docker镜像制作之dockercompose.yml文件---hadoop伪分布式

来源：互联网发布：淘宝一件代发怎么加入编辑：程序博客网时间：2024/06/08 15:19

一、其实对于hadoop集群不是太适合放在docker服务器里面来跑，因为docker提倡容器和服务是1:1的关系，但是

hadoop提倡datanode和nodemanager在一个节点上（容器），但是当docker使用swarm之后，还是可以考虑将hadoop

集群的各个服务扔进容器里面。

二、构建hadoop集群的基础镜像

1.构建hadoop集群的基础镜像需要如下文件：

├── build.sh
├── Dockerfile
├── entrypoint.sh
├── hadoop-2.7.3.tar.gz
└── jdk-8u92-linux-x64.tar.gz

2.说明：hadoop-2.7.3.tar.gz和jdk-8u92-linux-x64.tar.gz需要提前下载后放在该目录下

3.Dockerfile文件的内容如下

FROM debian:jessie-backportsRUN apt-get update \    #&& DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends openjdk-8-jdk \    && rm -rf /var/lib/apt/lists/*ENV  JAVA_VERSION jdk1.8.0_92COPY jdk-8u92-linux-x64.tar.gz /optRUN  tar -zxvf /opt/jdk-8u92-linux-x64.tar.gz -C /optENV JAVA_HOME=/opt/$JAVA_VERSION/RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends net-tools curlRUN gpg --keyserver pool.sks-keyservers.net --recv-keys \    07617D4968B34D8F13D56E20BE5AAA0BA210C095 \    2CAC83124870D88586166115220F69801F27E622 \    4B96409A098DBD511DF2BC18DBAF69BEA7239D59 \    9DD955653083EFED6171256408458C39E964B5FF \    B6B3F7EDA5BA7D1E827DE5180DFF492D8EE2F25C \    6A67379BEFC1AE4D5595770A34005598B8F47547 \    47660BC98BC433F01E5C90581209E7F13D0C92B9 \    CE83449FDC6DACF9D24174DCD1F99F6EE3CD2163 \    A11DF05DEA40DA19CE4B43C01214CF3F852ADB85 \    686E5EDF04A4830554160910DF0F5BBC30CD0996 \    5BAE7CB144D05AD1BB1C47C75C6CC6EFABE49180 \    AF7610D2E378B33AB026D7574FB955854318F669 \    6AE70A2A38F466A5D683F939255ADF56C36C5F0F \    70F7AB3B62257ABFBD0618D79FDB12767CC7352A \    842AAB2D0BC5415B4E19D429A342433A56D8D31A \    1B5D384B734F368052862EB55E43CAB9AEC77EAF \    785436A782586B71829C67A04169AA27ECB31663 \    5E49DA09E2EC9950733A4FF48F1895E97869A2FB \    A13B3869454536F1852C17D0477E02D33DD51430 \    A6220FFCC86FE81CE5AAC880E3814B59E4E11856 \    EFE2E7C571309FE00BEBA78D5E314EEF7340E1CB \    EB34498A9261F343F09F60E0A9510905F0B000F0 \    3442A6594268AC7B88F5C1D25104A731B021B57F \    6E83C32562C909D289E6C3D98B25B9B71EFF7770 \    E9216532BF11728C86A11E3132CF4BF4E72E74D3 \ E8966520DA24E9642E119A5F13971DA39475BD5D \    1D369094D4CFAC140E0EF05E992230B1EB8C6EFA \    A312CE6A1FA98892CB2C44EBA79AB712DE5868E6 \    0445B7BFC4515847C157ECD16BA72FF1C99785DE \    B74F188889D159F3D7E64A7F348C6D7A0DCED714 \    4A6AC5C675B6155682729C9E08D51A0A7501105C \    8B44A05C308955D191956559A5CEE20A90348D47ENV HADOOP_VERSION 2.7.3COPY hadoop-$HADOOP_VERSION.tar.gz /optRUN  tar  -zxvf /opt/hadoop-$HADOOP_VERSION.tar.gz -C /optRUN  rm /opt/hadoop-$HADOOP_VERSION.tar.gzRUN ln -s /opt/hadoop-$HADOOP_VERSION/etc/hadoop /etc/hadoopRUN cp /etc/hadoop/mapred-site.xml.template /etc/hadoop/mapred-site.xmlRUN mkdir /opt/hadoop-$HADOOP_VERSION/logsRUN mkdir /hadoop-dataENV HADOOP_PREFIX=/opt/hadoop-$HADOOP_VERSIONENV HADOOP_CONF_DIR=/etc/hadoopENV MULTIHOMED_NETWORK=1ENV USER=rootENV PATH $HADOOP_PREFIX/bin/:$PATHADD entrypoint.sh /entrypoint.shRUN chmod a+x /entrypoint.shENTRYPOINT ["/entrypoint.sh"]

