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  • centos安装集群笔记

    时间同步

          服务端 内网主机

            yum install ntpdate ntp -y

            systemctl start ntpdate
            systemctl start ntpd

         客户端同步内网主机时间

             yum install ntpdate

             ntpdate 192.168.0.123
            18 Sep 09:17:38 ntpdate[9284]: step time server 192.168.0.123 offset -682.947247 sec

    解压rar包

             wget http://www.rarsoft.com/rar/rarlinux-x64-5.4.0.tar.gz

             tar -xvf rarlinux-x64-5.4.0.tar.gz

             cd rar
             make

             看见下面这些信息就是安装成功了
             mkdir -p /usr/local/bin
             mkdir -p /usr/local/lib
             cp rar unrar /usr/local/bin
             cp rarfiles.lst /etc
             cp default.sfx /usr/local/lib

            解压rar包

               rar x tianyiyun.rar

    ES配置内存大小

           不要超过32G

           Elasticsearch默认安装后设置的内存是1GB,对于任何一个业务部署来说,这个都太小了。如果你正在使用这些默认堆内存配置,你的集群配置可能有点问题
           这里有另外一个原因不分配大内存给Elasticsearch,事实上jvm在内存小于32G的时候会采用一个内存对象指针压缩技术。
           在java中,所有的对象都分配在堆上,然后有一个指针引用它。指向这些对象的指针大小通常是CPU的字长的大小,不是32bit就是64bit,这取决于你的处理器,指针指向了你的值的精确位置。
           对于32位系统,你的内存最大可使用4G。对于64系统可以使用更大的内存。但是64位的指针意味着更大的浪费,因为你的指针本身大了。浪费内存不算,更糟糕的是,更大的指针在主内存和缓存器(例如LLC, L1等)之间移动数据的时候,会占用更多的带宽。
           java 使用一个叫内存指针压缩的技术来解决这个问题。它的指针不再表示对象在内存中的精确位置,而是表示偏移量。这意味着32位的指针可以引用40亿个对象,而不是40亿个字节。最终,也就是说堆内存长到32G的物理内存,也可以用32bit的指针表示。
            一旦你越过那个神奇的30-32G的边界,指针就会切回普通对象的指针,每个对象的指针都变长了,就会使用更多的CPU内存带宽,也就是说你实际上失去了更多的内存,事实上当内存到达40-50GB的时候,有效内存才相当于使用内存对象指针压缩技术时候的32G内存
           这段描述的意思就是说:即便你有足够的内存,也尽量不要超过32G,因为它浪费了内存,降低了CPU的性能,还要让GC应对大内存

    Ansible过滤特定组的主机

           

     Flink Jobmanager(Master HA)高可用

                        

             

             

            

           

    ################################################################################
    #  Licensed to the Apache Software Foundation (ASF) under one
    #  or more contributor license agreements.  See the NOTICE file
    #  distributed with this work for additional information
    #  regarding copyright ownership.  The ASF licenses this file
    #  to you under the Apache License, Version 2.0 (the
    #  "License"); you may not use this file except in compliance
    #  with the License.  You may obtain a copy of the License at
    #
    #      http://www.apache.org/licenses/LICENSE-2.0
    #
    #  Unless required by applicable law or agreed to in writing, software
    #  distributed under the License is distributed on an "AS IS" BASIS,
    #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    #  See the License for the specific language governing permissions and
    # limitations under the License.
    ################################################################################
    
    
    #==============================================================================
    # Common
    #==============================================================================
    
    # The external address of the host on which the JobManager runs and can be
    # reached by the TaskManagers and any clients which want to connect. This setting
    # is only used in Standalone mode and may be overwritten on the JobManager side
    # by specifying the --host <hostname> parameter of the bin/jobmanager.sh executable.
    # In high availability mode, if you use the bin/start-cluster.sh script and setup
    # the conf/masters file, this will be taken care of automatically. Yarn/Mesos
    # automatically configure the host name based on the hostname of the node where the
    # JobManager runs.
    
    jobmanager.rpc.address: 192.168.0.195
    
    # The RPC port where the JobManager is reachable.
    
    jobmanager.rpc.port: 6123
    
    #taskmanager.memory.jvm-metaspace.size: 1024m
    
    # The total process memory size for the JobManager.
    #
    # Note this accounts for all memory usage within the JobManager process, including JVM metaspace and other overhead.
    
