Hadoop中单机模式和伪分布式分别是什么?

发布网友 发布时间：2022-04-25 21:02

我来回答

共2个回答

懂视网 时间：2022-04-12 03:47

机器mac book，virtualbox4.3.6，virtualbox安装ubunt13.10，在多点分布环境中，配置好一个机器后，clone出另外2个，一共三台机器。 1. Configure the Environment Bash语言: sudo apt-get install -y openjdk-7-jdk openssh-server sudo addgroup hadoop su

机器mac book，virtualbox4.3.6，virtualbox安装ubunt13.10，在多点分布环境中，配置好一个机器后，clone出另外2个，一共三台机器。

1. Configure the Environment

Bash语言: sudo apt-get install -y openjdk-7-jdk openssh-server

sudo addgroup hadoop

sudo adduser —ingroup hadoop hadoop # create password

sudo visudo

hadoop ALL=(ALL) ALL # hadoop user can use sudo

su - hadoop # need password

ssh-keygen -t rsa -P "" # Enter file (/home/hadoop/.ssh/id_rsa)

cat /home/hadoop/.ssh/id_rsa.pub >> /home/hadoop/.ssh/authorized_keys

wget http://apache.fayea.com/apache-mirror/hadoop/common/hadoop-2.3.0/hadoop-2.3.0.tar.gz

tar zxvf hadoop-2.3.0.tar.gz

sudo cp -r hadoop-2.3.0/ /opt

cd /opt

sudo ln -s hadoop-2.3.0 hadoop

sudo chown -R hadoop:hadoop hadoop-2.3.0

sed -i '$a \nexport JAVA_HOME=/usr/lib/jvm/java-7-openjdk-amd' hadoop/etc/hadoop/hadoop-env.sh

2. Configure hadoop single Node environment

cp mapred-site.xml.template mapred-site.xml

vi mapred-site.xml

mapreduce.cluster.temp.dir

No description

true

mapreduce.cluster.local.dir

No description

true

vi yarn-site.xml

yarn.resourcemanager.resource-tracker.address

127.0.0.1:8021

host is the hostname of the resource manager and port is the port on which the NodeManagers contact the Resource Manager.

yarn.resourcemanager.scheduler.address

127.0.0.1:8022

host is the hostname of the resourcemanager and port is the port on which the Applications in the cluster talk to the Resource Manager.

yarn.resourcemanager.scheduler.class

org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.CapacityScheduler

In case you do not want to use the default scheduler

yarn.resourcemanager.address

127.0.0.1:8023

the host is the hostname of the ResourceManager and the port is the port on which the clients can talk to the Resource Manager.

yarn.nodemanager.local-dirs

the local directories used by the nodemanager

yarn.nodemanager.address

0.0.0.0:8041

the nodemanagers bind to this port

yarn.nodemanager.resource.memory-mb

10240

the amount of memory on the NodeManager in GB

yarn.nodemanager.remote-app-log-dir

/app-logs

directory on hdfs where the application logs are moved to

yarn.nodemanager.log-dirs

the directories used by Nodemanagers as log directories

yarn.nodemanager.aux-services

mapreduce_shuffle

shuffle service that needs to be set for Map Reduce to run

补充配置：

mapred-site.xml

mapreduce.framework.name

yarn

core-site.xml

fs.defaultFS

hdfs://127.0.0.1:9000

hdfs-site.xml

dfs.replication

1

Bash语言: cd /opt/hadoop

bin/hdfs namenode -format

sbin/hadoop-daemon.sh start namenode

sbin/hadoop-daemon.sh start datanode

sbin/yarn-daemon.sh start resourcemanager

sbin/yarn-daemon.sh start nodemanager

jps

# Run a job on this node

bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.3.0.jar pi 5 10

3. Running Problem

14/01/04 05:38:22 INFO ipc.Client: Retrying connect to server: localhost/127.0.0.1:8023. Already tried 9 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1 SECONDS)

netstat -atnp # found tcp6

Solve:

cat /proc/sys/net/ipv6/conf/all/disable_ipv6 # 0 means ipv6 is on, 1 means off

cat /proc/sys/net/ipv6/conf/lo/disable_ipv6

cat /proc/sys/net/ipv6/conf/default/disable_ipv6

ip a | grep inet6 # have means ipv6 is on

vi /etc/sysctl.conf

net.ipv6.conf.all.disable_ipv6=1

net.ipv6.conf.default.disable_ipv6=1

net.ipv6.conf.lo.disable_ipv6=1

sudo sysctl -p # have the same effect with reboot

sudo /etc/init.d/networking restart

4. Cluster setup

Config /opt/hadoop/etc/hadoop/{hadoop-env.sh, yarn-env.sh}

export JAVA_HOME=/usr/lib/jvm/java-7-openjdk-amd

cd /opt/hadoop

mkdir -p tmp/{data,name} # on every node. name on namenode, data on datanode

vi /etc/hosts # hostname also changed on each node

192.168.1.110 cloud1

192.168.1.112 cloud2

192.168.1.114 cloud3

vi /opt/hadoop/etc/hadoop/slaves

cloud2

cloud3

core-site.xml

fs.defaultFS

hdfs://cloud1:9000

io.file.buffer.size

131072

hadoop.tmp.dir

/opt/hadoop/tmp

A base for other temporary directories.

据说dfs.datanode.data.dir 需要清空，不然datanode不能启动

hdfs-site.xml

dfs.namenode.name.dir

/opt/hadoop/name

dfs.datanode.data.dir

/opt/hadoop/data

dfs.replication

2

yarn-site.xml

yarn.resourcemanager.address

cloud1:8032

ResourceManager host:port for clients to submit jobs.

yarn.resourcemanager.scheduler.address

cloud1:8030

ResourceManager host:port for ApplicationMasters to talk to Scheduler to obtain resources.

yarn.resourcemanager.resource-tracker.address

cloud1:8031

ResourceManager host:port for NodeManagers.

yarn.resourcemanager.admin.address

cloud1:8033

ResourceManager host:port for administrative commands.

yarn.resourcemanager.webapp.address

cloud1:8088

ResourceManager web-ui host:port.

yarn.resourcemanager.scheduler.class

org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.CapacityScheduler

In case you do not want to use the default scheduler

yarn.nodemanager.resource.memory-mb

10240

the amount of memory on the NodeManager in MB

yarn.nodemanager.local-dirs

the local directories used by the nodemanager

yarn.nodemanager.log-dirs

the directories used by Nodemanagers as log directories

yarn.nodemanager.remote-app-log-dir

/app-logs

directory on hdfs where the application logs are moved to

yarn.nodemanager.aux-services

mapreduce_shuffle

shuffle service that needs to be set for Map Reduce to run

yarn.nodemanager.aux-services.mapreduce_shuffle.class

org.apache.hadoop.mapred.ShuffleHandler

-->

mapred-site.xml

mapreduce.framework.name

yarn

mapreduce.jobhistory.address

cloud1:10020

mapreduce.jobhistory.webapp.address

cloud1:19888

cd /opt/hadoop/

bin/hdfs namenode -format

sbin/start-dfs.sh # cloud1 NameNode SecondaryNameNode, cloud2 and cloud3 DataNode

sbin/start-yarn.sh # cloud1 ResourceManager, cloud2 and cloud3 NodeManager

jps

查看集群状态 bin/hdfs dfsadmin -report

查看文件块组成 bin/hdfs fsck / -files -blocks

NameNode查看hdfs http://192.168.1.110:50070

查看RM http://192.168.1.110:8088

bin/hdfs dfs -mkdir /input

bin/hadoop jar ./share/hadoop/mapreduce/hadoop-mapreduce-examples-2.3.0.jar randomwriter input

5. Questions:

Q: 14/01/05 23:59:05 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

A: /opt/hadoop/lib/native/ 下面的动态链接库是32bit的，要替换成位的

Q: ssh 登录出现Are you sure you want to continue connecting (yes/no)?解决方法

A: 修改/etc/ssh/ssh_config 将其中的# StrictHostKeyChecking ask 改成 StrictHostKeyChecking no

Q: 两个slaves的DataNode无法加入cluster系统，

A: 把/etc/hosts 里面127.0.1.1或localhost 的内容行删除

热心网友 时间：2022-04-12 00:55

1、Hadoop是Apache开源组织的一个分布式计算框架，可以在大量廉价硬件设备组成的集群上运行应用程序，并未应用程序提供一组稳定可靠的接口，旨在构建一个具有高可靠性和良好扩展性的分布式系统。Hadoop的核心是HDFS（Hadoop Distributed File System），Maprece和Hbase，他们分别是Google云计算核心技术GFS，Maprece和Bigtable的开源实现。Hadoop集群有三种运行模式，分别为单机模式，伪分布式模式和完全分布式模式。hadoop完全分布式：3个及以上的实体机或者虚拟机组件的机群。hadoop伪分布式：一个节点。

2、单机模式在一台单机上运行，没有分布式文件系统，而是直接读写本地操作系统的文件系统。默认情况下，Hadoop被配置成以非分布式模式运行的一个Java进程。hadoop完全分布式：3个及以上的实体机或者虚拟机组件的机群。通过分析bin/hadoop脚本可知，-jar并不是bin/hadoop脚本定义的参数，此脚本会把-jar作为Java的参数，Java的-jar参数表示执行一个Jar文件(这个Jar文件必须是一个可执行的Jar,即在MANIFEST中定义了主类),此时外部定义的classpath是不起作用的，因而会抛出java.lang.NoClassDefFoundError异常。而jar是bin/hadoop脚本定义的参数，会调用Hadoop自己的一个工具类RunJar，这个工具类也能够执行一个Jar文件，并且外部定义的classpath有效。

3、伪分布模式也是在一台单机上运行，但用不同的Java进程模仿分布式运行中的各类结点(NameNode,DataNode,JobTracker,TaskTracker,SecondaryNameNode)，请注意分布式运行中的这几个结点的区别：从分布式存储的角度来说，集群中的结点由一个NameNode和若干个DataNode组成,另有一个SecondaryNameNode作为NameNode的备份。从分布式应用的角度来说，集群中的结点由一个JobTracker和若干个TaskTracker组成，JobTracker负责任务的调度，TaskTracker负责并行执行任务。TaskTracker必须运行在DataNode上，这样便于数据的本地计算。JobTracker和NameNode则无须在同一台机器上。