Nutch相关框架安装使用最佳指南

一、nutch1.2
二、nutch1.5.1
三、nutch2.0
四、配置SSH
五、安装Hadoop Cluster（伪分布式运行模式）并运行Nutch
六、安装Hadoop Cluster（分布式运行模式）并运行Nutch
七、配置Ganglia监控Hadoop集群和HBase集群
八、Hadoop配置Snappy压缩
九、Hadoop配置Lzo压缩
十、配置zookeeper集群以运行hbase
十一、配置Hbase集群以运行nutch-2.1(Region Servers会因为内存的问题宕机)
十二、配置Accumulo集群以运行nutch-2.1(gora存在BUG)
十三、配置Cassandra 集群以运行nutch-2.1（Cassandra 采用去中心化结构）
十四、配置MySQL 单机服务器以运行nutch-2.1
十五、nutch2.1 使用DataFileAvroStore作为数据源
十六、nutch2.1 使用AvroStore作为数据源
十七、配置SOLR
十八、Nagios监控
十九、配置Splunk
二十、配置Pig
二十一、配置Hive
二十二、配置Hadoop2.x集群



一、nutch1.2
步骤和二大同小异，在步骤 5、配置构建路径 中需要多两个操作：在左部Package Explorer的 nutch1.2文件夹上单击右键 > Build Path > Configure Build Path...   >  选中Source选项 > Default output folder:修改nutch1.2/bin为nutch1.2/_bin，在左部Package Explorer的 nutch1.2文件夹下的bin文件夹上单击右键 > Team > 还原
二中黄色背景部分是版本号的差异，红色部分是1.2版本没有的，绿色部分是不一样的地方，如下：
1、Add JARs... >  nutch1.2 > lib ，选中所有的.jar文件 > OK
2、crawl-urlfilter.txt
3、将crawl -urlfilter.txt.template改名为crawl -urlfilter.txt
4、修改crawl-urlfilter.txt，将
# accept hosts in MY.DOMAIN.NAME
+^http://([a-z0-9]*\.)*MY.DOMAIN.NAME/

# skip everything else
-.
5、cd /home/ysc/workspace/nutch1.2
nutch1.2是一个完整的搜索引擎，nutch1.5.1只是一个爬虫。nutch1.2可以把索引提交给SOLR，也可以直接生成LUCENE索引，nutch1.5.1则只能把索引提交给SOLR：
1、cd /home/ysc
2、wget http://mirrors.tuna.tsinghua.edu.cn/apache/tomcat/tomcat-7/v7.0.29/bin/apache-tomcat-7.0.29.tar.gz
3、tar -xvf apache-tomcat-7.0.29.tar.gz
4、在左部Package Explorer的 nutch1.2文件夹下的build.xml文件上单击右键 > Run As > Ant Build... > 选中war target > Run
5、cd /home/ysc/workspace/nutch1.2/build
6、unzip nutch-1.2.war -d nutch-1.2
7、cp -r nutch-1.2 /home/ysc/apache-tomcat-7.0.29/webapps
8、vi /home/ysc/apache-tomcat-7.0.29/webapps/nutch-1.2/WEB-INF/classes/nutch-site.xml
加入以下配置：
<property>
  <name>searcher.dir</name>
  <value>/home/ysc/workspace/nutch1.2/data</value>
  <description>
  Path to root of crawl.  This directory is searched (in
  order) for either the file search-servers.txt, containing a list of
  distributed search servers, or the directory "index" containing
  merged indexes, or the directory "segments" containing segment
  indexes.
  </description>
</property>
9、vi /home/ysc/apache-tomcat-7.0.29/conf/server.xml
将
<Connector port="8080" protocol="HTTP/1.1"
               connectionTimeout="20000"
               redirectPort="8443"/>
改为
<Connector port="8080" protocol="HTTP/1.1"
               connectionTimeout="20000"
               redirectPort="8443" URIEncoding="utf-8"/>

10、cd /home/ysc/apache-tomcat-7.0.29/bin
11、./startup.sh
12、访问：http://localhost:8080/nutch-1.2/

关于nutch1.2更多的BUG修复及资料，请参看我在CSDN发布的资源：http://download.csdn.net/user/yangshangchuan

