spark-2.4.0-hadoop2.7-高可用(HA)安装部署 5.1. Spark安装5.2. 环境变量修改5.3. 配置修改5.4. 分发到其他机器5.5.

时间:2022-07-26
本文章向大家介绍spark-2.4.0-hadoop2.7-高可用(HA)安装部署 5.1. Spark安装5.2. 环境变量修改5.3. 配置修改5.4. 分发到其他机器5.5. ,主要内容包括其使用实例、应用技巧、基本知识点总结和需要注意事项,具有一定的参考价值,需要的朋友可以参考一下。

1. 主机规划

主机名称

IP地址

操作系统

部署软件

运行进程

备注

mini01

172.16.1.11【内网】 10.0.0.11 【外网】

CentOS 7.5

Jdk-8、zookeeper-3.4.5、Hadoop2.7.6、hbase-2.0.2、kafka_2.11-2.0.0、spark-2.4.0-hadoop2.7【主】

QuorumPeerMain、

mini02

172.16.1.12【内网】 10.0.0.12 【外网】

CentOS 7.5

Jdk-8、zookeeper-3.4.5、Hadoop2.7.6、hbase-2.0.2、kafka_2.11-2.0.0、spark-2.4.0-hadoop2.7【主】

QuorumPeerMain、

mini03

172.16.1.13【内网】 10.0.0.13 【外网】

CentOS 7.5

Jdk-8、zookeeper-3.4.5、Hadoop2.7.6、hbase-2.0.2、kafka_2.11-2.0.0、spark-2.4.0-hadoop2.7

QuorumPeerMain、

mini04

172.16.1.14【内网】 10.0.0.14 【外网】

CentOS 7.5

Jdk-8、zookeeper-3.4.5、Hadoop2.7.6、hbase-2.0.2、spark-2.4.0-hadoop2.7

QuorumPeerMain、

mini05

172.16.1.15【内网】 10.0.0.15 【外网】

CentOS 7.5

Jdk-8、zookeeper-3.4.5、Hadoop2.7.6、hbase-2.0.2、spark-2.4.0-hadoop2.7

QuorumPeerMain、

说明

借助zookeeper,并且启动至少两个Master节点来实现高可靠。

2. 免密码登录

实现mini01、mini02到mini01、mini02、mini03、mini04、mini05通过秘钥免密码登录。

参见文章:Hadoop2.7.6_01_部署

3. Jdk【java8】

参见文章:Hadoop2.7.6_01_部署

4. Zookeeper部署

参见文章:zookeeper-02 部署

并启动zookeeper服务

5. Spark部署步骤

5.1. Spark安装

 1 [yun@mini01 software]$ pwd
 2 /app/software
 3 [yun@mini01 software]$ ll
 4 total 238572
 5 -rw-r--r--  1 yun yun 227893062 Nov 19 21:24 spark-2.4.0-bin-hadoop2.7.tgz
 6 [yun@mini01 software]$ tar xf spark-2.4.0-bin-hadoop2.7.tgz  
 7 [yun@mini01 software]$ mv spark-2.4.0-bin-hadoop2.7 /app/  
 8 [yun@mini01 software]$ cd /app/
 9 [yun@mini01 ~]$ ln -s spark-2.4.0-bin-hadoop2.7/ spark  
10 [yun@mini01 ~]$ ll -d spark-*   
11 drwxr-xr-x 13 yun yun 211 Oct 29 14:36 spark-2.4.0-bin-hadoop2.7
12 lrwxrwxrwx  1 yun yun  26 Nov 24 14:23 spark -> spark-2.4.0-bin-hadoop2.7/

5.2. 环境变量修改

  根据规划,该环境变量的修改包括mini01、mini02、mini03、mini04、mini05

1 # 需要root权限去添加环境变量
2 [root@mini01 ~]# tail /etc/profile
3 ………………
4 # spark环境变量
5 export SPARK_HOME="/app/spark"
6 export PATH=$SPARK_HOME/bin:$SPARK_HOME/sbin:$PATH
7 
8 [root@mini01 ~]# logout
9 [yun@mini01 conf]$ source /etc/profile  # 重新加载该环境变量

5.3. 配置修改

 1 [yun@mini01 conf]$ pwd
 2 /app/spark/conf
 3 [yun@mini01 conf]$ cp -a spark-env.sh.template spark-env.sh  
 4 [yun@mini01 conf]$ tail spark-env.sh  # 修改环境变量配置
 5 # Options for native BLAS, like Intel MKL, OpenBLAS, and so on.
 6 # You might get better performance to enable these options if using native BLAS (see SPARK-21305).
 7 # - MKL_NUM_THREADS=1        Disable multi-threading of Intel MKL
 8 # - OPENBLAS_NUM_THREADS=1   Disable multi-threading of OpenBLAS
 9 
10 # 添加配置如下
11 # 配置JAVA_HOME
12 export JAVA_HOME=/app/jdk
13 # -Dspark.deploy.recoverMode=ZOOKEEPER #代表发生故障使用zookeeper服务
14 # -Dspark.depoly.zookeeper.url=mini01:2181,mini02:2181,mini03:2181,mini04:2181,mini05:2181 #zookeeper的连接信息
15 # -Dspark.deploy.zookeeper.dir=/app/zookeeper/spark #spark要在zookeeper上写数据时的保存目录
16 export SPARK_DAEMON_JAVA_OPTS="-Dspark.deploy.recoveryMode=ZOOKEEPER -Dspark.deploy.zookeeper.url=mini01:2181,mini02:2181,mini03:2181,mini04:2181,mini05:2181 -Dspark.deploy.zookeeper.dir=/spark"
17 # 每一个Worker最多可以使用的内存,我的虚拟机就2g
18 # 真实服务器如果有128G,你可以设置为100G
19 # 所以这里设置为1024m或1g
20 export SPARK_WORKER_MEMORY=1024m
21 # 每一个Worker最多可以使用的cpu core的个数,我虚拟机就一个...
22 # 真实服务器如果有32个,你可以设置为32个
23 export SPARK_WORKER_CORES=1
24 # 提交Application的端口,默认就是这个,万一要改呢,改这里
25 export SPARK_MASTER_PORT=7077
26 
27 [yun@mini01 conf]$ pwd
28 /app/spark /conf
29 [yun@mini01 conf]$ cp -a slaves.template slaves 
30 [yun@mini01 conf]$ tail slaves  # 修改slaves 配置
31 # distributed under the License is distributed on an "AS IS" BASIS,
32 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
33 # See the License for the specific language governing permissions and
34 # limitations under the License.
35 #
36 
37 # A Spark Worker will be started on each of the machines listed below.
38 mini03
39 mini04
40 mini05

配置说明

# -Dspark.deploy.zookeeper.dir=/app/zookeeper/spark # spark要在zookeeper上写数据时的保存目录

1 [yun@mini05 ~]$ zkCli.sh  # 进入zookeeper命令行  【在spark启动后查看】
2 [zk: localhost:2181(CONNECTED) 0] ls /   # 其中的 /spark 就是 我们在spark-env.sh中的配置
3 [cluster, brokers, zookeeper, yarn-leader-election, hadoop-ha, admin, isr_change_notification, log_dir_event_notification, controller_epoch, spark, consumers, latest_producer_id_block, config, hbase]
4 [zk: localhost:2181(CONNECTED) 1] ls /spark
5 [leader_election, master_status]
6 [zk: localhost:2181(CONNECTED) 2] ls /spark/master_status
7 [worker_worker-20181125113658-172.16.1.13-18433, worker_worker-20181125113658-172.16.1.14-14175, worker_worker-20181125113658-172.16.1.15-8887]
8 [zk: localhost:2181(CONNECTED) 3] ls /spark/leader_election
9 [_c_6c6d0c36-3017-4354-a05c-9414a78d79e2-latch-0000000000, _c_04ceffff-b763-454a-b3f1-7fb56f56fa84-latch-0000000001]

5.4. 分发到其他机器

  分发到mini02、mini03、mini04和mini05

  其中mini01和mini02作为master

1 [yun@mini01 ~]$ scp -pr spark-2.4.0-bin-hadoop2.7/ yun@mini02:/app  # 拷贝到mini02
2 [yun@mini01 ~]$ scp -pr spark-2.4.0-bin-hadoop2.7/ yun@mini03:/app  # 拷贝到mini03
3 [yun@mini01 ~]$ scp -pr spark-2.4.0-bin-hadoop2.7/ yun@mini04:/app  # 拷贝到mini04
4 [yun@mini01 ~]$ scp -pr spark-2.4.0-bin-hadoop2.7/ yun@mini05:/app  # 拷贝到mini05

在mini02、mini03、mini04和mini05上操作

1 [yun@mini04 ~]$ pwd
2 /app
3 [yun@mini04 ~]$ ll -d spark-2.4.0-bin-hadoop2.7
4 drwxr-xr-x 13 yun yun 211 Oct 29 14:36 spark-2.4.0-bin-hadoop2.7
5 [yun@mini04 ~]$ ln -s spark-2.4.0-bin-hadoop2.7/ spark  
6 [yun@mini04 ~]$ ll -d spark-*
7 drwxr-xr-x 13 yun yun 211 Oct 29 14:36 spark-2.4.0-bin-hadoop2.7
8 lrwxrwxrwx  1 yun yun  26 Nov 24 23:39 spark -> spark-2.4.0-bin-hadoop2.7/

5.5. 启动spark

5.5.1. 在mini01上操作

 1 [yun@mini01 sbin]$ pwd
 2 /app/spark/sbin
 3 [yun@mini01 sbin]$ ./start-all.sh  # 关闭使用 stop-all.sh 脚本
 4 [yun@mini01 sbin]$ ./start-all.sh 
 5 starting org.apache.spark.deploy.master.Master, logging to /app/spark/logs/spark-yun-org.apache.spark.deploy.master.Master-1-mini01.out
 6 mini03: starting org.apache.spark.deploy.worker.Worker, logging to /app/spark/logs/spark-yun-org.apache.spark.deploy.worker.Worker-1-mini03.out
 7 mini04: starting org.apache.spark.deploy.worker.Worker, logging to /app/spark/logs/spark-yun-org.apache.spark.deploy.worker.Worker-1-mini04.out
 8 mini05: starting org.apache.spark.deploy.worker.Worker, logging to /app/spark/logs/spark-yun-org.apache.spark.deploy.worker.Worker-1-mini05.out
 9 [yun@mini01 ~]$ 
10 [yun@mini01 ~]$ jps  # 查看进程状态 
11 4033 QuorumPeerMain
12 4683 Jps
13 4575 Master

5.5.2. 在mini02上操作

1 [yun@mini02 sbin]$ pwd
2 /app/spark/sbin
3 [yun@mini02 sbin]$ ./start-master.sh 
4 starting org.apache.spark.deploy.master.Master, logging to /app/spark/logs/spark-yun-org.apache.spark.deploy.master.Master-1-mini02.out
5 [yun@mini02 sbin]$ jps  # 查看进程状态
6 2914 Master
7 2999 Jps
8 2313 QuorumPeerMain

5.5.3. mini03进程查看

1 [yun@mini03 ~]$ jps
2 2824 Jps
3 2558 QuorumPeerMain
4 2766 Worker

5.5.4. mini04进程查看

1 [yun@mini04 ~]$ jps 
2 2931 Jps
3 2824 Worker
4 2555 QuorumPeerMain

5.5.5. mini05进程查看

1 [yun@mini05 ~]$ jps 
2 2806 Jps
3 2747 Worker
4 2527 QuorumPeerMain

5.6. 浏览器访问

1 http://mini01:8080/    
1 http://mini02:8080/    

说明

如果我们停了mini01的spark master,稍等一会儿可见mini02的master状态从standby变为了alive。

此时再启动mini01的master,可见mini01的master状态是standby。