Hadoop on k8s 编排部署进阶篇-六虎

一、概述

Hadoop 是一个开源的分布式计算框架，用于处理大规划数据集的存储和处理。它运用了 Hadoop 分布式文件系统（Hadoop Distributed File System，HDFS）来存储数据，并经过 MapReduce 编程模型进行数据处理。

Kubernetes（通常简称为K8s）是一个开源的容器编列渠道，用于主动化布置、扩展和办理容器化运用程序。它供给了一种强壮的方法来办理容器化运用程序的资源和生命周期。

将Hadoop布置在Kubernetes上（通常称为Hadoop on K8s或Hadoop on Kubernetes）是一种将Hadoop与 Kubernetes 结合运用的方法。它将 Hadoop 集群中的各个组件（如 NameNode、DataNode、ResourceManager 和 NodeManager ）打包为容器，并运用Kubernetes来主动办理和编列这些容器。

Hadoop on K8s具有以下一些优势：

弹性扩展：Kubernetes供给了动态扩展的才能，能够根据作业负载的需求主动调整Hadoop集群的规划。
灵活性：经过将Hadoop布置在Kubernetes上，能够愈加灵活地办理Hadoop集群的资源分配和调度，以适应不同的作业负载。
多租户支撑：Kubernetes的多租户支撑使得能够在同一个Kubernetes集群上运转多个独立的Hadoop集群，从而更好地隔离不同的运用和用户。
资源运用率：Kubernetes能够更好地办理和运用集群资源，防止资源糟蹋，进步资源运用率。
毛病康复：Kubernetes供给了毛病康复和自愈才能，能够在节点毛病时主动重新调度Hadoop容器，进步集群的可靠性。

要在 Kubernetes上布置 Hadoop 集群，需求运用适当的东西和装备，例如 Apache Hadoop Kubernetes 项目（Hadoop K8s）或其他第三方东西。这些东西供给了与 Kubernetes 集成的方法，并简化了在Kubernetes 上布置和办理 Hadoop 集群的过程。

总之，Hadoop on K8s 供给了一种在Kubernetes上运转Hadoop集群的方法，充分运用了Kubernetes的弹性、灵活性和资源办理功用。它能够简化Hadoop集群的布置和办理，并供给更好的资源运用率和可靠性。