4.entrypoint.sh文件内容如下

#!/bin/bash# Set some sensible defaultsexport CORE_CONF_fs_defaultFS=${CORE_CONF_fs_defaultFS:-hdfs://`hostname -f`:9000}function addProperty() {  local path=$1  local name=$2  local value=$3  local entry="<property><name>$name</name><value>${value}</value></property>"  local escapedEntry=$(echo $entry | sed 's/\//\\\//g')  sed -i "/<\/configuration>/ s/.*/${escapedEntry}\n&/" $path}function configure() {    local path=$1    local module=$2    local envPrefix=$3    local var    local value    echo "Configuring $module"    for c in `printenv | perl -sne 'print "$1 " if m/^${envPrefix}_(.+?)=.*/' -- -envPrefix=$envPrefix`; do        name=`echo ${c} | perl -pe 's/___/-/g; s/__/_/g; s/_/./g'`        var="${envPrefix}_${c}"        value=${!var}        echo " - Setting $name=$value"        addProperty /etc/hadoop/$module-site.xml $name "$value"    done}configure /etc/hadoop/core-site.xml core CORE_CONFconfigure /etc/hadoop/hdfs-site.xml hdfs HDFS_CONFconfigure /etc/hadoop/yarn-site.xml yarn YARN_CONFconfigure /etc/hadoop/httpfs-site.xml httpfs HTTPFS_CONFconfigure /etc/hadoop/kms-site.xml kms KMS_CONFif [ "$MULTIHOMED_NETWORK" = "1" ]; then    echo "Configuring for multihomed network"    # HDFS    addProperty /etc/hadoop/hdfs-site.xml dfs.namenode.rpc-bind-host 0.0.0.0    addProperty /etc/hadoop/hdfs-site.xml dfs.namenode.servicerpc-bind-host 0.0.0.0    addProperty /etc/hadoop/hdfs-site.xml dfs.namenode.http-bind-host 0.0.0.0    addProperty /etc/hadoop/hdfs-site.xml dfs.namenode.https-bind-host 0.0.0.0    addProperty /etc/hadoop/hdfs-site.xml dfs.client.use.datanode.hostname true    addProperty /etc/hadoop/hdfs-site.xml dfs.datanode.use.datanode.hostname true    # YARN    addProperty /etc/hadoop/yarn-site.xml yarn.resourcemanager.bind-host 0.0.0.0    addProperty /etc/hadoop/yarn-site.xml yarn.nodemanager.bind-host 0.0.0.0    addProperty /etc/hadoop/yarn-site.xml yarn.nodemanager.bind-host 0.0.0.0    addProperty /etc/hadoop/yarn-site.xml yarn.timeline-service.bind-host 0.0.0.0    # MAPRED    addProperty /etc/hadoop/mapred-site.xml yarn.nodemanager.bind-host 0.0.0.0fiif [ -n "$GANGLIA_HOST" ]; then    mv /etc/hadoop/hadoop-metrics.properties /etc/hadoop/hadoop-metrics.properties.orig    mv /etc/hadoop/hadoop-metrics2.properties /etc/hadoop/hadoop-metrics2.properties.orig    for module in mapred jvm rpc ugi; do        echo "$module.class=org.apache.hadoop.metrics.ganglia.GangliaContext31"        echo "$module.period=10"        echo "$module.servers=$GANGLIA_HOST:8649"    done > /etc/hadoop/hadoop-metrics.properties    for module in namenode datanode resourcemanager nodemanager mrappmaster jobhistoryserver; do        echo "$module.sink.ganglia.class=org.apache.hadoop.metrics2.sink.ganglia.GangliaSink31"        echo "$module.sink.ganglia.period=10"        echo "$module.sink.ganglia.supportsparse=true"        echo "$module.sink.ganglia.slope=jvm.metrics.gcCount=zero,jvm.metrics.memHeapUsedM=both"        echo "$module.sink.ganglia.dmax=jvm.metrics.threadsBlocked=70,jvm.metrics.memHeapUsedM=40" done > /etc/hadoop/hadoop-metrics2.propertiesfiexec $@

5、build.sh 文件内容

#!/bin/shdocker build -t hadoop/base .

6、给build.sh文件赋予可执行权限

chmod +x build.sh

7、执行build.sh，创建hadoop集群的基础镜像

sh build.sh

三、构建hadoop集群的namenode镜像

1.构建hadoop集群的namenode镜像需要如下文件：

├── build.sh
├── Dockerfile
└── run.sh

2、Dockerfile文件的内容如下：

FROM hadoop/baseENV HDFS_CONF_dfs_namenode_name_dir=file:///hadoop/dfs/nameRUN mkdir -p /hadoop/dfs/nameVOLUME /hadoop/dfs/nameADD run.sh /run.shRUN chmod a+x /run.shCMD ["/run.sh"]

3、run,sh文件内容如下

#!/bin/bashnamedir=`echo $HDFS_CONF_dfs_namenode_name_dir | perl -pe 's#file://##'`if [ ! -d $namedir ]; then  echo "Namenode name directory not found: $namedir"  exit 2fiif [ -z "$CLUSTER_NAME" ]; then  echo "Cluster name not specified"  exit 2fiif [ "`ls -A $namedir`" == "" ]; then  echo "Formatting namenode name directory: $namedir"  $HADOOP_PREFIX/bin/hdfs --config $HADOOP_CONF_DIR namenode -format $CLUSTER_NAMEfi$HADOOP_PREFIX/bin/hdfs --config $HADOOP_CONF_DIR namenode

3、build.sh文件内容

#!/bin/shdocker build -t hadoop/namenode .

4、给build.sh文件赋予可执行权限

chmod +x build.sh

5、创建镜像

sh build.sh

四、构建hadoop集群的resourcemanager镜像

1.构建hadoop集群的resourcemanager镜像需要如下文件：

.
├── build.sh
├── Dockerfile
└── run.sh
2、Dockerfile文件内容如下

FROM hadoop/baseADD run.sh /run.shRUN chmod a+x /run.shCMD ["/run.sh"]

3、run.sh文件内容

#!/bin/bash$HADOOP_PREFIX/bin/yarn --config $HADOOP_CONF_DIR resourcemanager

4、build.sh文件内容

#!/bin/shdocker build -t hadoop/resourcemanager .

