1.官方网址
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2.点击下载
下载最新版本目前是（2.4.3）
此spark预设为hadoop2.7或者更高版本，我前面安装的是hadoop3.1.2后面试一下不知道兼容不
具体地址：http://spark.apache.org/downloads.html
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跳转到此页面继续选择一个下载地址
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选择我们下载好的spark安装包上传到我们的虚拟机
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上传成功
[shaozhiqi@hadoop102 opt]$ cd software/
[shaozhiqi@hadoop102 software]$ ll
total 739668
-rw-rw-r--. 1 shaozhiqi shaozhiqi 332433589 Jun 23 19:59 hadoop-3.1.2.tar.gz
-rw-rw-r--. 1 shaozhiqi shaozhiqi 194990602 Jun 23 19:59 jdk-8u211-linux-x64.tar.gz
-rw-rw-r--. 1 shaozhiqi shaozhiqi 229988313 Jun 30 17:46 spark-2.4.3-bin-hadoop2.7.tgz
解压
[shaozhiqi@hadoop102 software]$ tar -zxvf spark-2.4.3-bin-hadoop2.7.tgz -C /opt/module/
进入解压后的spark目录
[shaozhiqi@hadoop102 module]$ pwd
/opt/module
[shaozhiqi@hadoop102 module]$ ll
total 12
drwxr-xr-x. 15 shaozhiqi shaozhiqi 4096 Jun 30 10:48 hadoop-3.1.2
drwxr-xr-x. 7 shaozhiqi shaozhiqi 4096 Jun 23 15:46 jdk1.8.0_211
drwxr-xr-x. 13 shaozhiqi shaozhiqi 4096 May 1 13:19 spark-2.4.3-bin-hadoop2.7
[shaozhiqi@hadoop102 module]$ cd spark-2.4.3-bin-hadoop2.7/
[shaozhiqi@hadoop102 spark-2.4.3-bin-hadoop2.7]$ ls
bin data jars LICENSE NOTICE R RELEASE yarn
conf examples kubernetes licenses python README.md sbin
[shaozhiqi@hadoop102 spark-2.4.3-bin-hadoop2.7]$
3 相关文件解释
3.1 有bin目录和sbin目录，sbin目录里放的都是负责管理集群的命令
[shaozhiqi@hadoop102 spark-2.4.3-bin-hadoop2.7]$ cd sbin/
[shaozhiqi@hadoop102 sbin]$ ls
slaves.sh start-mesos-shuffle-service.sh stop-mesos-dispatcher.sh
spark-config.sh start-shuffle-service.sh stop-mesos-shuffle-service.sh
spark-daemon.sh start-slave.sh stop-shuffle-service.sh
spark-daemons.sh start-slaves.sh stop-slave.sh
start-all.sh start-thriftserver.sh stop-slaves.sh
start-history-server.sh stop-all.sh stop-thriftserver.sh
start-master.sh stop-history-server.sh
start-mesos-dispatcher.sh stop-master.sh
[shaozhiqi@hadoop102 sbin]$
3.2 bin目录里面是一些spark具体的操作命令，如提交任务等
[shaozhiqi@hadoop102 spark-2.4.3-bin-hadoop2.7]$ cd bin/
[shaozhiqi@hadoop102 bin]$ ls
beeline load-spark-env.sh spark-class spark-shell spark-submit
beeline.cmd pyspark spark-class2.cmd spark-shell2.cmd spark-submit2.cmd
docker-image-tool.sh pyspark2.cmd spark-class.cmd spark-shell.cmd spark-submit.cmd
find-spark-home pyspark.cmd sparkR spark-sql
find-spark-home.cmd run-example sparkR2.cmd spark-sql2.cmd
load-spark-env.cmd run-example.cmd sparkR.cmd spark-sql.cmd
[shaozhiqi@hadoop102 bin]$
3.3 Conf主要是spark的配置文件
[shaozhiqi@hadoop102 conf]$ ll
total 36
-rw-r--r--. 1 shaozhiqi shaozhiqi 996 May 1 13:19 docker.properties.template
-rw-r--r--. 1 shaozhiqi shaozhiqi 1105 May 1 13:19 fairscheduler.xml.template
-rw-r--r--. 1 shaozhiqi shaozhiqi 2025 May 1 13:19 log4j.properties.template
-rw-r--r--. 1 shaozhiqi shaozhiqi 7801 May 1 13:19 metrics.properties.template
-rw-r--r--. 1 shaozhiqi shaozhiqi 865 May 1 13:19 slaves.template
-rw-r--r--. 1 shaozhiqi shaozhiqi 1292 May 1 13:19 spark-defaults.conf.template
-rwxr-xr-x. 1 shaozhiqi shaozhiqi 4221 May 1 13:19 spark-env.sh.template
[shaozhiqi@hadoop102 conf]$ pwd
/opt/module/spark-2.4.3-bin-hadoop2.7/conf
[shaozhiqi@hadoop102 conf]$
4. 操作
4.1 重命名这三个配置文件：
[shaozhiqi@hadoop102 conf]$ mv slaves.template slaves
[shaozhiqi@hadoop102 conf]$ mv spark-defaults.conf.template spark-defaults.conf
[shaozhiqi@hadoop102 conf]$ mv spark-env.sh.template spark-env.sh
4.2修改slaves(配置worker)
[shaozhiqi@hadoop102 conf]$ vim slaves
# A Spark Worker will be started on each of the machines listed below.
hadoop102
hadoop103
hadoop104
4.3修改spark-env.sh，配置marster
[shaozhiqi@hadoop102 conf]$ vim spark-env.sh
SPARK_MASTER_HOST=hadoop102
SPARK_MASTER_PORT=7077
# Options for the daemons used in the standalone deploy mode
# - SPARK_MASTER_HOST, to bind the master to a different IP address or hostname
# - SPARK_MASTER_PORT / SPARK_MASTER_WEBUI_PORT, to use non-default ports for the master
4.4分发到我们的其他机器
[shaozhiqi@hadoop102 module]$ testxsync spark-2.4.3-bin-hadoop2.7/
4.5检查是否分发成功
103成功多了spark-2.4.3-bin-hadoop2.7
[shaozhiqi@hadoop103 module]$ ll
total 12
drwxr-xr-x. 15 shaozhiqi shaozhiqi 4096 Jun 30 10:30 hadoop-3.1.2
drwxr-xr-x. 7 shaozhiqi shaozhiqi 4096 Jun 23 15:19 jdk1.8.0_211
drwxr-xr-x. 13 shaozhiqi shaozhiqi 4096 Jun 30 18:35 spark-2.4.3-bin-hadoop2.7
[shaozhiqi@hadoop103 module]$
104成功
[shaozhiqi@hadoop104 ~]$ cd /opt/module/
[shaozhiqi@hadoop104 module]$ ll
total 12
drwxr-xr-x. 15 shaozhiqi shaozhiqi 4096 Jun 30 10:27 hadoop-3.1.2
drwxr-xr-x. 7 shaozhiqi shaozhiqi 4096 Jun 23 15:23 jdk1.8.0_211
drwxr-xr-x. 13 shaozhiqi shaozhiqi 4096 Jun 30 18:35 spark-2.4.3-bin-hadoop2.7
[shaozhiqi@hadoop104 module]$
4.6单独启动spark(Hadoop的namenode和datanode都没有启动)
[shaozhiqi@hadoop102 hadoop-3.1.2]$ jps
12022 Jps
[shaozhiqi@hadoop102 hadoop-3.1.2]$
到spark目录
[shaozhiqi@hadoop102 spark-2.4.3-bin-hadoop2.7]$ sbin/start-all.sh
starting org.apache.spark.deploy.master.Master, logging to /opt/module/spark-2.4.3-bin-hadoop2.7/logs/spark-shaozhiqi-org.apache.spark.deploy.master.Master-1-hadoop102.out
hadoop104: starting org.apache.spark.deploy.worker.Worker, logging to /opt/module/spark-2.4.3-bin-hadoop2.7/logs/spark-shaozhiqi-org.apache.spark.deploy.worker.Worker-1-hadoop104.out
hadoop103: starting org.apache.spark.deploy.worker.Worker, logging to /opt/module/spark-2.4.3-bin-hadoop2.7/logs/spark-shaozhiqi-org.apache.spark.deploy.worker.Worker-1-hadoop103.out
hadoop102: starting org.apache.spark.deploy.worker.Worker, logging to /opt/module/spark-2.4.3-bin-hadoop2.7/logs/spark-shaozhiqi-org.apache.spark.deploy.worker.Worker-1-hadoop102.out
hadoop104: failed to launch: nice -n 0 /opt/module/spark-2.4.3-bin-hadoop2.7/bin/spark-class org.apache.spark.deploy.worker.Worker --webui-port 8081 spark://hadoop102:7077
hadoop104: JAVA_HOME is not set
hadoop104: full log in /opt/module/spark-2.4.3-bin-hadoop2.7/logs/spark-shaozhiqi-org.apache.spark.deploy.worker.Worker-1-hadoop104.out
hadoop103: failed to launch: nice -n 0 /opt/module/spark-2.4.3-bin-hadoop2.7/bin/spark-class org.apache.spark.deploy.worker.Worker --webui-port 8081 spark://hadoop102:7077
hadoop103: JAVA_HOME is not set
hadoop103: full log in /opt/module/spark-2.4.3-bin-hadoop2.7/logs/spark-shaozhiqi-org.apache.spark.deploy.worker.Worker-1-hadoop103.out
hadoop102: failed to launch: nice -n 0 /opt/module/spark-2.4.3-bin-hadoop2.7/bin/spark-class org.apache.spark.deploy.worker.Worker --webui-port 8081 spark://hadoop102:7077
hadoop102: JAVA_HOME is not set
hadoop102: full log in /opt/module/spark-2.4.3-bin-hadoop2.7/logs/spark-shaozhiqi-org.apache.spark.deploy.worker.Worker-1-hadoop102.out
[shaozhiqi@hadoop102 spark-2.4.3-bin-hadoop2.7]$
日志中也有fail,验证下页面：
