如何启动spark

解决:spark的bin目录下,无法启动spark问题

root@hadoop7 sbin# ./start-all.sh

./start-all.sh:行29: /root/install/spark-2.4.0-bin-hadoop2.7/sbin/spark-config.sh: 没有那个文件或目录

./start-all.sh:行32: /root/install/spark-2.4.0-bin-hadoop2.7/sbin/start-master.sh: 没有那个文件或目录

./start-all.sh:行35: /root/install/spark-2.4.0-bin-hadoop2.7/sbin/start-slaves.sh: 没有那个文件或目录


root@hadoop7 \~# jps

1357 Jps

root@hadoop7 \~# start-all.sh

This script is Deprecated. Instead use start-dfs.sh and start-yarn.sh

Starting namenodes on hadoop7

hadoop7: starting namenode, logging to /root/install/hadoop-2.7.7/logs/hadoop-root-namenode-hadoop7.out

localhost: starting datanode, logging to /root/install/hadoop-2.7.7/logs/hadoop-root-datanode-hadoop7.out

Starting secondary namenodes 0.0.0.0

0.0.0.0: starting secondarynamenode, logging to /root/install/hadoop-2.7.7/logs/hadoop-root-secondarynamenode-hadoop7.out

starting yarn daemons

starting resourcemanager, logging to /root/install/hadoop-2.7.7/logs/yarn-root-resourcemanager-hadoop7.out

localhost: starting nodemanager, logging to /root/install/hadoop-2.7.7/logs/yarn-root-nodemanager-hadoop7.out

root@hadoop7 \~# jps

2850 Jps

1763 DataNode

2515 NodeManager

1564 NameNode

2268 ResourceManager

2014 SecondaryNameNode

root@hadoop7 \~# zkServer.sh start

ZooKeeper JMX enabled by default

Using config: /root/install/zookeeper-3.4.14/bin/../conf/zoo.cfg

Starting zookeeper ... STARTED


root@hadoop7 spark-2.4.5-bin-hadoop2.7# cd conf/

root@hadoop7 conf# ls

docker.properties.template hive-site.xml metrics.properties.template slaves.template spark-env.sh

fairscheduler.xml.template log4j.properties.template slaves spark-defaults.conf.template spark-env.sh.template

root@hadoop7 conf# vi spark-env.sh //把hadoop6 改为了hadoop7

root@hadoop7 conf#

root@hadoop7 conf# cd ..

root@hadoop7 spark-2.4.5-bin-hadoop2.7# cd logs/

root@hadoop7 logs# ls

spark-root-org.apache.spark.deploy.master.Master-1-hadoop4.out spark-root-org.apache.spark.deploy.worker.Worker-1-hadoop4.out

spark-root-org.apache.spark.deploy.master.Master-1-hadoop4.out.1 spark-root-org.apache.spark.deploy.worker.Worker-1-hadoop4.out.1

spark-root-org.apache.spark.deploy.master.Master-1-hadoop4.out.2 spark-root-org.apache.spark.deploy.worker.Worker-1-hadoop4.out.2

spark-root-org.apache.spark.deploy.master.Master-1-hadoop4.out.3 spark-root-org.apache.spark.deploy.worker.Worker-1-hadoop4.out.3

spark-root-org.apache.spark.deploy.master.Master-1-hadoop4.out.4 spark-root-org.apache.spark.deploy.worker.Worker-1-hadoop5.out

spark-root-org.apache.spark.deploy.master.Master-1-hadoop5.out spark-root-org.apache.spark.deploy.worker.Worker-1-hadoop5.out.1

spark-root-org.apache.spark.deploy.master.Master-1-hadoop5.out.1 spark-root-org.apache.spark.deploy.worker.Worker-1-hadoop5.out.2

spark-root-org.apache.spark.deploy.master.Master-1-hadoop5.out.2 spark-root-org.apache.spark.deploy.worker.Worker-1-hadoop5.out.3

spark-root-org.apache.spark.deploy.master.Master-1-hadoop5.out.3 spark-root-org.apache.spark.deploy.worker.Worker-1-hadoop5.out.4

spark-root-org.apache.spark.deploy.master.Master-1-hadoop5.out.4 spark-root-org.apache.spark.deploy.worker.Worker-1-hadoop5.out.5

spark-root-org.apache.spark.deploy.master.Master-1-hadoop5.out.5 spark-root-org.apache.spark.deploy.worker.Worker-1-hadoop6.out

spark-root-org.apache.spark.deploy.master.Master-1-hadoop6.out spark-root-org.apache.spark.deploy.worker.Worker-1-hadoop6.out.1

spark-root-org.apache.spark.deploy.master.Master-1-hadoop6.out.1

root@hadoop7 logs# rm -rf *

root@hadoop7 logs# cd ..

root@hadoop7 spark-2.4.5-bin-hadoop2.7# cd sbin/

root@hadoop7 sbin# ls

slaves.sh start-all.sh start-mesos-shuffle-service.sh start-thriftserver.sh stop-mesos-dispatcher.sh stop-slaves.sh

spark-config.sh start-history-server.sh start-shuffle-service.sh stop-all.sh stop-mesos-shuffle-service.sh stop-thriftserver.sh

spark-daemon.sh start-master.sh start-slave.sh stop-history-server.sh stop-shuffle-service.sh

spark-daemons.sh start-mesos-dispatcher.sh start-slaves.sh stop-master.sh stop-slave.sh

root@hadoop7 sbin# ./start-all.sh

starting org.apache.spark.deploy.master.Master, logging to /root/install/spark-2.4.5-bin-hadoop2.7/logs/spark-root-org.apache.spark.deploy.master.Master-1-hadoop7.out

localhost: starting org.apache.spark.deploy.worker.Worker, logging to /root/install/spark-2.4.5-bin-hadoop2.7/logs/spark-root-org.apache.spark.deploy.worker.Worker-1-hadoop7.out

就启动成功了

相关推荐
Web3_Daisy8 小时前
Pump.fun 与 FOMO 竞争背后的 Meme 市场变局
大数据·人工智能·金融·web3·区块链
江畔柳前堤8 小时前
HBM:大语言模型时代的「算力血液」——从内存墙到带宽革命的深度拆解
服务器·人工智能·windows·目标检测·语言模型·自然语言处理·软件工程
不会就选b9 小时前
Linux之信号(二)
linux·运维·服务器
论文避坑指南10 小时前
论文写作全流程AI合规边界:从选题到投稿的“红绿灯“清单
大数据·人工智能·深度学习
GlueNa2SiO310 小时前
第十八章 Linux故障排查与恢复
linux·服务器·笔记·学习
寺中人11 小时前
Linux 基础命令入门实战教程:从零掌握常用操作,新手快速上手
linux·运维·服务器·shell·linux 命令·linux 基础教程·linux 入门
V哥AI增长11 小时前
Schema.org 结构化数据与GEO技术落地:AI引擎引用机制与JSON-LD部署实证研究
大数据·运维·人工智能
嘉禾望岗50311 小时前
datagrip连接带有kerberos认证的hive
大数据·kerberos
小张成长计划..12 小时前
【Linux】18:基础IO
linux·运维·服务器
爱吃面的猫13 小时前
大数据Kafka3.x之——Kafka3.3.0安装与使用(详细)
大数据·分布式·zookeeper