5、给build.sh文件赋予可执行权限

chmod +x build.sh

6、创建镜像

sh build.sh

五、构建hadoop集群的datanode镜像

1.构建hadoop集群的datanode镜像需要如下文件：

.
├── build.sh
├── Dockerfile
└── run.sh

2、Dockerfile文件内容

FROM hadoop/baseENV HDFS_CONF_dfs_datanode_data_dir=file:///hadoop/dfs/dataRUN mkdir -p /hadoop/dfs/dataVOLUME /hadoop/dfs/dataADD run.sh /run.shRUN chmod a+x /run.shCMD ["/run.sh"]

3、run.sh文件内容

#!/bin/bashdatadir=`echo $HDFS_CONF_dfs_datanode_data_dir | perl -pe 's#file://##'`if [ ! -d $datadir ]; then  echo "Datanode data directory not found: $dataedir"  exit 2fi$HADOOP_PREFIX/bin/hdfs --config $HADOOP_CONF_DIR datanode

4、build文件内容

#!/bin/shdocker build -t hadoop/datanode .

5、给build.sh文件赋予可执行权限

chmod +x build.sh

6、创建镜像

sh build.sh

六、构建hadoop集群的nodemanager镜像

1.构建hadoop集群的nodemanager镜像需要如下文件：

.
├── build.sh
├── Dockerfile
└── run.sh
2、Dockerfile文件内容

FROM hadoop/baseADD run.sh /run.shRUN chmod a+x /run.shCMD ["/run.sh"]

3、run.sh文件内容

#!/bin/bash$HADOOP_PREFIX/bin/yarn --config $HADOOP_CONF_DIR nodemanager

4、build.sh 文件内容

#!/bin/shdocker build -t hadoop/nodemanager .

5、给build.sh文件赋予可执行权限

chmod +x build.sh

6、创建镜像

sh build.sh

七、构建hadoop集群的historyserver镜像

1.构建hadoop集群的historyserver镜像需要如下文件：

.
├── build.sh
├── Dockerfile
└── run.sh
2、Dockerfile文件内容

FROM hadoop/baseENV YARN_CONF_yarn_timeline___service_leveldb___timeline___store_path=/hadoop/yarn/timelineRUN mkdir -p /hadoop/yarn/timelineVOLUME /hadoop/yarn/timelineADD run.sh /run.shRUN chmod a+x /run.shCMD ["/run.sh"]

3、run.sh文件内容

#!/bin/bash$HADOOP_PREFIX/bin/yarn --config $HADOOP_CONF_DIR historyserver

4、build.sh文件内容

#!/bin/shdocker build -t hadoop/historyserver .

5、给build.sh文件赋予可执行权限

chmod +x build.sh

6、创建镜像

sh build.sh

八、通过docker-compose编排hadoop集群

1.编排hadoop集群镜像需要如下文件：

.
├── docker-compose.yml
└── hadoop.env
2、docker-compose.yml文件内筒如下

version: '2'services:  namenode:    image: hadoop/namenode    container_name: namenode    hostname: namenode    networks:      - hadoop    volumes:      - hadoop_namenode:/hadoop/dfs/name    environment:      CLUSTER_NAME: my-cluster    env_file:      - ./hadoop.env  resourcemanager:    image: hadoop/resourcemanager    container_name: resourcemanager        hostname: resourcemanager    depends_on:      - namenode    networks:      - hadoop    env_file:      - ./hadoop.env  historyserver:    image: hadoop/historyserver    container_name: historyserver        hostname: historyserver    depends_on:      - namenode    networks:      - hadoop    volumes:      - hadoop_historyserver:/hadoop/yarn/timeline    env_file:      - ./hadoop.env    nodemanager1:    image: hadoop/nodemanager    container_name: nodemanager1    hostname: nodemanager1    depends_on:      - namenode      - resourcemanager    networks:      - hadoop    env_file:      - ./hadoop.env  datanode1:    image: hadoop/datanode    container_name: datanode1        hostname: datanode1    depends_on:      - namenode    networks:      - hadoop    volumes:      - hadoop_datanode1:/hadoop/dfs/data    env_file:      - ./hadoop.envnetworks:  hadoop:    external: truevolumes:  hadoop_namenode:    external: true      hadoop_datanode1:    external: true  hadoop_historyserver:    external: true

