您的位置:首页 > 大数据

大数据 IMF传奇 如何搭建 8台设备的SPARK分布式 集群

2016-02-07 17:40 671 查看
1.下载spark-1.6.0-bin-hadoop2.6.tgz

2.解压

root@master:/usr/local/setup_tools# tar -zxvf spark-1.6.0-bin-hadoop2.6.tgz

3.配置Spark的全局环境变量

输入# vi /etc/profile打开profile文件,按i可以进入文本输入模式,在profile文件的增加SPARK_HOME及修改PATH的环境变量

export SPARK_HOME=/usr/local/spark-1.6.0-bin-hadoop2.6

export

PATH=.:$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$SCALA_HOME/bin:$SPARK_HOME/bin

4.source /etc/profile

5.

root@master:/usr/local/spark-1.6.0-bin-hadoop2.6# cd /usr/local/spark-1.6.0-bin-hadoop2.6/conf

root@master:/usr/local/spark-1.6.0-bin-hadoop2.6/conf# ls

docker.properties.template log4j.properties.template slaves.template spark-env.sh.template

fairscheduler.xml.template metrics.properties.template spark-defaults.conf.template

root@master:/usr/local/spark-1.6.0-bin-hadoop2.6/conf#

6.

配置 spark-env.sh

root@master:/usr/local/spark-1.6.0-bin-hadoop2.6/conf# mv spark-env.sh.template spark-env.sh

export SCALA_HOME=/usr/local/scala-2.10.4

export JAVA_HOME=/usr/local/jdk1.8.0_60

export SPARK_MASTER_IP=192.168.189.1

export SPARK_WORKER_MEMORY=2g

export HADOOP_CONF_DIR=/usr/local/hadoop-2.6.0/etc/hadoop

7.配置slaves

# mv slaves.template slaves

worker1

worker2

worker3

worker4

worker5

worker6

worker7

worker8

8.分发配置

root@master:/usr/local/setup_scripts# vi spark_scp.sh

#!/bin/sh

for i in 2 3 4 5 6 7 8 9

do

scp -rq /etc/profile root@192.168.189.$i:/etc/profile

ssh root@192.168.189.$i source /etc/profile

scp -rq /usr/local/spark-1.6.0-bin-hadoop2.6 root@192.168.189.$i:/usr/local/spark-1.6.0-bin-hadoop2.6

done

root@master:/usr/local/setup_scripts# chmod u+x spark_scp.sh

root@master:/usr/local/setup_scripts# ./spark_scp.sh

9.启动spark集群

root@master:/usr/local/hadoop-2.6.0/sbin# cd /usr/local/spark-1.6.0-bin-hadoop2.6/sbin

root@master:/usr/local/spark-1.6.0-bin-hadoop2.6/sbin# start-all.sh

starting org.apache.spark.deploy.master.Master, logging to /usr/local/spark-1.6.0-bin-hadoop2.6/logs/spark-root-org.apache.spark.deploy.master.Master-1-master.out

worker5: starting org.apache.spark.deploy.worker.Worker, logging to /usr/local/spark-1.6.0-bin-hadoop2.6/logs/spark-root-org.apache.spark.deploy.worker.Worker-1-worker5.out

worker4: starting org.apache.spark.deploy.worker.Worker, logging to /usr/local/spark-1.6.0-bin-hadoop2.6/logs/spark-root-org.apache.spark.deploy.worker.Worker-1-worker4.out

worker7: starting org.apache.spark.deploy.worker.Worker, logging to /usr/local/spark-1.6.0-bin-hadoop2.6/logs/spark-root-org.apache.spark.deploy.worker.Worker-1-worker7.out

worker2: starting org.apache.spark.deploy.worker.Worker, logging to /usr/local/spark-1.6.0-bin-hadoop2.6/logs/spark-root-org.apache.spark.deploy.worker.Worker-1-worker2.out

worker1: starting org.apache.spark.deploy.worker.Worker, logging to /usr/local/spark-1.6.0-bin-hadoop2.6/logs/spark-root-org.apache.spark.deploy.worker.Worker-1-worker1.out

worker6: starting org.apache.spark.deploy.worker.Worker, logging to /usr/local/spark-1.6.0-bin-hadoop2.6/logs/spark-root-org.apache.spark.deploy.worker.Worker-1-worker6.out

worker3: starting org.apache.spark.deploy.worker.Worker, logging to /usr/local/spark-1.6.0-bin-hadoop2.6/logs/spark-root-org.apache.spark.deploy.worker.Worker-1-worker3.out

worker8: starting org.apache.spark.deploy.worker.Worker, logging to /usr/local/spark-1.6.0-bin-hadoop2.6/logs/spark-root-org.apache.spark.deploy.worker.Worker-1-worker8.out

root@master:/usr/local/spark-1.6.0-bin-hadoop2.6/sbin# jps

5378 NameNode

5608 SecondaryNameNode

7260 Jps

7181 Master

5742 ResourceManager

root@master:/usr/local/spark-1.6.0-bin-hadoop2.6/sbin#

root@worker3:~/.ssh# jps

4152 Worker

3994 NodeManager

4202 Jps

3262 DataNode

root@worker3:~/.ssh#

root@worker6:/usr/local# jps

3809 NodeManager

4017 Jps

3077 DataNode

3966 Worker

root@worker6:/usr/local#

10.web查看 ok
http://192.168.189.1:8080/
1.6.0 Spark Master at spark://192.168.189.1:7077

URL: spark://192.168.189.1:7077

REST URL: spark://192.168.189.1:6066 (cluster mode)

Alive Workers: 8

Cores in use: 8 Total, 0 Used

Memory in use: 16.0 GB Total, 0.0 B Used

Applications: 0 Running, 0 Completed

Drivers: 0 Running, 0 Completed

Status: ALIVE

Workers

Worker Id Address
State Cores
Memory

worker-20160207173343-192.168.189.2-33566 192.168.189.2:33566
ALIVE 1 (0 Used)
2.0 GB (0.0 B Used)

worker-20160207173344-192.168.189.3-37775 192.168.189.3:37775
ALIVE 1 (0 Used)
2.0 GB (0.0 B Used)

worker-20160207173344-192.168.189.4-51803 192.168.189.4:51803
ALIVE 1 (0 Used)
2.0 GB (0.0 B Used)

worker-20160207173344-192.168.189.5-36047 192.168.189.5:36047
ALIVE 1 (0 Used)
2.0 GB (0.0 B Used)

worker-20160207173344-192.168.189.6-55502 192.168.189.6:55502
ALIVE 1 (0 Used)
2.0 GB (0.0 B Used)

worker-20160207173344-192.168.189.7-49027 192.168.189.7:49027
ALIVE 1 (0 Used)
2.0 GB (0.0 B Used)

worker-20160207173344-192.168.189.8-55787 192.168.189.8:55787
ALIVE 1 (0 Used)
2.0 GB (0.0 B Used)

worker-20160207173344-192.168.189.9-56628 192.168.189.9:56628
ALIVE 1 (0 Used)
2.0 GB (0.0 B Used)



11 spark-shell

root@master:/usr/local/spark-1.6.0-bin-hadoop2.6/sbin# spark-shell

16/02/07 17:36:35 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

16/02/07 17:36:35 INFO spark.SecurityManager: Changing view acls to: root

16/02/07 17:36:35 INFO spark.SecurityManager: Changing modify acls to: root

16/02/07 17:36:35 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(root); users with modify permissions: Set(root)

16/02/07 17:36:36 INFO spark.HttpServer: Starting HTTP Server

16/02/07 17:36:36 INFO server.Server: jetty-8.y.z-SNAPSHOT

16/02/07 17:36:36 INFO server.AbstractConnector: Started SocketConnector@0.0.0.0:51277

16/02/07 17:36:36 INFO util.Utils: Successfully started service 'HTTP class server' on port 51277.

Welcome to

____ __

/ __/__ ___ _____/ /__

_\ \/ _ \/ _ `/ __/ '_/

/___/ .__/\_,_/_/ /_/\_\ version 1.6.0

/_/

Using Scala version 2.10.5 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_60)

Type in expressions to have them evaluated.

Type :help for more information.

16/02/07 17:36:45 INFO spark.SparkContext: Running Spark version 1.6.0

16/02/07 17:36:45 INFO spark.SecurityManager: Changing view acls to: root

16/02/07 17:36:45 INFO spark.SecurityManager: Changing modify acls to: root

16/02/07 17:36:45 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(root); users with modify permissions: Set(root)

16/02/07 17:36:46 INFO util.Utils: Successfully started service 'sparkDriver' on port 46612.

16/02/07 17:36:47 INFO slf4j.Slf4jLogger: Slf4jLogger started

。。。

16/02/07 17:37:25 WARN metastore.ObjectStore: Failed to get database default, returning NoSuchObjectException

16/02/07 17:37:26 INFO metastore.HiveMetaStore: Added admin role in metastore

16/02/07 17:37:26 INFO metastore.HiveMetaStore: Added public role in metastore

16/02/07 17:37:26 INFO metastore.HiveMetaStore: No user is added in admin role, since config is empty

16/02/07 17:37:26 INFO metastore.HiveMetaStore: 0: get_all_databases

16/02/07 17:37:26 INFO HiveMetaStore.audit: ugi=root ip=unknown-ip-addr cmd=get_all_databases

16/02/07 17:37:26 INFO metastore.HiveMetaStore: 0: get_functions: db=default pat=*

16/02/07 17:37:26 INFO HiveMetaStore.audit: ugi=root ip=unknown-ip-addr cmd=get_functions: db=default pat=*

16/02/07 17:37:26 INFO DataNucleus.Datastore: The class "org.apache.hadoop.hive.metastore.model.MResourceUri" is tagged as "embedded-only" so does not have its own datastore table.

16/02/07 17:37:27 INFO session.SessionState: Created local directory: /tmp/821b1835-fa8e-4b49-9e36-064bda6b9d32_resources

16/02/07 17:37:27 INFO session.SessionState: Created HDFS directory: /tmp/hive/root/821b1835-fa8e-4b49-9e36-064bda6b9d32

16/02/07 17:37:27 INFO session.SessionState: Created local directory: /tmp/root/821b1835-fa8e-4b49-9e36-064bda6b9d32

16/02/07 17:37:27 INFO session.SessionState: Created HDFS directory: /tmp/hive/root/821b1835-fa8e-4b49-9e36-064bda6b9d32/_tmp_space.db

16/02/07 17:37:27 INFO repl.SparkILoop: Created sql context (with Hive support)..

SQL context available as sqlContext.
内容来自用户分享和网络整理,不保证内容的准确性,如有侵权内容,可联系管理员处理 点击这里给我发消息
标签: