一.Apache Druid简述
Apache Druid是MetaMarket公司研发，专门为做海量数据集上的高性能OLAP（OnLine Analysis Processing）而设计的数据存储和分析系统，目前在Apache基金会下孵化。
采用Lambda架构，分为实时层（Overlad、MiddleManager）和批处理层（Coordinator、Historical），通过Broker节点客户端提供查询服务，Router节点Overlad、Coordinator和Broker提供统一的API网关服务，系统架构如下：
二.主要角色简述
Ⅰ).Overload
Overload进程负责监控MiddleManager进程，它负责将摄取任务分配给MiddleManager并协调segment的发布；它就是数据摄入到Dirid的控制器
Ⅱ).Coordinator
Coordinator进程负责监控Historical进程，它负责将segment分配到指定的Historical服务上，确保所有Historical节点的数据均衡
Ⅲ).MiddleManager
MiddleManager进程负责将新的数据摄入到集群中，将外部数据源数据转换为Druid所识别的segment
Ⅳ).Broker
Broker进程负责接受Client的查询请求，并将查询转发到Historical和MiddleManager中；Broker会接受所有的子查询的结果，并将数据进行合并然后返回给Client
Ⅴ).Historical
Historical是用于处理存储和查询历史数据的进程，它会从Deep Storage中下载查询区间数据，然后响应该段数据的查询
Ⅵ).Router
Router进程是一个可选的进程，它为Broker、Overload和Coordinator提供统一的API网关服务。如果不启动该进程，也可以直接连接Broker、Overload和Coordinator服务
三.安装部署
Ⅰ).角色分布
Ⅱ).下载
下载地址：
https://druid.apache.org/downloads.html apache-druid-0.15.0Ⅲ).解压
tar -zxvf apache-druid-0.15.0-incubating-bin.tar.gz Ⅳ).目录
| PATH | DESCRIPTION |
|---|---|
| bin | 执行脚本 |
| conf | 角色配置 |
| extensions | 扩展插件 |
| lib | 依赖jar包 |
| log | 日志 |
| quickstart | 测试样例数据 |
| hadoop-dependencies | hadoop集群依赖 |
Ⅴ).配置
a)../_common/common.runtime.properties
#
# Extensions
#
# This is not the full list of Druid extensions, but common ones that people often use. You may need to change this list
# based on your particular setup.
druid.extensions.loadList=[ "druid-datasketches", "druid-hdfs-storage","druid-kafka-eight", "mysql-metadata-storage","druid-kafka-indexing-service"]
# If you have a different version of Hadoop, place your Hadoop client jar files in your hadoop-dependencies directory
# and uncomment the line below to point to your directory.
druid.extensions.hadoopDependenciesDir=/druid/druid/hadoop-dependencies/
#
# Logging
#
# Log all runtime properties on startup. Disable to avoid logging properties on startup:
druid.startup.logging.logProperties=true
#
# Zookeeper
#
druid.zk.service.host=hostname1:2181,hostname2:2181,hostname3:2181
druid.zk.paths.base=/druid
#
# Metadata storage
#
# For Derby server on your Druid Coordinator (only viable in a cluster with a single Coordinator, no fail-over):
#druid.metadata.storage.type=derby
#druid.metadata.storage.connector.connectURI=jdbc:derby://metadata.store.ip:1527/var/druid/metadata.db;create=true
#druid.metadata.storage.connector.host=metadata.store.ip
#druid.metadata.storage.connector.port=1527
# For MySQL:
druid.metadata.storage.type=mysql
druid.metadata.storage.connector.connectURI=jdbc:mysql://hostname1:3306/druid
druid.metadata.storage.connector.user=username
druid.metadata.storage.connector.password=password
# For PostgreSQL (make sure to additionally include the Postgres extension):
#druid.metadata.storage.type=postgresql
#druid.metadata.storage.connector.connectURI=jdbc:postgresql://db.example.com:5432/druid
#druid.metadata.storage.connector.user=...
#druid.metadata.storage.connector.password=...
#
# Deep storage
#
# For local disk (only viable in a cluster if this is a network mount):
#druid.storage.type=local
#druid.storage.storageDirectory=var/druid/segments
# For HDFS (make sure to include the HDFS extension and that your Hadoop config files in the cp):
druid.storage.type=hdfs
druid.storage.storageDirectory=/druid/segments
# For S3:
#druid.storage.type=s3
#druid.storage.bucket=your-bucket
#druid.storage.baseKey=druid/segments
#druid.s3.accessKey=...
#druid.s3.secretKey=...