之前也写过一篇相似的文章，因操作的过程比较多，这儿将进行改善升级，感兴趣的小伙伴请仔细阅读下文，这儿也供给经过docker-compse一键布置教程：

经过 docker-compose 快速布置 Hadoop 集群具体教程
经过 docker-compose 快速布置 Hive 具体教程

二、k8s 布置布置

k8s 环境布置这儿不重复讲解了，重点是 Hadoop on k8s，不知道怎么布置k8s环境的能够参阅我以下几篇文章：

【云原生】k8s 环境快速布置（一小时以内布置完）
【云原生】k8s 离线布置讲解和实战操作

三、开端编列布置 Hadoop

1）构建镜像 Dockerfile

FROM registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/centos:7.7.1908
RUN rm -f /etc/localtime && ln -sv /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && echo "Asia/Shanghai" > /etc/timezone
RUN export LANG=zh_CN.UTF-8
# 创立用户和用户组，跟yaml编列里的user: 10000:10000
RUN groupadd --system --gid=10000 hadoop && useradd --system --home-dir /home/hadoop --uid=10000 --gid=hadoop hadoop
# 装置sudo
RUN yum -y install sudo ; chmod 640 /etc/sudoers
# 给hadoop增加sudo权限
RUN echo "hadoop ALL=(ALL) NOPASSWD: ALL" >> /etc/sudoers
RUN yum -y install install net-tools telnet wget nc expect which
RUN mkdir /opt/apache/
# 装置 JDK
ADD jdk-8u212-linux-x64.tar.gz /opt/apache/
ENV JAVA_HOME /opt/apache/jdk1.8.0_212
ENV PATH $JAVA_HOME/bin:$PATH
# 装备 Hadoop
ENV HADOOP_VERSION 3.3.5
ADD hadoop-${HADOOP_VERSION}.tar.gz /opt/apache/
ENV HADOOP_HOME /opt/apache/hadoop
RUN ln -s /opt/apache/hadoop-${HADOOP_VERSION} $HADOOP_HOME
ENV HADOOP_COMMON_HOME=${HADOOP_HOME} \
    HADOOP_HDFS_HOME=${HADOOP_HOME} \
    HADOOP_MAPRED_HOME=${HADOOP_HOME} \
    HADOOP_YARN_HOME=${HADOOP_HOME} \
    HADOOP_CONF_DIR=${HADOOP_HOME}/etc/hadoop \
    PATH=${PATH}:${HADOOP_HOME}/bin
# 装备Hive
ENV HIVE_VERSION 3.1.3
ADD apache-hive-${HIVE_VERSION}-bin.tar.gz /opt/apache/
ENV HIVE_HOME=/opt/apache/hive
ENV PATH=$HIVE_HOME/bin:$PATH
RUN ln -s /opt/apache/apache-hive-${HIVE_VERSION}-bin ${HIVE_HOME}
# 装备spark
ENV SPARK_VERSION 3.3.2
ADD spark-${SPARK_VERSION}-bin-hadoop3.tgz /opt/apache/
ENV SPARK_HOME=/opt/apache/spark
ENV PATH=$SPARK_HOME/bin:$PATH
RUN ln -s /opt/apache/spark-${SPARK_VERSION}-bin-hadoop3 ${SPARK_HOME}
# 装备 flink
ENV FLINK_VERSION 1.17.0
ADD flink-${FLINK_VERSION}-bin-scala_2.12.tgz /opt/apache/
ENV FLINK_HOME=/opt/apache/flink
ENV PATH=$FLINK_HOME/bin:$PATH
RUN ln -s /opt/apache/flink-${FLINK_VERSION} ${FLINK_HOME}
# 创立namenode、datanode存储目录
RUN mkdir -p /opt/apache/hadoop/data/{hdfs,yarn} /opt/apache/hadoop/data/hdfs/namenode /opt/apache/hadoop/data/hdfs/datanode/data{1..3} /opt/apache/hadoop/data/yarn/{local-dirs,log-dirs,apps}
COPY bootstrap.sh /opt/apache/
COPY config/hadoop-config/* ${HADOOP_HOME}/etc/hadoop/
# hive  config
COPY hive-config/* ${HIVE_HOME}/conf/
COPY mysql-connector-java-5.1.49/mysql-connector-java-5.1.49-bin.jar ${HIVE_HOME}/lib/
RUN sudo mkdir -p /home/hadoop/ && sudo chown -R hadoop:hadoop /home/hadoop/
#RUN yum -y install which
ENV ll "ls -l"
RUN chown -R hadoop:hadoop /opt/apache
WORKDIR /opt/apache

bootstrap.sh 脚本内容

#!/usr/bin/env sh
source /etc/profile
wait_for() {
        if [ -n "$1" -a  -z -n "$2" ];then
           echo Waiting for $1 to listen on $2...
           while ! nc -z $1 $2; do echo waiting...; sleep 1s; done
        fi
}
start_hdfs_namenode() {
        namenode_dir=`grep -A1 'dfs.namenode.name.dir' ${HADOOP_HOME}/etc/hadoop/hdfs-site.xml |tail -1|sed 's/<value>//'|sed 's/<\/value>//'`
        if [ ! -d ${namenode_dir}/current ];then
           ${HADOOP_HOME}/bin/hdfs namenode -format
        fi
        ${HADOOP_HOME}/bin/hdfs --loglevel INFO --daemon start namenode
        tail -f ${HADOOP_HOME}/logs/*namenode*.log
}
start_hdfs_datanode() {
        wait_for $1 $2
        ${HADOOP_HOME}/bin/hdfs --loglevel INFO --daemon start datanode
        tail -f ${HADOOP_HOME}/logs/*datanode*.log
}
start_yarn_resourcemanager() {
        ${HADOOP_HOME}/bin/yarn --loglevel INFO --daemon start resourcemanager
        tail -f ${HADOOP_HOME}/logs/*resourcemanager*.log
}
start_yarn_nodemanager() {
        wait_for $1 $2
        ${HADOOP_HOME}/bin/yarn --loglevel INFO --daemon start nodemanager
        tail -f ${HADOOP_HOME}/logs/*nodemanager*.log
}
start_yarn_proxyserver() {
        wait_for $1 $2
        ${HADOOP_HOME}/bin/yarn --loglevel INFO --daemon start proxyserver
        tail -f ${HADOOP_HOME}/logs/*proxyserver*.log
}
start_mr_historyserver() {
        wait_for $1 $2
        ${HADOOP_HOME}/bin/mapred --loglevel INFO  --daemon  start historyserver
        tail -f ${HADOOP_HOME}/logs/*historyserver*.log
}
start_hive_metastore() {
        if [ ! -f ${HIVE_HOME}/formated ];then
                schematool -initSchema -dbType mysql --verbose >  ${HIVE_HOME}/formated
        fi
        $HIVE_HOME/bin/hive --service metastore
}
start_hive_hiveserver2() {
        $HIVE_HOME/bin/hive --service hiveserver2
}
case $1 in
        hadoop-hdfs-nn)
                start_hdfs_namenode $2 $3
                ;;
        hadoop-hdfs-dn)
                start_hdfs_datanode $2 $3
                ;;
        hadoop-yarn-rm)
                start_yarn_resourcemanager $2 $3
                ;;
        hadoop-yarn-nm)
                start_yarn_nodemanager $2 $3
                ;;
        hadoop-yarn-proxyserver)
                start_yarn_proxyserver $2 $3
                ;;
        hadoop-mr-historyserver)
                start_mr_historyserver $2 $3
                ;;
        hive-metastore)
                start_hive_metastore $2 $3
                ;;
        hive-hiveserver2)
                start_hive_hiveserver2 $2 $3
                ;;
        *)
                echo "请输入正确的服务发动命令~"
        ;;
esac

