinator:
    image: apache/druid:32.0.0
    container_name: coordinator
    volumes:
      - druid_shared:/opt/shared
      - coordinator_var:/opt/druid/var
    depends_on:
      - zookeeper
      - postgres
    ports:
      - "8081:8081"
    command:
      - coordinator
    env_file:
      - environment

  broker:
    image: apache/druid:32.0.0
    container_name: broker
    volumes:
      - broker_var:/opt/druid/var
    depends_on:
      - zookeeper
      - postgres
      - coordinator
    ports:
      - "8082:8082"
    command:
      - broker
    env_file:
      - environment

  historical:
    image: apache/druid:32.0.0
    container_name: historical
    volumes:
      - druid_shared:/opt/shared
      - historical_var:/opt/druid/var
    depends_on: 
      - zookeeper
      - postgres
      - coordinator
    ports:
      - "8083:8083"
    command:
      - historical
    env_file:
      - environment

  middlemanager:
    image: apache/druid:32.0.0
    container_name: middlemanager
    volumes:
      - druid_shared:/opt/shared
      - middle_var:/opt/druid/var
    depends_on: 
      - zookeeper
      - postgres
      - coordinator
    ports:
      - "8091:8091"
      - "8100-8105:8100-8105"
    command:
      - middleManager
    env_file:
      - environment

  router:
    image: apache/druid:32.0.0
    container_name: router
    volumes:
      - router_var:/opt/druid/var
    depends_on:
      - zookeeper
      - postgres
      - coordinator
    ports:
      - "3012:8888" #这里笔者改为3012防止霸占有用的端口
    command:
      - router
    env_file:
      - environment

参照官网另一篇：

https://druid.apache.org/docs/latest/configuration/

自己玩玩可以先不改这些运行时配置，容器启动的，后续要重新部署也非常容易！！！

还需要：

https://raw.githubusercontent.com/apache/druid/32.0.0/distribution/docker/environment

做另一个配置文件：

# Java tuning
#DRUID_XMX=1g
#DRUID_XMS=1g
#DRUID_MAXNEWSIZE=250m
#DRUID_NEWSIZE=250m
#DRUID_MAXDIRECTMEMORYSIZE=6172m
DRUID_SINGLE_NODE_CONF=micro-quickstart

druid_emitter_logging_logLevel=debug

druid_extensions_loadList=["druid-histogram", "druid-datasketches", "druid-lookups-cached-global", "postgresql-metadata-storage", "druid-multi-stage-query"]

druid_zk_service_host=zookeeper

druid_metadata_storage_host=
druid_metadata_storage_type=postgresql
druid_metadata_storage_connector_connectURI=jdbc:postgresql://postgres:5432/druid
druid_metadata_storage_connector_user=druid
druid_metadata_storage_connector_password=FoolishPassword

druid_indexer_runner_javaOptsArray=["-server", "-Xmx1g", "-Xms1g", "-XX:MaxDirectMemorySize=3g", "-Duser.timezone=UTC", "-Dfile.encoding=UTF-8", "-Djava.util.logging.manager=org.apache.logging.log4j.jul.LogManager"]
druid_indexer_fork_property_druid_processing_buffer_sizeBytes=256MiB

druid_storage_type=local
druid_storage_storageDirectory=/opt/shared/segments
druid_indexer_logs_type=file
druid_indexer_logs_directory=/opt/shared/indexing-logs

druid_processing_numThreads=2
druid_processing_numMergeBuffers=2

DRUID_LOG4J=<?xml version="1.0" encoding="UTF-8" ?><Configuration status="WARN"><Appenders><Console name="Console" target="SYSTEM_OUT"><PatternLayout pattern="%d{ISO8601} %p [%t] %c - %m%n"/></Console></Appenders><Loggers><Root level="info"><AppenderRef ref="Console"/></Root><Logger name="org.apache.druid.jetty.RequestLog" additivity="false" level="DEBUG"><AppenderRef ref="Console"/></Logger></Loggers></Configuration>

部署文件看起来麻雀虽小五脏俱全！！！

部署

PS C:\Users\zhiyong> cd E:\dockerData\volume\druid1
PS E:\dockerData\volume\druid1> ls


    目录: E:\dockerData\volume\druid1


Mode                 LastWriteTime         Length Name
----                 -------------         ------ ----
-a----        2025-02-13     23:26           2980 docker-compose.yml
-a----        2025-02-13     23:33           1576 environment
PS E:\dockerData\volume\druid1> docker compose up -d
time="2025-02-13T23:34:39+08:00" level=warning msg="E:\\dockerData\\volume\\druid1\\docker-compose.yml: the attribute `version` is obsolete, it will be ignored, please remove it to avoid potential confusion"
[+] Running 72/15
 ✔ router Pulled                                          230.7s 
 ✔ coordinator Pulled                                     230.7s 
 ✔ postgres Pulled                                        181.0s 
 ✔ historical Pulled                                      230.7s 
 ✔ broker Pulled                                          230.7s 
 ✔ middlemanager Pulled                                   230.7s 
 ✔ zookeeper Pulled                                        85.7s 








[+] Running 15/15
 ✔ Network druid1_default           Created                 0.1s 
 ✔ Volume "druid1_druid_shared"     Created                 0.0s 
 ✔ Volume "druid1_historical_var"   Created                 0.0s 
 ✔ Volume "druid1_middle_var"       Created                 0.0s 
 ✔ Volume "druid1_router_var"       Created                 0.0s 
 ✔ Volume "druid1_metadata_data"    Created                 0.0s 
 ✔ Volume "druid1_coordinator_var"  Created                 0.0s 
 ✔ Volume "druid1_broker_var"       Created                 0.0s 
 ✔ Container postgres               Started                 2.4s 
 ✔ Container zookeeper              Started                 2.4s 
 ✔ Container coordinator            Started                 1.6s 
 ✔ Container router                 Started                 2.5s 
 ✔ Container broker                 Started                 2.3s 
 ✔ Container historical             Started                 2.5s 
 ✔ Container middlemanager          Started                 2.8s 
PS E:\dockerData\volume\druid1>

拉取镜像成功后很快就能拉起容器：

好家伙。。。还顺便把其它组件的端口也给暴露出来了。。。

于是还**白piao**到一个PG和Zookeeper！！！

验证

http://localhost:3012/unified-console.html#

灰常好，现在已经拥有了一个最新Apache Druid32.0.0！！！

转载请注明出处：https://lizhiyong.blog.csdn.net/article/details/145622903