Win10环境借助DockerDesktop部署大数据时序数据库Apache Druid的操作方法_F11

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：

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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