构建镜像：

docker build -t registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/hadoop_hive:v1 . --no-cache
# 为了便利小伙伴下载即可运用，我这儿将镜像文件推送到阿里云的镜像库房
docker push registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/hadoop_hive:v1
### 参数解释
# -t：指定镜像称号
# . ：当前目录Dockerfile
# -f：指定Dockerfile途径
#  --no-cache：不缓存

【温馨提示】假如不更换版别包，就无需再构建镜像，我现已构建好传到阿里云镜像库房了。假如需求修正Hadoop版别，能够基于我的镜像进行修正。

2）values.yaml 文件装备

image:
  repository: registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/hadoop_hive
  tag: v1
  pullPolicy: IfNotPresent
# The version of the hadoop libraries being used in the image.
hadoopVersion: 3.3.5
logLevel: INFO
# Select antiAffinity as either hard or soft, default is soft
antiAffinity: "soft"
hdfs:
  nameNode:
    replicas: 1
    pdbMinAvailable: 1
    resources:
      requests:
        memory: "1024Mi"
        cpu: "1000m"
      limits:
        memory: "2048Mi"
        cpu: "1000m"
  dataNode:
    # Will be used as dfs.datanode.hostname
    # You still need to set up services + ingress for every DN
    # Datanodes will expect to
    externalHostname: example.com
    externalDataPortRangeStart: 9866
    externalHTTPPortRangeStart: 9864
    replicas: 1
    pdbMinAvailable: 1
    resources:
      requests:
        memory: "1024Mi"
        cpu: "1000m"
      limits:
        memory: "2048Mi"
        cpu: "1000m"
  webhdfs:
    enabled: true
  jounralNode:
    replicas: 3
    pdbMinAvailable: 1
    resources:
      requests:
        memory: "1024Mi"
        cpu: "1000m"
      limits:
        memory: "2048Mi"
        cpu: "1000m"
  mrHistoryserver:
    pdbMinAvailable: 1
    replicas: 1
    resources:
      requests:
        memory: "1024Mi"
        cpu: "1000m"
      limits:
        memory: "1024Mi"
        cpu: "1000m"
yarn:
  resourceManager:
    pdbMinAvailable: 1
    replicas: 1
    resources:
      requests:
        memory: "1024Mi"
        cpu: "1000m"
      limits:
        memory: "1024Mi"
        cpu: "1000m"
  nodeManager:
    pdbMinAvailable: 1
    # The number of YARN NodeManager instances.
    replicas: 1
    # Create statefulsets in parallel (K8S 1.7+)
    parallelCreate: false
    # CPU and memory resources allocated to each node manager pod.
    # This should be tuned to fit your workload.
    resources:
      requests:
        memory: "1024Mi"
        cpu: "1000m"
      limits:
        memory: "2048Mi"
        cpu: "1000m"
  proxyServer:
    pdbMinAvailable: 1
    replicas: 1
    resources:
      requests:
        memory: "1024Mi"
        cpu: "1000m"
      limits:
        memory: "1024Mi"
        cpu: "1000m"
hive:
  metastore:
    replicas: 1
    pdbMinAvailable: 1
    resources:
      requests:
        memory: "1024Mi"
        cpu: "1000m"
      limits:
        memory: "2048Mi"
        cpu: "1000m"
  hiveserver2:
    replicas: 1
    pdbMinAvailable: 1
    resources:
      requests:
        memory: "1024Mi"
        cpu: "1000m"
      limits:
        memory: "1024Mi"
        cpu: "1000m"
persistence:
  nameNode:
    enabled: true
    enabledStorageClass: false
    storageClass: "hadoop-nn-local-storage"
    accessMode: ReadWriteOnce
    size: 1Gi
    local:
    #- name: hadoop-nn-0
    #  host: "local-168-182-110"
    #  path: "/opt/bigdata/servers/hadoop/nn/data/data1"
    volumes:
    - name: nn1
      mountPath: /opt/apache/hadoop/data/hdfs/namenode
      hostPath: /opt/bigdata/servers/hadoop/nn/data/data1
  dataNode:
    enabled: true
    enabledStorageClass: false
    storageClass: "hadoop-dn-local-storage"
    accessMode: ReadWriteOnce
    size: 1Gi
    #local:
    #- name: hadoop-dn-0
    #  host: "local-168-182-110"
    #  path: "/opt/bigdata/servers/hadoop/dn/data/data1"
    #- name: hadoop-dn-1
    #  host: "local-168-182-110"
    #  path: "/opt/bigdata/servers/hadoop/dn/data/data2"
    #- name: hadoop-dn-2
    #  host: "local-168-182-110"
    #  path: "/opt/bigdata/servers/hadoop/dn/data/data3"
    #- name: hadoop-dn-3
    #  host: "local-168-182-111"
    #  path: "/opt/bigdata/servers/hadoop/dn/data/data1"
    #- name: hadoop-dn-4
    #  host: "local-168-182-111"
    #  path: "/opt/bigdata/servers/hadoop/dn/data/data2"
    #- name: hadoop-dn-5
    #  host: "local-168-182-111"
    #  path: "/opt/bigdata/servers/hadoop/dn/data/data3"
    #- name: hadoop-dn-6
    #  host: "local-168-182-112"
    #  path: "/opt/bigdata/servers/hadoop/dn/data/data1"
    #- name: hadoop-dn-7
    #  host: "local-168-182-112"
    #  path: "/opt/bigdata/servers/hadoop/dn/data/data2"
    #- name: hadoop-dn-8
    #  host: "local-168-182-112"
    #  path: "/opt/bigdata/servers/hadoop/dn/data/data3"
    volumes:
    - name: dfs1
      mountPath: /opt/apache/hdfs/datanode1
      hostPath: /opt/bigdata/servers/hadoop/dn/data/data1
    - name: dfs2
      mountPath: /opt/apache/hdfs/datanode2
      hostPath: /opt/bigdata/servers/hadoop/dn/data/data2
    - name: dfs3
      mountPath: /opt/apache/hdfs/datanode3
      hostPath: /opt/bigdata/servers/hadoop/dn/data/data3
service:
  nameNode:
    type: NodePort
    ports:
      dfs: 9000
      webhdfs: 9870
    nodePorts:
      dfs: 30900
      webhdfs: 30870
  dataNode:
    type: NodePort
    ports:
      webhdfs: 9864
    nodePorts:
      webhdfs: 30864
  mrHistoryserver:
    type: NodePort
    ports:
      web: 19888
    nodePorts:
      web: 30888
  resourceManager:
    type: NodePort
    ports:
      web: 8088
    nodePorts:
      web: 30088
  nodeManager:
    type: NodePort
    ports:
      web: 8042
    nodePorts:
      web: 30042
  proxyServer:
    type: NodePort
    ports:
      web: 9111
    nodePorts:
      web: 30911
  hive:
    metastore:
      type: NodePort
      port: 9083
      nodePort: 31183
    hiveserver2:
      type: NodePort
      port: 10000
      nodePort: 30000
securityContext:
  runAsUser: 10000
  privileged: true

