Druid集群配置
一、默认端口
二、集群配置思想
(一)本集群有五个节点(master, slave1,slave2,slave3,slave4),节点安排情况如下:
master节点:Mysql server, coordinator node, overlord node
slave1节点: historical node, middleManager node
slave2节点: historical node, middleManager node
slave3节点: broker node
slave4节点: realtime node(没有配置,空着)
(二)配置deep storage(保存冷数据)为HDFS
三、集群配置
(一)配置所有节点(master, slave1,slave2,slave3,slave4)的_common/common.runtime.properties文件
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- #
- # 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.
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- # under the License.
- #
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- # 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=["mysql-metadata-storage","druid-hdfs-storage"]
- # 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=/my/dir/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=master:2181,slave1:2181,slave2:2181,slave3:2181,slave4:2181
- #druid.zk.service.host=master: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://localhost:3306/druid?characterEncoding=UTF-8
- druid.metadata.storage.connector.user=***
- druid.metadata.storage.connector.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=hdfs://master:9000/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=hdfs://master:9000/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=["com.metamx.metrics.JvmMonitor"]
- druid.emitter=logging
- druid.emitter.logging.logLevel=info
(二)配置master节点的coordinator(在coordinator/runtime.properties文件里)
- druid.service=druid/coordinator
- druid.port=8081
- druid.coordinator.startDelay=PT30S
- druid.coordinator.period=PT30S
- #Below it's append by fenghui for test
- druid.host=master
配置master节点的 overlord(在overlord/runtime.properties文件里)
- druid.service=druid/overlord
- druid.port=8090
- #druid.indexer.queue.startDelay=PT30S
- druid.indexer.runner.type=remote
- druid.indexer.storage.type=metadata
- #below it is append by fenghui for test!
- druid.host=master
- #druid.indexer.logs.type=hdfs
- #druid.indexer.logs.directory=/druid/indexing-logs
(三)配置slave1节点的historical (在historical /runtime.properties文件里)
- druid.service=druid/historical
- druid.port=8083
- # HTTP server threads
- druid.server.http.numThreads=25
- # Processing threads and buffers
- druid.processing.buffer.sizeBytes=6870912
- druid.processing.numThreads=7
- # Segment storage
- druid.segmentCache.locations=[{"path":"var/druid/segment-cache","maxSize"\:130000000000}]
- druid.server.maxSize=130000000000
- druid.host=slave1
- druid.historical.cache.useCache=false
- druid.historical.cache.populateCache=false
配置slave1节点的middleManager (在middleManager /runtime.properties文件里)
- druid.service=druid/middleManager
- druid.port=8091
- # Number of tasks per middleManager
- druid.worker.capacity=3
- # Task launch parameters
- druid.indexer.runner.javaOpts=-server -Xmx256m -Duser.timezone=UTC -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
- druid.processing.buffer.sizeBytes=65536
- druid.processing.numThreads=2
- # Hadoop indexing
- druid.indexer.task.hadoopWorkingPath=var/druid/hadoop-tmp
- druid.indexer.task.defaultHadoopCoordinates=["org.apache.hadoop:hadoop-client:2.3.0"]
- #below it's append by fenghui for test
- druid.host=slave1
- #druid.indexer.logs.type=hdfs
- #druid.indexer.logs.directory=/druid/indexing-logs
(四)配置slave2节点(同slave1节点)
(五)配置slave1节点的broker(在broker/runtime.properties文件里)
- druid.service=druid/broker
- druid.port=8082
- # HTTP server threads
- druid.broker.http.numConnections=5
- druid.server.http.numThreads=25
- # Processing threads and buffers
- druid.processing.buffer.sizeBytes=32768
- druid.processing.numThreads=2
- # Query cache
- druid.broker.cache.useCache=true
- druid.broker.cache.populateCache=true
- druid.cache.type=local
- druid.cache.sizeInBytes=2000000000
- druid.host=slave3
三、启动集群命令
分别到每个节点(master, slave1,slave2,slave3,slave4)去启动相应的服务,命令如下(下面是启动broker的命令): java -Xmx256m -Duser.timezone=UTC -Dfile.encoding=UTF-8 -classpath conf/druid/_common:conf/druid/broker:lib/* io.druid.cli.Main server broker &
四、验证集群
(一)打开web端
http://master:8090/console.html
http://master:8081/#/

(二)下载测试文件,把文件解压到每个节点(master, slave1,slave2,slave3,slave4)的druid-0.9.1.1目录下,然后再file目录下执行 bash submit_task.sh命令,可以在http://master:8090/console.html下查看状态
在file目录下执行bash query_task.sh命令
参考文件: