Spark 2.3.4 StandAlone 集群模式部署

Spark 2.3.4 StandAlone 集群模式部署

  • 相关文档
  • 依赖服务
  • 系统优化
  • 创建路径
  • 配置 /etc/profile
  • 配置 $SPARK_HOME/conf/spark-env.sh
  • 配置 $SPARK_HOME/conf/spark-defaults.conf
  • 配置 $SPARK_HOME/conf/slaves
  • 分发配置
  • 启动 Spark
  • 验证 Spark

相关文档

介质路径：https://archive.apache.org/dist/spark/

  • 部署文档：https://spark.apache.org/docs/latest/spark-standalone.html

依赖服务

  • JDK 1.8.0_333

  • ZooKeeper 3.5.10：https://blog.csdn.net/weixin_42598916/article/details/135726572?spm=1001.2014.3001.5502

  • Hadoop 3.1.1：https://blog.csdn.net/weixin_42598916/article/details/135726131?spm=1001.2014.3001.5502

  • Scala 2.13.1

系统优化

  • 每个节点都需进行如下优化
# 按需求更改主机名
hostname hadoop1

# 关闭 SELinux
# 将 SELINUX 值更改为 disabled
vi /etc/selinux/config
SELINUX=disabled

# 需要重启后才可生效
# 查看 SELinux 状态
getenforce

# 关闭防火墙
systemctl stop firewalld && systemctl disable firewalld && systemctl status firewalld

# 安装 Chrony 服务
yum install chrony -y

# 配置 Chrony 服务
# 注释默认的 NTP 服务地址
# 配置所需的 NTP 服务地址
vi /etc/chonry.conf
server hadoop1 iburst

# 重启 Chrony 服务并配置开机自启
systemctl enable chronyd --now

# 查看 Chrony 服务状态
chronyc sources -v
210 Number of sources = 1
.-- Source mode  '^' = server, '=' = peer, '#' = local clock.
/ .- Source state '*' = current synced, '+' = combined , '-' = not combined,
| /   '?' = unreachable, 'x' = time may be in error, '~' = time too variable.
||                                                 .- xxxx [ yyyy ] +/- zzzz
||      Reachability register (octal) -.           |  xxxx = adjusted offset,
||      Log2(Polling interval) --.      |          |  yyyy = measured offset,
||                                     |          |  zzzz = estimated error.
||                                 |    |         
MS Name/IP address         Stratum Poll Reach LastRx Last sample
====================================================================================================================
^* hadoop1                        4   6   377    12    -28us[  -45us] +/-   75ms

# 配置免密登录
# 所有节点生成 id_rsa.pub
ssh-keygen -t rsa

# 将每个节点的 id_rsa.pub 信息，分别放入所有节点的 authorized_keys 文件内
cat id_rsa.pub >> hadoop1:/root/.ssh/authorized_keys
cat id_rsa.pub >> hadoop2:/root/.ssh/authorized_keys
cat id_rsa.pub >> hadoop3:/root/.ssh/authorized_keys

# 最终效果
cat /root/.ssh/authorized_keys
# redis-nodes
ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDwuKw9LdfDO3Ln+ViNtQEqZtH/RvoFymKkexBXRUK/2XcczKHPv967KHH71L/5vPOQPUXZLZg3TPERlRTIW9MvCh0LmceGAiQHrxczx56RnYh8nESknd2jbHBToGwqgoB8xsB2IQuhze0CqvRs7A0nrbyBvnUpg/DvePTOSSgii4z9kishBCbrCPamQm20drXVDK3gQ9Q+/YJLKa3+mxzI67xfk/jby0A0DD9XKL7fflRgMK0GXEtYsJ04tKc5Bo+w6Zc8gHyryFrKD4wpeoPakqmrdzaTVYI1x5WvrAPrQplxAP8iNfBqRJSHvlDBXVeXgSxz2I4HBshsStkKp root@redis1
ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDkspWeTwWoWyr6biMnefOYT4kh+7gPAboHAWe7p67IR9pfu+Rkk/vxLFDbi7X6Td9AhIXEZH6fY5BhihBzhRO/VtjE24QqnXdOLDHV1i0rSEYh6GOAbnVl/93lKidQF/2wvnQET31m1iwls3ul6aWw8/pOcxWy6kB+6MRiOExhu+0erE3jBFLcl+e0IJLKp/nLjCof/qWh3hLGVyhgMn/WmGhf7OyUbedXFqAwwS83/M60jSL1nB1lnIOoHrNSdnrN/GJVXmmwJjJAG4g4hbAg2zNind2rz6p4mq5k7iBbDUFghFwKKYsGeV0Onm7SKErFlHCJNFSOgfVNpaUYJ root@redis2
ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQC+DGKAYw3tbdmv2GDsz3HEOdoKk8JVCEvDFczap2g3DoaqwEBkRag2l9IQ3RZL/WtpKe0f2vZzcm5t3d7e6YhyfEXRn1fjOmynTcykB13xAVrlRfJ6Sayur0OiPzWBktpNj8qaTKjwH+lyHGBwa5duqKiVEglEH2mX5grcOa/mH2Mo+IWsCYeCldKjfdBy2drlAim1fYvJwvtg0uDe8sfDUdDonG4phNOVaWB2u79SxKlGnGewGNuOrifIzkbc0mH9kNgrlw/xdSIqaFA738Yn/4n/kSe3BgceJ0wBowLzorgW2ogyGOdQp6MzBRlg/hxn4EDLJisrC9mSCMOOl root@redis3

# hadoop-nodes
ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQCvWawSJqu4/Adnu6TjvV8rVDAqTU2CGNaSBOTDjcytHHOaY8UiwUMKvXUJugBmRkyhtWhQPHrVSmOH6+qMnHk5XQcWBmce8qCQqDoz49WwyZH95ciY/ynKR9dzAJwXN5fvJEoKxBhSJLk27SDsgRUX05IAjTN5Wx05GCNC36CRGHr6bwsC5iK+nv1ZllkRPyqoICJcvVVoJFDe+svNwLJS8bEpTUS/3C6w1RdfEgGVK0/NLnmANz6VIu5LAZqOpwFcB8Zed3wgnoHUfDCSXLEUQbcgRxDvba7lcvOqbiNh4Tr6WctSHw0UD9PSK6AXdS0jAAyjZ1J5kbWaI+vmZ root@hadoop1
ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQCwCqgQWDgw7sSqNer1oONzsFhoCWBmLqdWOQCcC7RYhD6kiVzdAEP7qZwWKRwoe/E++xP0+slgxsIsXGVoObGrlT3n+g/2xsgTCaBT/6sGV7k28UOozh76GlyfJjzavbwWE9Q2yR2mkb3/ILGE6CUNCkqqLuYEDTG4DxNupGhsGSYChAcjclzYFrMxDARiOJ8cahDjVlmGzFWxNhzJ36pFC1Rdyeu4CrtZ8tkuqQagGZqB63bVmvTiOM2fY8Wp8TNv0Zz2XmFmv7IUhpDXlPZdFCviwLYLLoJ9LTG32rO/jY0U78LFdDpsYdebthztNakKMZEhCqVIR+k1VMPtp root@hadoop2
ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDHmj5qT64jSc3LCR2EBKB+12C1XxhFlc44X8zdf3mL8gbepG+ndMgBV4eombLg7QjZshCsjhk9d8esofAlrPk5tX/nWWHg3p5jYTh5/6V+iU7VDpWmMVN/87dsjBbmM9P6jTNiwqk4rdSXDKXkmrVygGHnEj95eP35Nq1JKg+GS7RjWWB0+loGQ4eYKO1nj2nYNOlNBi28CKh1uMWf42bDtcfKP3Z4gEOtPBD5rVPiU2Tq6jgtAs/VvaYGv5FHO4MB0lBE1ik8zp/4trfGU5hie/1PzCRAIvsqPEBSzeUs9nhHODj6vZYwgQupK9Qv5jEbQgh6pCGEfFZlfsC03 root@hadoop3

# 配置 OracleJDK
# 下载 Oracle JDK 并存放至指定路径内
# 配置 /etc/profile 文件
cat > /etc/profile << EOF

# Oracle JDK 1.8.0_333
export JAVA_HOME=/data/service/jdk/jdk1.8.0_333
export CLASSPATH=$:CLASSPATH:$JAVA_HOME/lib/
export PATH=$PATH:$JAVA_HOME/bin
EOF

# 刷新配置
source /etc/profile

# 查看 JDK 状态
java -version
java version "1.8.0_333"
Java(TM) SE Runtime Environment (build 1.8.0_333-b02)
Java HotSpot(TM) 64-Bit Server VM (build 25.333-b02, mixed mode)