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Workers没有其他机器，启动失败
4.7重新修改下我们的配置文件，先停掉spark
[shaozhiqi@hadoop102 spark-2.4.3-bin-hadoop2.7]$ sbin/stop-all.sh
export JAVA_HOME=/opt/module/jdk1.8.0_211
export SPARK_MASTER_HOS=hadoop102
export SPARK_MASTER_PORT=7077
4.8重新分发下修改的配置
[shaozhiqi@hadoop102 module]$ testxsync spark-2.4.3-bin-hadoop2.7/
4.9重新启动spark
[shaozhiqi@hadoop102 spark-2.4.3-bin-hadoop2.7]$ sbin/start-all.sh
starting org.apache.spark.deploy.master.Master, logging to /opt/module/spark-2.4.3-bin-hadoop2.7/logs/spark-shaozhiqi-org.apache.spark.deploy.master.Master-1-hadoop102.out
hadoop103: starting org.apache.spark.deploy.worker.Worker, logging to /opt/module/spark-2.4.3-bin-hadoop2.7/logs/spark-shaozhiqi-org.apache.spark.deploy.worker.Worker-1-hadoop103.out
hadoop104: starting org.apache.spark.deploy.worker.Worker, logging to /opt/module/spark-2.4.3-bin-hadoop2.7/logs/spark-shaozhiqi-org.apache.spark.deploy.worker.Worker-1-hadoop104.out
hadoop102: starting org.apache.spark.deploy.worker.Worker, logging to /opt/module/spark-2.4.3-bin-hadoop2.7/logs/spark-shaozhiqi-org.apache.spark.deploy.worker.Worker-1-hadoop102.out
[shaozhiqi@hadoop102 spark-2.4.3-bin-hadoop2.7]$
4.10验证：
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4.11查看进程：
102
[shaozhiqi@hadoop102 spark-2.4.3-bin-hadoop2.7]$ jps
13217 Worker
13297 Jps
13135 Master
[shaozhiqi@hadoop102 spark-2.4.3-bin-hadoop2.7]$
103
[shaozhiqi@hadoop103 conf]$ jps
10528 Worker
10601 Jps
[shaozhiqi@hadoop103 conf]$
104
[shaozhiqi@hadoop104 module]$ jps
11814 Jps
11741 Worker
[shaozhiqi@hadoop104 module]$
4.12跑一个官方的示例
查看示例版本
[shaozhiqi@hadoop102 examples]$ cd jars
[shaozhiqi@hadoop102 jars]$ ll
total 2132
-rw-r--r--. 1 shaozhiqi shaozhiqi 153982 May 1 13:19 scopt_2.11-3.7.0.jar
-rw-r--r--. 1 shaozhiqi shaozhiqi 2023919 May 1 13:19 spark-examples_2.11-2.4.3.jar
提交任务
bin/spark-submit
--class org.apache.spark.examples.SparkPi \ //指定一个主类
--master spark://hadoop102:7077 \ //指明也提交给那个集群
--executor-memory 1G \ //任务执行时的内存可不指定
--total-executor-cores 2 // 执行executor个数
./examples/jars/spark-examples_2.11-2.4.3.jar \ //那个jar包执行
100 //参数
bin/spark-submit \
--class org.apache.spark.examples.SparkPi \
--master spark://hadoop102:7077 \
--executor-memory 1G \
--total-executor-cores 2 \
./examples/jars/spark-examples_2.11-2.4.3.jar \
100
查看我们的spark监控：发现了我们刚刚执行的任务在执行中
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4.13 Spark-shell也可以提交任务。会打开我们的Scala代码编辑器，这样我们可以直接写代码进行提交任务
[shaozhiqi@hadoop102 spark-2.4.3-bin-hadoop2.7]$ bin/spark-shell --master spark://hadoop102:7077
Using Spark\'s default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Spark context Web UI available at http://hadoop102:4040
Spark context available as \'sc\' (master = spark://hadoop102:7077, app id = app-20190630044455-0001).
Spark session available as \'spark\'.
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ \'_/
/___/ .__/\_,_/_/ /_/\_\ version 2.4.3
/_/
Using Scala version 2.11.12 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_211)
Type in expressions to have them evaluated.
Type :help for more information.
scala>
访问4.13.中的web ui http://hadoop102:4040
之所以要替换成IP是因为我们的win10没有配置ip和机器名的映射，此页面的作用我后续会补充
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