搭建docker-spark-hadoop-hive-zeppelin分布式集群环境
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一、软件准备
1、基础docker镜像：ubuntu，目前最新的版本是18
2、需准备的环境软件包：
(1) spark-2.3.0-bin-hadoop2.7.tgz
(2) hadoop-2.7.3.tar.gz
(3) apache-hive-2.3.2-bin.tar.gz
(4) jdk-8u101-linux-x64.tar.gz
(5) mysql-5.5.45-linux2.6-x86_64.tar.gz、mysql-connector-java-5.1.37-bin.jar
(6) scala-2.11.8.tgz
(7) zeppelin-0.8.0-bin-all.tgz
二、ubuntu镜像准备
1、获取官方的镜像：
docker pull ubuntu
2、因官方镜像中的apt源是国外资源，后续扩展安装软件包时较麻烦。先修改为国内源：
（1）启动ubuntu容器，并进入容器中的apt配置目录
docker run -it -d ubuntu
docker exec -it ubuntu /bin/bash
cd /etc/apt
（2）先将原有的源文件备份：
mv sources.list sources.list.bak
（3）换为国内源，这里提供阿里的资源。因官方的ubuntu没有艰装vi等软件，使用echo指令写入。需注意一点，资源必须与系统版本匹配。
echo deb http://mirrors.aliyun.com/ubuntu/ bionic main restricted universe multiverse >> sources.list echo deb http://mirrors.aliyun.com/ubuntu/ bionic-security main restricted universe multiverse >> sources.list echo deb http://mirrors.aliyun.com/ubuntu/ bionic-updates main restricted universe multiverse >> sources.list echo deb http://mirrors.aliyun.com/ubuntu/ bionic-proposed main restricted universe multiverse >> sources.list echo deb http://mirrors.aliyun.com/ubuntu/ bionic-backports main restricted universe multiverse >> sources.list echo deb-src http://mirrors.aliyun.com/ubuntu/ bionic main restricted universe multiverse >> sources.list echo deb-src http://mirrors.aliyun.com/ubuntu/ bionic-security main restricted universe multiverse >> sources.list echo deb-src http://mirrors.aliyun.com/ubuntu/ bionic-updates main restricted universe multiverse >> sources.list echo deb-src http://mirrors.aliyun.com/ubuntu/ bionic-proposed main restricted universe multiverse >> sources.list echo deb-src http://mirrors.aliyun.com/ubuntu/ bionic-backports main restricted universe multiverse >> sources.list
3、退出容器，提交镜像
exit docker commit 容器id ubuntu:latest
生成的ubuntu镜像，就可以做为基础镜像使用。
三、spark-hadoop集群配置
先前所准备的一列系软件包，在构建镜像时，直接用RUN ADD指令添加到镜像中，这里先将一些必要的配置处理好。这些配置文件，都来自于各个软件包中的conf目录下。
1、Spark配置
（1）spark-env.sh
声明Spark需要的环境变量
SPARK_MASTER_WEBUI_PORT=8888
export SPARK_HOME=$SPARK_HOME
export HADOOP_HOME=$HADOOP_HOME
export MASTER=spark://hadoop-maste:7077
export SCALA_HOME=$SCALA_HOME
export SPARK_MASTER_HOST=hadoop-maste
export JAVA_HOME=/usr/local/jdk1.8.0_101
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
（2）spark-default.conf
关于spark的默认配置
spark.executor.memory=2G spark.driver.memory=2G spark.executor.cores=2 #spark.sql.codegen.wholeStage=false #spark.memory.offHeap.enabled=true #spark.memory.offHeap.size=4G #spark.memory.fraction=0.9 #spark.memory.storageFraction=0.01 #spark.kryoserializer.buffer.max=64m #spark.shuffle.manager=sort #spark.sql.shuffle.partitions=600 spark.speculation=true spark.speculation.interval=5000 spark.speculation.quantile=0.9 spark.speculation.multiplier=2 spark.default.parallelism=1000 spark.driver.maxResultSize=1g #spark.rdd.compress=false spark.task.maxFailures=8 spark.network.timeout=300 spark.yarn.max.executor.failures=200 spark.shuffle.service.enabled=true spark.dynamicAllocation.enabled=true spark.dynamicAllocation.minExecutors=4 spark.dynamicAllocation.maxExecutors=8 spark.dynamicAllocation.executorIdleTimeout=60 #spark.serializer=org.apache.spark.serializer.JavaSerializer #spark.sql.adaptive.enabled=true #spark.sql.adaptive.shuffle.targetPostShuffleInputSize=100000000 #spark.sql.adaptive.minNumPostShufflePartitions=1 ##for spark2.0 #spark.sql.hive.verifyPartitionPath=true #spark.sql.warehouse.dir spark.sql.warehouse.dir=/spark/warehouse
（3）节点声明文件，包括masters文件及slaves文件
主节点声明文件：masters
hadoop-maste