    #jobmanager.memory.process.size: 1600m
    jobmanager.memory.process.size: 4096m
    jobmanager.memory.jvm-metaspace.size: 2048m
    
    # The total process memory size for the TaskManager.
    #
    # Note this accounts for all memory usage within the TaskManager process, including JVM metaspace and other overhead.
    
    taskmanager.memory.task.heap.size: 2048m
    taskmanager.memory.managed.size: 1024m
    taskmanager.memory.framework.off-heap.size: 2048m
    taskmanager.memory.jvm-metaspace.size: 2048m
    #taskmanager.memory.process.size: 1728m
    # To exclude JVM metaspace and overhead, please, use total Flink memory size instead of 'taskmanager.memory.process.size'.
    # It is not recommended to set both 'taskmanager.memory.process.size' and Flink memory.
    #
    # taskmanager.memory.flink.size: 1280m
    
    # The number of task slots that each TaskManager offers. Each slot runs one parallel pipeline.
    
    taskmanager.numberOfTaskSlots: 300
    
    # The parallelism used for programs that did not specify and other parallelism.
    
    parallelism.default: 1
    
    # The default file system scheme and authority.
    #
    # By default file paths without scheme are interpreted relative to the local
    # root file system 'file:///'. Use this to override the default and interpret
    # relative paths relative to a different file system,
    # for example 'hdfs://mynamenode:12345'
    #
    # fs.default-scheme
    
    #==============================================================================
    # High Availability
    #==============================================================================
    
    # The high-availability mode. Possible options are 'NONE' or 'zookeeper'.
    #
    high-availability: zookeeper
    
    # The path where metadata for master recovery is persisted. While ZooKeeper stores
    # the small ground truth for checkpoint and leader election, this location stores
    # the larger objects, like persisted dataflow graphs.
    #
    # Must be a durable file system that is accessible from all nodes
    # (like HDFS, S3, Ceph, nfs, ...)
    #
    high-availability.storageDir: /data/tianyiyun/nfsdata/flink/flink-ha/
    
    # The list of ZooKeeper quorum peers that coordinate the high-availability
    # setup. This must be a list of the form:
    # "host1:clientPort,host2:clientPort,..." (default clientPort: 2181)
    #
    high-availability.zookeeper.quorum: 192.168.0.232:32181,192.168.0.125:32181,192.168.0.40:32181/flinkha
    
    
    # ACL options are based on https://zookeeper.apache.org/doc/r3.1.2/zookeeperProgrammers.html#sc_BuiltinACLSchemes
    # It can be either "creator" (ZOO_CREATE_ALL_ACL) or "open" (ZOO_OPEN_ACL_UNSAFE)
    # The default value is "open" and it can be changed to "creator" if ZK security is enabled
    #
    # high-availability.zookeeper.client.acl: open
    
    #==============================================================================
    # Fault tolerance and checkpointing
    #==============================================================================
    
    # The backend that will be used to store operator state checkpoints if
    # checkpointing is enabled.
    #
    # Supported backends are 'jobmanager', 'filesystem', 'rocksdb', or the
    # <class-name-of-factory>.
    #
    # state.backend: filesystem
    
    # Directory for checkpoints filesystem, when using any of the default bundled
    # state backends.
    #
    # state.checkpoints.dir: hdfs://namenode-host:port/flink-checkpoints
    
    # Default target directory for savepoints, optional.
    #
    # state.savepoints.dir: hdfs://namenode-host:port/flink-checkpoints
    
    # Flag to enable/disable incremental checkpoints for backends that
    # support incremental checkpoints (like the RocksDB state backend).
    #
    # state.backend.incremental: false
    state.checkpoints.num-retained: 2
    
    # The failover strategy, i.e., how the job computation recovers from task failures.
    # Only restart tasks that may have been affected by the task failure, which typically includes
    # downstream tasks and potentially upstream tasks if their produced data is no longer available for consumption.
    
    jobmanager.execution.failover-strategy: region
    
    #==============================================================================
    # Rest & web frontend
    #==============================================================================
    
    # The port to which the REST client connects to. If rest.bind-port has
    # not been specified, then the server will bind to this port as well.
    #
    #rest.port: 8081
    
    # The address to which the REST client will connect to
    #
    #rest.address: 0.0.0.0
    
    # Port range for the REST and web server to bind to.
    #
    #rest.bind-port: 8080-8090
    
    # The address that the REST & web server binds to
    #
    #rest.bind-address: 0.0.0.0
    rest.bind-address: 0.0.0.0
    # Flag to specify whether job submission is enabled from the web-based
    # runtime monitor. Uncomment to disable.
    
    #web.submit.enable: false
    
    #==============================================================================
    # Advanced
    #==============================================================================
    
    # Override the directories for temporary files. If not specified, the
    # system-specific Java temporary directory (java.io.tmpdir property) is taken.
    #
    # For framework setups on Yarn or Mesos, Flink will automatically pick up the
    # containers' temp directories without any need for configuration.
    #
    # Add a delimited list for multiple directories, using the system directory
    # delimiter (colon ':' on unix) or a comma, e.g.:
    #     /data1/tmp:/data2/tmp:/data3/tmp
    #
    # Note: Each directory entry is read from and written to by a different I/O
    # thread. You can include the same directory multiple times in order to create
    # multiple I/O threads against that directory. This is for example relevant for
    # high-throughput RAIDs.
    #
    # io.tmp.dirs: /tmp
    io.tmp.dirs: /data/tianyiyun/nfsdata/flink/flink-temp
    # The classloading resolve order. Possible values are 'child-first' (Flink's default)
    # and 'parent-first' (Java's default).
    #
    # Child first classloading allows users to use different dependency/library
    # versions in their application than those in the classpath. Switching back
    # to 'parent-first' may help with debugging dependency issues.
    #
    # classloader.resolve-order: child-first
    
    # The amount of memory going to the network stack. These numbers usually need
    # no tuning. Adjusting them may be necessary in case of an "Insufficient number
    # of network buffers" error. The default min is 64MB, the default max is 1GB.
    #
    #taskmanager.memory.network.fraction: 0.1
    #taskmanager.memory.network.min: 64mb
    #taskmanager.memory.network.max: 1gb
    
    #==============================================================================
    # Flink Cluster Security Configuration
    #==============================================================================
    
    # Kerberos authentication for various components - Hadoop, ZooKeeper, and connectors -
    # may be enabled in four steps:
    # 1. configure the local krb5.conf file
    # 2. provide Kerberos credentials (either a keytab or a ticket cache w/ kinit)
    # 3. make the credentials available to various JAAS login contexts
    # 4. configure the connector to use JAAS/SASL
    
    # The below configure how Kerberos credentials are provided. A keytab will be used instead of
    # a ticket cache if the keytab path and principal are set.
    
    # security.kerberos.login.use-ticket-cache: true
    # security.kerberos.login.keytab: /path/to/kerberos/keytab
    # security.kerberos.login.principal: flink-user
    
    # The configuration below defines which JAAS login contexts
    
    # security.kerberos.login.contexts: Client,KafkaClient
    
    #==============================================================================
    # ZK Security Configuration
    #==============================================================================
    
    # Below configurations are applicable if ZK ensemble is configured for security
    
    # Override below configuration to provide custom ZK service name if configured
    # zookeeper.sasl.service-name: zookeeper
    
    # The configuration below must match one of the values set in "security.kerberos.login.contexts"
    # zookeeper.sasl.login-context-name: Client
    
    #==============================================================================
    # HistoryServer
    #==============================================================================
    
    # The HistoryServer is started and stopped via bin/historyserver.sh (start|stop)
    
    # Directory to upload completed jobs to. Add this directory to the list of
    # monitored directories of the HistoryServer as well (see below).
    jobmanager.archive.fs.dir: file:///data/tianyiyun/nfsdata/flink/flink-history
    
    # The address under which the web-based HistoryServer listens.
    #historyserver.web.address: 0.0.0.0
    
    # The port under which the web-based HistoryServer listens.
    historyserver.web.port: 8882
    
    # Comma separated list of directories to monitor for completed jobs.
    historyserver.archive.fs.dir: file:///data/tianyiyun/nfsdata/flink/flink-history
    # Interval in milliseconds for refreshing the monitored directories.
    #historyserver.archive.fs.refresh-interval: 10000
    
    env.java.home: /usr/lib/java/jdk1.8.0_191
    web.upload.dir: /data/tianyiyun/nfsdata/flink/flink-web-jar
    
    
    metrics.reporters: prom
    metrics.reporter.prom.class: org.apache.flink.metrics.prometheus.PrometheusReporter
    metrics.reporter.prom.port: 9213-9214
    flink-conf.yaml
    192.168.0.195:8081
    192.168.0.170:8081
    masters
    192.168.0.75
    192.168.0.7
    workers

    flink 集群重启宕机服务

          jobmanager.sh start cluster jobmanager-01

         

     zk常用命令

      #1.连接zk命令
         [root@raid2t shell]# zkCli.sh -server localhost:2181
      #2.创建zk节点
         [zk: localhost:2181(CONNECTED) 1] create  /master  myData
      #3. 获取master节点数据
         [zk: localhost:2181(CONNECTED) 1]  get /master
      #4. 给master节点赋值data123456
         [zk: localhost:2181(CONNECTED) 1]  set /master  data123456
      #5. 删除master节点
        [zk: localhost:2181(CONNECTED) 1]  delete /master   deleteall /master 删除非空节点
     
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  • 原文地址:https://www.cnblogs.com/yxh168/p/15307223.html
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