【温馨提示】这儿的 namenode 和 datanode 存储目录运用 hostPath 挂载方法，经过 enabledStorageClass 来控制是选择宿主机还是PVC挂载，为 false 是 hostPath 挂载方法，反之亦然。

在每个k8s节点上创立挂载目录：

# 假如运用pv，pvc挂载方法，就不需求在宿主机上创立目录了，非高可用可不用创立jn
mkdir -p /opt/bigdata/servers/hadoop/{nn,jn,dn}/data/data{1..3}
chmod 777 -R /opt/bigdata/servers/hadoop/

3）hadoop configmap yaml

apiVersion: v1
kind: ConfigMap
metadata:
  name: {{ include "hadoop.fullname" . }}
  labels:
    app.kubernetes.io/name: {{ include "hadoop.name" . }}
    helm.sh/chart: {{ include "hadoop.chart" . }}
    app.kubernetes.io/instance: {{ .Release.Name }}
data:
  core-site.xml: |
    <?xml version="1.0"?>
    <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
    <configuration>
      <property>
          <name>fs.defaultFS</name>
          <value>hdfs://{{ include "hadoop.fullname" . }}-hdfs-nn:9000/</value>
          <description>NameNode URI</description>
      </property>
      <property>
          <name>hadoop.proxyuser.root.hosts</name>
          <value>*</value>
      </property>
      <property>
          <name>hadoop.proxyuser.root.groups</name>
          <value>*</value>
      </property>
      <property>
          <name>hadoop.proxyuser.hadoop.hosts</name>
          <value>*</value>
      </property>
      <property>
          <name>hadoop.proxyuser.hadoop.groups</name>
          <value>*</value>
      </property>
    </configuration>
  hdfs-site.xml: |
    <?xml version="1.0"?>
    <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
    <configuration>
{{- if .Values.hdfs.webhdfs.enabled -}}
      <property>
          <name>dfs.webhdfs.enabled</name>
          <value>true</value>
      </property>
{{- end -}}
      <property>
        <name>dfs.datanode.use.datanode.hostname</name>
        <value>false</value>
      </property>
      <property>
        <name>dfs.client.use.datanode.hostname</name>
        <value>false</value>
      </property>
      <!--
      <property>
        <name>dfs.datanode.hostname</name>
        <value>{{ .Values.hdfs.dataNode.externalHostname }}</value>
      </property>
      -->
      <property>
        <name>dfs.namenode.datanode.registration.ip-hostname-check</name>
        <value>false</value>
      </property>
      <property>
        <name>dfs.datanode.http.address</name>
        <value>0.0.0.0:9864</value>
      </property>
      <property>
        <name>dfs.datanode.address</name>
        <value>0.0.0.0:9866</value>
      </property>
      <property>
        <name>dfs.replication</name>
          <value>3</value>
      </property>
      <property>
        <name>dfs.datanode.data.dir</name>
        <value>/opt/apache/hadoop/data/hdfs/datanode/data1,/opt/apache/hadoop/data/hdfs/datanode/data2,/opt/apache/hadoop/data/hdfs/datanode/data3</value>
        <description>DataNode directory</description>
      </property>
      <property>
        <name>dfs.namenode.name.dir</name>
        <value>/opt/apache/hadoop/data/hdfs/namenode</value>
        <description>NameNode directory for namespace and transaction logs storage.</description>
      </property>
      <property>
        <name>dfs.namenode.datanode.registration.ip-hostname-check</name>
        <value>false</value>
      </property>
      <!-- Bind to all interfaces -->
      <property>
        <name>dfs.namenode.rpc-bind-host</name>
        <value>0.0.0.0</value>
      </property>
      <property>
        <name>dfs.namenode.servicerpc-bind-host</name>
        <value>0.0.0.0</value>
      </property>
      <!-- /Bind to all interfaces -->
    </configuration>
  mapred-site.xml: |
    <?xml version="1.0"?>
    <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
    <configuration>
      <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
      </property>
      <property>
        <name>mapreduce.jobhistory.address</name>
        <value>{{ include "hadoop.fullname" . }}-mr-historyserver-0:10020</value>
      </property>
      <property>
        <name>mapreduce.jobhistory.webapp.address</name>
        <value>{{ include "hadoop.fullname" . }}-mr-historyserver-0:{{ .Values.service.mrHistoryserver.ports.web }}</value>
      </property>
    </configuration>
  yarn-site.xml: |
    <?xml version="1.0"?>
    <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
    <configuration>
      <property>
        <name>yarn.resourcemanager.hostname</name>
        <value>{{ include "hadoop.fullname" . }}-yarn-rm-headless</value>
      </property>
      <!-- Bind to all interfaces -->
      <property>
        <name>yarn.resourcemanager.bind-host</name>
        <value>0.0.0.0</value>
      </property>
      <property>
        <name>yarn.nodemanager.bind-host</name>
        <value>0.0.0.0</value>
      </property>
      <property>
        <name>yarn.timeline-service.bind-host</name>
        <value>0.0.0.0</value>
      </property>
      <!-- /Bind to all interfaces -->
      <property>
        <name>yarn.nodemanager.vmem-check-enabled</name>
        <value>false</value>
      </property>
      <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
      </property>
      <property>
        <name>yarn.nodemanager.aux-services.mapreduce_shuffle.class</name>
        <value>org.apache.hadoop.mapred.ShuffleHandler</value>
      </property>
      <property>
        <description>List of directories to store localized files in.</description>
        <name>yarn.nodemanager.local-dirs</name>
        <value>/opt/apache/hadoop/data/yarn/local-dirs</value>
      </property>
      <property>
        <description>Where to store container logs.</description>
        <name>yarn.nodemanager.log-dirs</name>
        <value>/opt/apache/hadoop/data/yarn/log-dirs</value>
      </property>
      <property>
        <description>Where to aggregate logs to.</description>
        <name>yarn.nodemanager.remote-app-log-dir</name>
        <value>/opt/apache/hadoop/data/yarn/apps</value>
      </property>
      <property>
        <name>yarn.web-proxy.address</name>
        <value>{{ include "hadoop.fullname" . }}-yarn-proxyserver-0:{{ .Values.service.proxyServer.ports.web }}</value>
      </property>
      <property>
        <name>yarn.application.classpath</name>
        <value>
          /opt/apache/hadoop/etc/hadoop,
          /opt/apache/hadoop/share/hadoop/common/*,
          /opt/apache/hadoop/share/hadoop/common/lib/*,
          /opt/apache/hadoop/share/hadoop/hdfs/*,
          /opt/apache/hadoop/share/hadoop/hdfs/lib/*,
          /opt/apache/hadoop/share/hadoop/mapreduce/*,
          /opt/apache/hadoop/share/hadoop/mapreduce/lib/*,
          /opt/apache/hadoop/share/hadoop/yarn/*,
          /opt/apache/hadoop/share/hadoop/yarn/lib/*
        </value>
      </property>
    </configuration>
  dfs-hosts.includes: |
    {{ include "hadoop.fullname" . }}-hdfs-dn-0.{{ include "hadoop.fullname" . }}-hdfs-dn.{{ .Release.Namespace }}.svc.cluster.local
    {{ include "hadoop.fullname" . }}-hdfs-dn-1.{{ include "hadoop.fullname" . }}-hdfs-dn.{{ .Release.Namespace }}.svc.cluster.local
    {{ include "hadoop.fullname" . }}-hdfs-dn-2.{{ include "hadoop.fullname" . }}-hdfs-dn.{{ .Release.Namespace }}.svc.cluster.local
  dfs-hosts.excludes: |
  yarn-hosts.includes: |
    {{ include "hadoop.fullname" . }}-yarn-nm-0.{{ include "hadoop.fullname" . }}-yarn-nm.{{ .Release.Namespace }}.svc.cluster.local
    {{ include "hadoop.fullname" . }}-yarn-nm-1.{{ include "hadoop.fullname" . }}-yarn-nm.{{ .Release.Namespace }}.svc.cluster.local
    {{ include "hadoop.fullname" . }}-yarn-nm-2.{{ include "hadoop.fullname" . }}-yarn-nm.{{ .Release.Namespace }}.svc.cluster.local
  yarn-hosts.excludes: |

4）hive configmap yaml

apiVersion: v1
kind: ConfigMap
metadata:
  name: {{ include "hadoop.fullname" . }}-hive
  labels:
    app.kubernetes.io/name: {{ include "hadoop.name" . }}
    helm.sh/chart: {{ include "hadoop.chart" . }}
    app.kubernetes.io/instance: {{ .Release.Name }}-hive
data:
  hive-site.xml: |
    <?xml version="1.0"?>
    <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
    <configuration>
        <!-- 装备hdfs存储目录 -->
        <property>
                <name>hive.metastore.warehouse.dir</name>
                <value>/user/hive_remote/warehouse</value>
        </property>
        <property>
                <name>hive.metastore.local</name>
                <value>false</value>
        </property>
        <!-- 所连接的 MySQL 数据库的地址，hive_local是数据库，程序会主动创立，自定义就行 -->
        <property>
                <name>javax.jdo.option.ConnectionURL</name>
                <value>jdbc:mysql://192.168.182.110:13306/hive_metastore?createDatabaseIfNotExist=true&amp;useSSL=false&amp;serverTimezone=Asia/Shanghai</value>
        </property>
        <!-- MySQL 驱动 -->
        <property>
                <name>javax.jdo.option.ConnectionDriverName</name>
                <!--<value>com.mysql.cj.jdbc.Driver</value>-->
                <value>com.mysql.jdbc.Driver</value>
        </property>
        <!-- mysql连接用户 -->
        <property>
                <name>javax.jdo.option.ConnectionUserName</name>
                <value>root</value>
        </property>
        <!-- mysql连接暗码 -->
        <property>
                <name>javax.jdo.option.ConnectionPassword</name>
                <value>123456</value>
        </property>
        <!--元数据是否校验-->
        <property>
                <name>hive.metastore.schema.verification</name>
                <value>false</value>
        </property>
        <property>
                <name>system:user.name</name>
                <value>root</value>
                <description>user name</description>
        </property>
        <property>
                <name>hive.metastore.uris</name>
                <value>thrift://{{ include "hadoop.fullname" . }}-hive-metastore-0.{{ include "hadoop.fullname" . }}-hive-metastore:{{ .Values.service.hive.metastore.port }}</value>
        </property>
        <!-- host -->
        <property>
                <name>hive.server2.thrift.bind.host</name>
                <value>0.0.0.0</value>
                <description>Bind host on which to run the HiveServer2 Thrift service.</description>
        </property>
        <!-- hs2端口 默许是10000-->
        <property>
                <name>hive.server2.thrift.port</name>
                <value>{{ .Values.service.hive.hiveserver2.port }}</value>
        </property>
        <property>
                <name>hive.server2.active.passive.ha.enable</name>
                <value>true</value>
        </property>
    </configuration>

【温馨提示】这儿仅仅列举出重要的装备和脚本。文末会供给git 下载地址，下载整个布置包。

5）开端装置

cd hadoop-on-kubernetes
# 装置
helm install hadoop ./ -n hadoop --create-namespace
# 更新
helm upgrade hadoop ./ -n hadoop
# 卸载
helm uninstall hadoop -n hadoop

6）测试验证

hdfs web：http://ip:30870

yarn web：http://ip:

经过 hive 创立库表和增加数据验证集群可用性

kubectl exec -it hadoop-hadoop-hive-hiveserver2-0 -n hadoop -- bash
beeline -u jdbc:hive2://hadoop-hadoop-hive-hiveserver2:10000  -n hadoop
# 建表
CREATE TABLE mytable (
  id INT,
  name STRING,
  age INT,
  address STRING
)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
LINES TERMINATED BY '\n';
# 增加数据
INSERT INTO mytable VALUES (1, 'Alice', 25, 'F'), (2, 'Bob', 30, 'M'), (3, 'Charlie', 35, 'M');

hadoop-on-kubernetes下载地址：gitee.com/hadoop-bigd…，后面会单独拿一篇文章来讲解布置时需求修正的当地和注意事项。

Hadoop on k8s 编列布置进阶篇就到这儿了，有任何疑问请关注我大众号：大数据与云原生技能分享，进行技能交流，如本篇文章对您有所帮助，麻烦帮忙一键三连（点赞、转发、收藏）~

Hadoop on k8s 编排部署进阶篇

一、概述

二、k8s 布置布置

三、开端编列布置 Hadoop

1）构建镜像 Dockerfile

2）values.yaml 文件装备

3）hadoop configmap yaml

4）hive configmap yaml

5）开端装置

6）测试验证

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