从节点文件：slaves
hadoop-node1
hadoop-node2
2、Hadoop配置
（1）hadoop-env.sh
声明Hadoop需要的环境变量
export JAVA_HOME=/usr/local/jdk1.8.0_101
export HADOOP_CONF_DIR=${HADOOP_CONF_DIR:-"/etc/hadoop"}
for f in $HADOOP_HOME/contrib/capacity-scheduler/*.jar; do
if [ "$HADOOP_CLASSPATH" ]; then
export HADOOP_CLASSPATH=$HADOOP_CLASSPATH:$f
else
export HADOOP_CLASSPATH=$f
fi
done
export HADOOP_OPTS="$HADOOP_OPTS -Djava.net.preferIPv4Stack=true"
export HADOOP_NAMENODE_OPTS="-Dhadoop.security.logger=${HADOOP_SECURITY_LOGGER:-INFO,RFAS} -Dhdfs.audit.logger=${HDFS_AUDIT_LOGGER:-INFO,NullAppender} $HADOOP_NAMENODE_OPTS"
export HADOOP_DATANODE_OPTS="-Dhadoop.security.logger=ERROR,RFAS $HADOOP_DATANODE_OPTS"
export HADOOP_SECONDARYNAMENODE_OPTS="-Dhadoop.security.logger=${HADOOP_SECURITY_LOGGER:-INFO,RFAS} -Dhdfs.audit.logger=${HDFS_AUDIT_LOGGER:-INFO,NullAppender} $HADOOP_SECONDARYNAMENODE_OPTS"
export HADOOP_NFS3_OPTS="$HADOOP_NFS3_OPTS"
export HADOOP_PORTMAP_OPTS="-Xmx512m $HADOOP_PORTMAP_OPTS"
export HADOOP_CLIENT_OPTS="-Xmx512m $HADOOP_CLIENT_OPTS"
export HADOOP_SECURE_DN_USER=${HADOOP_SECURE_DN_USER}
export HADOOP_SECURE_DN_LOG_DIR=${HADOOP_LOG_DIR}/${HADOOP_HDFS_USER}
export HADOOP_PID_DIR=${HADOOP_PID_DIR}
export HADOOP_SECURE_DN_PID_DIR=${HADOOP_PID_DIR}
export HADOOP_IDENT_STRING=$USER
（2）hdfs-site.xml
主要设置了Hadoop的name及data节点。name节点存储的是元数据，data存储的是数据文件
<?xml version="1.0"?> <configuration> <property> <name>dfs.namenode.name.dir</name> <value>file:/usr/local/hadoop2.7/dfs/name</value> </property> <property> <name>dfs.datanode.data.dir</name> <value>file:/usr/local/hadoop2.7/dfs/data</value> </property> <property> <name>dfs.webhdfs.enabled</name> <value>true</value> </property> <property> <name>dfs.replication</name> <value>2</value> </property> <property> <name>dfs.permissions.enabled</name> <value>false</value> </property> </configuration>
（3）core-site.xml
设置主节点的地址：hadoop-maste。与后面启动容器时，设置的主节点hostname要一致。
<?xml version="1.0"?> <configuration> <property> <name>fs.defaultFS</name> <value>hdfs://hadoop-maste:9000/</value> </property> <property> <name>hadoop.tmp.dir</name> <value>file:/usr/local/hadoop/tmp</value> </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.oozie.hosts</name> <value>*</value> </property> <property> <name>hadoop.proxyuser.oozie.groups</name> <value>*</value> </property> </configuration>
（4）yarn-site.xml
<?xml version="1.0"?> <configuration> <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> <name>yarn.resourcemanager.hostname</name> <value>hadoop-maste</value> </property> <property> <name>yarn.resourcemanager.address</name> <value>hadoop-maste:8032</value> </property> <property> <name>yarn.resourcemanager.scheduler.address</name> <value>hadoop-maste:8030</value> </property> <property> <name>yarn.resourcemanager.resource-tracker.address</name> <value>hadoop-maste:8035</value> </property> <property> <name>yarn.resourcemanager.admin.address</name> <value>hadoop-maste:8033</value> </property> <property> <name>yarn.resourcemanager.webapp.address</name> <value>hadoop-maste:8088</value> </property> <property> <name>yarn.log-aggregation-enable</name> <value>true</value> </property> <property> <name>yarn.nodemanager.vmem-pmem-ratio</name> <value>5</value> </property> <property> <name>yarn.nodemanager.resource.memory-mb</name> <value>22528</value> <discription>每个节点可用内存,单位MB</discription> </property> <property> <name>yarn.scheduler.minimum-allocation-mb</name> <value>4096</value> <discription>单个任务可申请最少内存，默认1024MB</discription> </property> <property> <name>yarn.scheduler.maximum-allocation-mb</name> <value>16384</value> <discription>单个任务可申请最大内存，默认8192MB</discription> </property> </configuration>
（5）mapred-site.xml
<?xml version="1.0"?> <configuration> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> <property> <name>mapreduce.jobhistory.address</name> <!-- 配置实际的Master主机名和端口--> <value>hadoop-maste:10020</value> </property> <property> <name>mapreduce.map.memory.mb</name> <value>4096</value> </property> <property> <name>mapreduce.reduce.memory.mb</name> <value>8192</value> </property> <property> <name>yarn.app.mapreduce.am.staging-dir</name> <value>/stage</value> </property> <property> <name>mapreduce.jobhistory.done-dir</name> <value>/mr-history/done</value> </property> <property> <name>mapreduce.jobhistory.intermediate-done-dir</name> <value>/mr-history/tmp</value> </property> </configuration>
（6）主节点声明文件：master
hadoop-maste
3、hive配置
（1）hive-site.xml
主要两个：一是hive.server2.transport.mode设为binary，使其支持JDBC连接；二是设置mysql的地址。
<?xml version="1.0" encoding="UTF-8" standalone="no"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <configuration> <property> <name>hive.metastore.warehouse.dir</name> <value>/home/hive/warehouse</value> </property> <property> <name>hive.exec.scratchdir</name> <value>/tmp/hive</value> </property> <property> <name>hive.metastore.uris</name> <value>thrift://hadoop-hive:9083</value> <description>Thrift URI for the remote metastore. Used by metastore client to connect to remote metastore.</description> </property> <property> <name>hive.server2.transport.mode</name> <value>binary</value> </property> <property> <name>hive.server2.thrift.http.port</name> <value>10001</value> </property> <property> <name>javax.jdo.option.ConnectionURL</name> <value>jdbc:mysql://hadoop-mysql:3306/hive?createDatabaseIfNotExist=true</value> </property> <property> <name>javax.jdo.option.ConnectionDriverName</name> <value>com.mysql.jdbc.Driver</value> </property> <property> <name>javax.jdo.option.ConnectionUserName</name> <value>root</value> </property> <property> <name>javax.jdo.option.ConnectionPassword</name> <value>root</value> </property> <property> <name>hive.metastore.schema.verification</name> <value>false</value> </property> <property> <name>hive.server2.authentication</name> <value>NONE</value> </property> </configuration>
4、Zeppelin配置
（1）zeppelin-env.sh
export JAVA_HOME=/usr/local/jdk1.8.0_101
export MASTER=spark://hadoop-maste:7077
export SPARK_HOME=$SPARK_HOME
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
（2）zeppelin-site.xml
http端口默认8080，这里改为18080。为方便加载第三方包，mvnRepo也改为阿里的源。
<?xml version="1.0"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration> <property> <name>zeppelin.server.addr</name> <value>0.0.0.0</value> <description>Server address</description> </property> <property> <name>zeppelin.server.port</name> <value>18080</value> <description>Server port.</description> </property> <property> <name>zeppelin.server.ssl.port</name> <value>18443</value> <description>Server ssl port. (used when ssl property is set to true)</description> </property> <property> <name>zeppelin.server.context.path</name> <value>/</value> <description>Context Path of the Web Application</description> </property> <property> <name>zeppelin.war.tempdir</name> <value>webapps</value> <description>Location of jetty temporary directory</description> </property> <property> <name>zeppelin.notebook.dir</name> <value>notebook</value> <description>path or URI for notebook persist</description> </property> <property> <name>zeppelin.notebook.homescreen以上是关于搭建docker-spark-hadoop-hive-zeppelin分布式集群环境的主要内容，如果未能解决你的问题，请参考以下文章