基础环境准备
- 安装JDK1.8+,并设置环境变量
- 搭建zookeeper集群
- 搭建Hadoop集群
Spark local模式
上传编译完成的spark安装程序到服务器上,并解压到指定目录
[root@hadoop01 soft]# tar zxvf spark-2.2.-bin-2.6.-cdh5.14.0.tgz -C /usr/local/
[root@hadoop01 soft]# cd /usr/local/
[root@hadoop01 local]# mv spark-2.2.-bin-2.6.-cdh5.14.0/ spark
[root@hadoop01 local]# cd spark/conf/
修啊改配置文件spark-env.sh.template为spark-env.sh
[root@hadoop01 conf]# mv spark-env.sh.template spark-env.sh
启动验证spark程序
[root@hadoop01 conf]# cd ../
[root@hadoop01 spark]# ./bin/spark-shell
[root@hadoop01 conf]# cd ../
[root@hadoop01 spark]# ./bin/spark-shell
退出spark命令行
scala> :quit
执行jar计算圆周率
bin/spark-submit \
--class org.apache.spark.examples.SparkPi \
--master local[] \
--executor-memory 1G \
--total-executor-cores \
/usr/local/spark/examples/jars/spark-examples_2.-2.2..jar \
spark的standAlone模式
修改配置文件spark-env.sh,添加下列内容
[root@hadoop01 conf]# vim spark-env.sh
export JAVA_HOME=/usr/local/java/jdk1..0_201
export SPARK_MASTER_HOST=node01
export SPARK_MASTER_PORT=
export SPARK_HISTORY_OPTS="-Dspark.history.ui.port=4000 -Dspark.history.retainedApplications=3 -Dspark.history.fs.logDirectory=hdfs://node01:9000/spark_log"
修改slaves文件,添加下列内容
[root@hadoop01 conf]# mv slaves.template slaves
[root@hadoop01 conf]# vim slaves
node01
node02
node03
修改配置文件spark-default.conf,添加下列内容
[root@hadoop01 conf]# mv spark-defaults.conf.template spark-defaults.conf
[root@hadoop01 conf]# vim spark-defaults.conf
spark.eventLog.enabled true
spark.eventLog.dir hdfs://node01:9000/spark_log
spark.eventLog.compress true
并在Hadoop的hdfs中创建spark日志目录spark_log
[root@hadoop01 conf]# hdfs dfs -ls /
分发配置好的spark程序到其它两台服务器上
[root@hadoop01 conf]# cd ../../
[root@hadoop01 conf]# scp -r spark root@node02:$PWD
[root@hadoop01 conf]# scp -r spark root@node03:$PWD
启动spark程序
[root@hadoop01 conf]# cd spark
[root@hadoop01 conf]# sbin/start-all.sh
[root@hadoop01 conf]# sbin/start-history-server.sh
spark的standAlone模式验证
[root@hadoop01 spark]# bin/spark-submit \
--class org.apache.spark.examples.SparkPi \
--master spark://node01:7077 \
--executor-memory 1G \
--total-executor-cores \
/usr/local/spark/examples/jars/spark-examples_2.-2.2..jar \
spark的HA高可用模式
停止启动的spark程序
[root@hadoop01 spark]# sbin/stop-all.sh
[root@hadoop01 spark]# sbin/stop-history-server.sh
解压spark程序到指定目录,并重命名为spark-HA
[root@hadoop01 soft]# tar zxvf spark-2.2.-bin-2.6.-cdh5.14.0.tgz -C /usr/local/
[root@hadoop01 soft]# cd /usr/local/
[root@hadoop01 local]# mv spark-2.2.-bin-2.6.-cdh5.14.0/ spark-HA
修改spark配置文件spark-env.sh
[root@hadoop01 local]# cd spark-HA/conf/
[root@hadoop01 conf]# mv spark-env.sh.template spark-env.sh
[root@hadoop01 conf]# vim spark-env.sh
export JAVA_HOME=/usr/local/java/jdk1..0_201
export SPARK_MASTER_PORT=
export SPARK_HISTORY_OPTS="-Dspark.history.ui.port=4000 -Dspark.history.retainedApplications=3 -Dspark.history.fs.logDirectory=hdfs://node01:9000/spark_log"
export SPARK_DAEMON_JAVA_OPTS="-Dspark.deploy.recoveryMode=ZOOKEEPER -Dspark.deploy.zookeeper.url=node01:2181,node02:2181,node03:2181 -Dspark.deploy.zookeeper.dir=/spark"
修改配置文件slave
[root@hadoop01 conf]# mv slaves.template slaves
[root@hadoop01 conf]# vim slaves
node01
node02
node03
修改配置文件spark-defaults.conf
[root@hadoop01 conf]# mv spark-defaults.conf.template spark-defaults.conf
[root@hadoop01 conf]# vim spark-defaults.conf
spark.eventLog.enabled true
spark.eventLog.dir hdfs://node01:9000/spark_log
spark.eventLog.compress true
在hadoop的hdfs上常见spark日志目录
[root@hadoop01 conf]# hdfs dfs -mkdir -p /spark_log
分发spark-HA程序到其他两台服务器上
启动spark高可用集群
[root@hadoop01 conf]# cd /usr/local/spark-HA/
[root@hadoop01 spark-HA]# sbin/start-all.sh
[root@hadoop01 spark-HA]# sbin/start-history-server.sh
node02服务器启动master节点
[root@hadoop01 spark-HA]# cd /usr/local/spark-HA/
[root@hadoop01 spark-HA]# sbin/start-master.sh
验证spark高可用集群
spark的HA模式下的spark的命令行
[root@hadoop01 spark-HA]# bin/spark-shell --master spark://node01:7077,node02:7077
运行jar包进行验证测试
[root@hadoop01 spark-HA]# bin/spark-submit \
--class org.apache.spark.examples.SparkPi \
--master spark://node01:7077,node02:7077 \
--executor-memory 1G \
--total-executor-cores \
/usr/local/spark-HA/examples/jars/spark-examples_2.-2.2..jar \
spark的on yarn模式
小提示:如果yarn集群资源不够,我们可以在yarn-site.xml当中添加以下两个配置,然后重启yarn集群,跳过yarn集群资源的检查
[root@hadoop01 conf]# scp -r spark-HA root@node02:$PWD
[root@hadoop01 conf]# scp -r spark-HA root@node03:$PWD
<property> <name> yarn.nodemanager.pmem-check-enabled</name <value>false</value> </property> <property> <name> yarn.nodemanager.vmem-check-enabled</name <value>false</value> </property>
修改配置文件spark-env.sh
HADOOP_CONF_DIR=/usr/local/hadoop-HA/etc/hadoop
YARN_CONF_DIR=/usr/local/hadoop-HA/etc/hadoop
提交任务到yarn集群上进行验证
[root@hadoop01 spark-HA]# bin/spark-submit \
--class org.apache.spark.examples.SparkPi \
--master yarn \
--deploy-mode client \
/usr/local/spark-HA/examples/jars/spark-examples_2.-2.2..jar \