# 配置 HOSTS 文件
cat > /etc/hosts << EOF
# redis-nodes
10.10.10.21 redis1
10.10.10.22 redis2
10.10.10.23 redis3

# hadoop-nodes
10.10.10.131 hadoop1
10.10.10.132 hadoop2
10.10.10.133 hadoop3
EOF

# 关闭 swap
swapoff -a

# 注销 swap 分区挂载
vi /etc/fstab
# 配置 vm.swapiness
echo "vm.swappiness = 0" >> /etc/sysctl.conf

# 刷新配置
sysctl -p

# 配置 transparent_hugepage
# 临时生效
echo never > /sys/kernel/mm/transparent_hugepage/enabled && echo never > /sys/kernel/mm/transparent_hugepage/defrag

# 永久生效
echo "echo never > /sys/kernel/mm/transparent_hugepage/enabled" >> /etc/rc.local && echo "echo never > /sys/kernel/mm/transparent_hugepage/defrag" >> /etc/rc.local

# 配置 最大连接数
# CentOS6 的文件名为 90-nproc.conf
# CentOS7 的文件名为 20-nproc.conf
vi /etc/security/limits.d/20-nproc.conf
* - nofile 655350
* - nproc 655350

创建路径

mkdir -p /data/service/spark/{spark_data1,spark_data2,spark_logs,spark_tmp}

配置 /etc/profile

# Spark 2.3.4
export SPARK_HOME=/data/service/spark/spark-2.3.4-bin-hadoop2.7
export PATH=$PATH:$SPARK_HOME/bin:$SPARK_HOME/sbin:$SPARK_HOME/lib

配置 $SPARK_HOME/conf/spark-env.sh

  • 将 $SPARK_HOME/conf/spark-env.sh.template 更改为 $SPARK_HOME/conf/spark-env.sh
# 指定相关服务路径
export JAVA_HOME=/data/service/jdk/jdk1.8.0_333
export SCALA_HOME=/data/service/scala/scala-2.13.1
export HADOOP_HOME=/data/service/hadoop/hadoop-3.1.1
export HADOOP_CONF_DIR=/data/service/hadoop/hadoop-3.1.1/etc/hadoop

# 指定 Spark 数据路径
export SPARK_LOG_DIR="/data/service/spark/spark_logs"
export SPARK_PID_DIR=/data/service/spark/spark_tmp
export SPARK_LOCAL_DIRS=/data/service/spark/spark_data1,/data/service/spark/spark_data2

# 指定 Master 配置
export SPARK_MASTER_HOST=redis1
export SPARK_MASTER_PORT=7077
export SPARK_MASTER_WEBUI_PORT=8080

# 指定 WORK 配置
export SPARK_WORKER_CORES=2
export SPARK_WORKER_MEMORY=4g
export SPARK_WORKER_INSTANCES=1

# 指定所有角色 JVM 大小
# 无法指定某一个角色的大小
exporter SPARK_DAEMON_MEMORY=512m

# 开启 Master HA 模式
export SPARK_DAEMON_JAVA_OPTS="$SPARK_DAEMON_JAVA_OPTS -Dspark.deploy.recoveryMode=ZOOKEEPER -Dspark.deploy.zookeeper.url=hadoop1:2181,hadoop2:2181,hadoop3:2181"

配置 $SPARK_HOME/conf/spark-defaults.conf

  • 将 $SPARK_HOME/conf/spark-defaults.conf.template 更改为 $SPARK_HOME/conf/spark-defaults.conf
spark.eventLog.enabled true
spark.eventLog.dir hdfs://hdfscluster/spark_history_logs
spark.history.fs.logDirectory hdfs://hdfscluster/spark_history_logs
spark.history.retainedApplications 5

配置 $SPARK_HOME/conf/slaves

redis1
redis2
redis3

分发配置

  • 将 /data/service/spark 分发至所有节点

  • Master-backup 节点调整 $SPARK_HOME/conf/spark-env.sh

export SPARK_MASTER_HOST=redis2

启动 Spark

  • Master-master
$SPARK_HOME/sbin/start-all.sh
$SPARK_HOME/sbin/start-history-server.sh
  • Master-backup
$SPARK_HOME/sbin/start-master.sh

验证 Spark

  • Spark Web UI：http://10.10.10.21:8080

  • Spark HistoryServer Web UI：http://10.10.10.21:18080