#
# Indexing service logs
#
# For local disk (only viable in a cluster if this is a network mount):
#druid.indexer.logs.type=file
#druid.indexer.logs.directory=var/druid/indexing-logs
# For HDFS (make sure to include the HDFS extension and that your Hadoop config files in the cp):
druid.indexer.logs.type=hdfs
druid.indexer.logs.directory=/druid/indexing-logs
# For S3:
#druid.indexer.logs.type=s3
#druid.indexer.logs.s3Bucket=your-bucket
#druid.indexer.logs.s3Prefix=druid/indexing-logs
#
# Service discovery
#
druid.selectors.indexing.serviceName=druid/overlord
druid.selectors.coordinator.serviceName=druid/coordinator
#
# Monitoring
#
druid.monitoring.monitors=["io.druid.java.util.metrics.JvmMonitor"]
druid.emitter=logging
druid.emitter.logging.logLevel=info
# Storage type of double columns
# ommiting this will lead to index double as float at the storage layer
druid.indexing.doubleStorage=double b)../overlord/runtime.properties
druid.service=druid/overlord
druid.port=8065
druid.indexer.queue.startDelay=PT30S
druid.indexer.runner.type=remote
druid.indexer.storage.type=metadata c)../coordinator/runtime.properties
druid.service=druid/coordinator
druid.port=8062
druid.coordinator.startDelay=PT30S
druid.coordinator.period=PT30S d)../broker/runtime.properties
druid.service=druid/broker
druid.port=8061
# HTTP server threads
druid.broker.http.numConnections=5
druid.server.http.numThreads=25
# Processing threads and buffers
druid.processing.buffer.sizeBytes=536870912
druid.processing.numThreads=7
# Query cache
druid.broker.cache.useCache=true
druid.broker.cache.populateCache=true
druid.cache.type=local
druid.cache.sizeInBytes=2000000000 e)../middleManager/runtime.properties
druid.service=druid/middleManager
druid.port=8064
# Number of tasks per middleManager
druid.worker.capacity=100
# Task launch parameters
druid.indexer.runner.javaOpts=-server -Xmx8g -Duser.timezone=UTC+0800 -Dfile.encoding=UTF-8 -Djava.util.logging.manager=org.apache.logging.log4j.jul.LogManager
druid.indexer.task.baseTaskDir=var/druid/task
# HTTP server threads
druid.server.http.numThreads=25
# Processing threads and buffers on Peons
druid.indexer.fork.property.druid.processing.buffer.sizeBytes=536870912
druid.indexer.fork.property.druid.processing.numThreads=5
# Hadoop indexing
druid.indexer.task.hadoopWorkingPath=var/druid/hadoop-tmp
druid.indexer.task.defaultHadoopCoordinates=["org.apache.hadoop:hadoop-client:2.6.0"] f)../historical/runtime.properties
druid.service=druid/historical
druid.port=8063
# HTTP server threads
druid.server.http.numThreads=25
# Processing threads and buffers
druid.processing.buffer.sizeBytes=536870912
druid.processing.numThreads=7
# Segment storage
druid.segmentCache.locations=[{"path":"var/druid/segment-cache","maxSize":130000000000}]
druid.server.maxSize=130000000000 g)../router/runtime.properties
druid.service=druid/router
druid.plaintextPort=8888
# HTTP proxy
druid.router.http.numConnections=50
druid.router.http.readTimeout=PT5M
druid.router.http.numMaxThreads=100
druid.server.http.numThreads=100
# Service discovery
druid.router.defaultBrokerServiceName=druid/broker
druid.router.coordinatorServiceName=druid/coordinator
# Management proxy to coordinator / overlord: required for unified web console.
druid.router.managementProxy.enabled=true Ⅵ).启动服务
## start broker
./bin/broker.sh start
## start coordinator
./bin/coordinator.sh start
## start historical
./bin/historical.sh start
## start middleManager
./bin/middleManager.sh start
## start overlord
./bin/overlord.sh start Ⅶ).验证
Coordinator URL: http://hostname:8062
Overload URL: http://hostname:8065
Router URL: http://hostname:8888
四.hadoop依赖
如果使用hadoop集群做为结果集数据存储时，需与hadoop建立关联
ln -s /etc/hadoop/core-site.xml ./conf/druid/_common/core-site.xml
ln -s /etc/hadoop/hdfs-site.xml ./conf/druid/_common/hdfs-site.xml
ln -s /etc/hadoop/mapred-site.xml ./conf/druid/_common/mapred-site.xml
ln -s /etc/hadoop/yarn-site.xml ./conf/druid/_common/yarn-site.xml