3、hadoop.env文件内容

#GANGLIA_HOST=ganglia.hadoopCORE_CONF_fs_defaultFS=hdfs://namenode.hadoop:8020#CORE_CONF_hadoop_http_staticuser_user=rootYARN_CONF_yarn_resourcemanager_hostname=resourcemanager.hadoopYARN_CONF_yarn_nodemanager_aux___services=mapreduce_shuffle#YARN_CONF_yarn_log___aggregation___enable=true#YARN_CONF_yarn_resourcemanager_recovery_enabled=true#YARN_CONF_yarn_resourcemanager_store_class=org.apache.hadoop.yarn.server.resourcemanager.recovery.FileSystemRMStateStore#YARN_CONF_yarn_resourcemanager_fs_state___store_uri=/rmstate#YARN_CONF_yarn_nodemanager_remote___app___log___dir=/app-logs#YARN_CONF_yarn_log_server_url=http://historyserver.hadoop:8188/applicationhistory/logs/#YARN_CONF_yarn_timeline___service_enabled=true#YARN_CONF_yarn_timeline___service_generic___application___history_enabled=true#YARN_CONF_yarn_resourcemanager_system___metrics___publisher_enabled=trueYARN_CONF_yarn_resourcemanager_hostname=resourcemanager.hadoopYARN_CONF_yarn_timeline___service_hostname=historyserver.hadoopHDFS_CONF_dfs_namenode_secondary_http___address=namenode.hadoop:50090HDFS_CONF_dfs_replication=2

4、执行如下命令

docker-compose up

5、通过docker ps查看集群镜像启动结果

docker@dockertest2:~/nopublicimage/hadoop_compose$ docker psCONTAINER ID        IMAGE                    COMMAND                  CREATED             STATUS              PORTS               NAMESe1eba51e4459        hadoop/nodemanager       "/entrypoint.sh /run."   43 minutes ago      Up 43 minutes                           nodemanager1e7c7ece55ee6        hadoop/resourcemanager   "/entrypoint.sh /run."   43 minutes ago      Up 43 minutes                           resourcemanagereb13c1a60c81        hadoop/datanode          "/entrypoint.sh /run."   43 minutes ago      Up 43 minutes                           datanode1583f5fe27119        hadoop/historyserver     "/entrypoint.sh /run."   43 minutes ago      Up 43 minutes                           historyserver3dfc276dafdf        hadoop/namenode          "/entrypoint.sh /run."   43 minutes ago      Up 43 minutes                           namenode831b00a867f7        aaef3f5ef5d4             "/bin/sh -c 'apt-get "   About an hour ago   Up About an hour                        gigantic_minsky

6、通过docker exec -ti namenode 进入容器查看集群是否正常启动

docker@dockertest2:~/nopublicimage/hadoop_compose$ docker exec -ti namenode /bin/bashroot@namenode:/# hdfs dfsadmin -reportConfigured Capacity: 29458821120 (27.44 GB)Present Capacity: 5402902528 (5.03 GB)DFS Remaining: 5402873856 (5.03 GB)DFS Used: 28672 (28 KB)DFS Used%: 0.00%Under replicated blocks: 0Blocks with corrupt replicas: 0Missing blocks: 0Missing blocks (with replication factor 1): 0-------------------------------------------------Live datanodes (1):Name: 172.19.0.5:50010 (datanode1.hadoop)Hostname: datanode1Decommission Status : NormalConfigured Capacity: 29458821120 (27.44 GB)DFS Used: 28672 (28 KB)Non DFS Used: 24055918592 (22.40 GB)DFS Remaining: 5402873856 (5.03 GB)DFS Used%: 0.00%DFS Remaining%: 18.34%Configured Cache Capacity: 0 (0 B)Cache Used: 0 (0 B)Cache Remaining: 0 (0 B)Cache Used%: 100.00%Cache Remaining%: 0.00%Xceivers: 1Last contact: Sat Oct 29 01:50:53 UTC 2016

九、实验结束

八、通过docker-compose编排hadoop集群

0 0