二、nutch1.5.1
1、下载并解压eclipse（集成开发环境）
下载地址：http://www.eclipse.org/downloads/，下载Eclipse IDE for Java EE Developers
2、安装Subclipse插件（SVN客户端）
插件地址：http://subclipse.tigris.org/update_1.8.x，
3、安装IvyDE插件（下载依赖Jar）
插件地址：http://www.apache.org/dist/ant/ivyde/updatesite/
4、签出代码
File > New > Project > SVN > 从SVN 检出项目
创建新的资源库位置 > URL：https://svn.apache.org/repos/asf/nutch/tags/release-1.5.1/ > 选中URL > Finish
弹出New Project向导，选择Java Project > Next，输入Project name：nutch1.5.1 > Finish
5、配置构建路径
在左部Package Explorer的 nutch1.5.1文件夹上单击右键 > Build Path > Configure Build Path...  
> 选中Source选项 > 选择src > Remove > Add Folder... > 选择src/bin, src/java, src/test 和 src/testresources（对于插件，需要选中src/plugin目录下的每一个插件目录下的src/java ， src/test文件夹） > OK
切换到Libraries选项 >
Add Class Folder... > 选中nutch1.5.1/conf > OK
Add JARs... >  需要选中src/plugin目录下的每一个插件目录下的lib目录下的jar文件 > OK
Add Library... > IvyDE Managed Dependencies > Next > Main > Ivy File > Browse > ivy/ivy.xml > Finish
切换到Order and Export选项>
选中conf > Top
6、执行ANT
在左部Package Explorer的 nutch1.5.1文件夹下的build.xml文件上单击右键 > Run As > Ant Build
在左部Package Explorer的 nutch1.5.1文件夹上单击右键 > Refresh
在左部Package Explorer的 nutch1.5.1文件夹上单击右键 > Build Path > Configure Build Path...   >  选中Libraries选项 > Add Class Folder... >  选中build > OK
7、修改配置文件nutch-site.xml 和regex-urlfilter.txt
将nutch-site.xml.template改名为nutch-site.xml
将regex-urlfilter.txt.template改名为regex-urlfilter.txt
在左部Package Explorer的 nutch1.5.1文件夹上单击右键 > Refresh
将如下配置项加入文件nutch-site.xml：
<property>
  <name>http.agent.name</name>
  <value>nutch</value>
</property>
<property>
  <name>http.content.limit</name>
  <value>-1</value>
</property>
修改regex-urlfilter.txt，将
# accept anything else
+.
替换为：
+^http://([a-z0-9]*\.)*news.163.com/
-.
8、开发调试
在左部Package Explorer的 nutch1.5.1文件夹上单击右键 > New > Folder > Folder name: urls
在刚新建的urls目录下新建一个文本文件url，文本内容为：http://news.163.com
打开src/java下的org.apache.nutch.crawl.Crawl.java类，单击右键Run As > Run Configurations > Arguments > 在Program arguments输入框中输入: urls -dir data -depth 3 > Run
在需要调试的地方打上断点Debug As > Java Applicaton
9、查看结果
查看segments目录：
打开src/java下的org.apache.nutch.segment.SegmentReader.java类
单击右键Run As > Java Applicaton，控制台会输出该命令的使用方法
单击右键Run As > Run Configurations > Arguments > 在Program arguments输入框中输入: -dump data/segments/*  data/segments/dump
用文本编辑器打开文件data/segments/dump/dump查看segments中存储的信息

查看crawldb目录：
打开src/java下的org.apache.nutch.crawl.CrawlDbReader.java类
单击右键Run As > Java Applicaton，控制台会输出该命令的使用方法
单击右键Run As > Run Configurations > Arguments > 在Program arguments输入框中输入: data/crawldb -stats
控制台会输出 crawldb统计信息

查看linkdb目录：
打开src/java下的org.apache.nutch.crawl.LinkDbReader.java类
单击右键Run As > Java Applicaton，控制台会输出该命令的使用方法
单击右键Run As > Run Configurations > Arguments > 在Program arguments输入框中输入: data/linkdb -dump data/linkdb_dump
用文本编辑器打开文件data/linkdb_dump/part-00000查看linkdb中存储的信息
10、全网分步骤抓取
在左部Package Explorer的 nutch1.5.1文件夹下的build.xml文件上单击右键 > Run As > Ant Build
cd  /home/ysc/workspace/nutch1.5.1/runtime/local
#准备URL列表
wget http://rdf.dmoz.org/rdf/content.rdf.u8.gz
gunzip content.rdf.u8.gz
mkdir dmoz
bin/nutch org.apache.nutch.tools.DmozParser content.rdf.u8 -subset 5000 > dmoz/url
#注入URL
bin/nutch inject crawl/crawldb dmoz
#生成抓取列表
bin/nutch generate crawl/crawldb crawl/segments
#第一次抓取
s1=`ls -d crawl/segments/2* | tail -1`
echo $s1
#抓取网页
bin/nutch fetch $s1
#解析网页
bin/nutch parse $s1
#更新URL状态
bin/nutch updatedb crawl/crawldb $s1
#第二次抓取
bin/nutch generate crawl/crawldb crawl/segments -topN 1000
s2=`ls -d crawl/segments/2* | tail -1`
echo $s2
bin/nutch fetch $s2
bin/nutch parse $s2
bin/nutch updatedb crawl/crawldb $s2
#第三次抓取
bin/nutch generate crawl/crawldb crawl/segments -topN 1000
s3=`ls -d crawl/segments/2* | tail -1`
echo $s3
bin/nutch fetch $s3
bin/nutch parse $s3
bin/nutch updatedb crawl/crawldb $s3
#生成反向链接库
bin/nutch invertlinks crawl/linkdb -dir crawl/segments

11、索引和搜索
cd  /home/ysc/
wget http://mirror.bjtu.edu.cn/apache/lucene/solr/3.6.1/apache-solr-3.6.1.tgz
tar -xvf apache-solr-3.6.1.tgz
cd apache-solr-3.6.1 /example

NUTCH_RUNTIME_HOME=/home/ysc/workspace/nutch1.5.1/runtime/local
APACHE_SOLR_HOME=/home/ysc/apache-solr-3.6.1

cp ${NUTCH_RUNTIME_HOME}/conf/schema.xml ${APACHE_SOLR_HOME}/example/solr/conf/
如果需要把网页内容存储到索引中，则修改 schema.xml文件中的
<field name="content" type="text" stored="false" indexed="true"/>
为
<field name="content" type="text" stored="true" indexed="true"/>

修改${APACHE_SOLR_HOME}/example/solr/conf/solrconfig.xml,将里面的<str name="df">text</str>都替换为<str name="df">content</str>

把${APACHE_SOLR_HOME}/example/solr/conf/schema.xml中的 <schema name="nutch" version="1.5.1">修改为<schema name="nutch" version="1.5">
#启动SOLR服务器
java -jar start.jar

http://127.0.0.1:8983/solr/admin/
http://127.0.0.1:8983/solr/admin/stats.jsp

cd  /home/ysc/workspace/nutch1.5.1/runtime/local
#提交索引
bin/nutch solrindex http://127.0.0.1:8983/solr/ crawl/crawldb -linkdb crawl/linkdb crawl/segments/*

执行完整crawl:
bin/nutch crawl urls -dir data -depth 2 -topN 100 -solr http://127.0.0.1:8983/solr/

使用以下命令分页查看所有索引的文档：
http://127.0.0.1:8983/solr/select/?q=*%3A*&version=2.2&start=0&rows=10&indent=on
标题包含“网易”的文档：
http://127.0.0.1:8983/solr/select/?q=title%3A%E7%BD%91%E6%98%93&version=2.2&start=0&rows=10&indent=on

12、查看索引信息
cd  /home/ysc/
wget http://luke.googlecode.com/files/lukeall-3.5.0.jar
java -jar lukeall-3.5.0.jar
Path: /home/ysc/apache-solr-3.6.1/example/solr/data

13、配置SOLR的中文分词
cd  /home/ysc/
wget http://mmseg4j.googlecode.com/files/mmseg4j-1.8.5.zip
unzip mmseg4j-1.8.5.zip -d  mmseg4j-1.8.5

APACHE_SOLR_HOME=/home/ysc/apache-solr-3.6.1
mkdir $APACHE_SOLR_HOME/example/solr/lib
mkdir $APACHE_SOLR_HOME/example/solr/dic
cp mmseg4j-1.8.5/mmseg4j-all-1.8.5.jar $APACHE_SOLR_HOME/example/solr/lib
cp mmseg4j-1.8.5/data/*.dic $APACHE_SOLR_HOME/example/solr/dic

将${APACHE_SOLR_HOME}/example/solr/conf/schema.xml文件中的
<tokenizer class="solr.WhitespaceTokenizerFactory"/>
和
<tokenizer class="solr.StandardTokenizerFactory"/>
替换为
<tokenizer class="com.chenlb.mmseg4j.solr.MMSegTokenizerFactory" mode="complex" dicPath="/home/ysc/apache-solr-3.6.1/example/solr/dic"/>

#重新启动SOLR服务器
java -jar start.jar

#重建索引，演示在开发环境中如何操作
打开src/java下的org.apache.nutch.indexer.solr.SolrIndexer.java类
单击右键Run As > Java Applicaton，控制台会输出该命令的使用方法
单击右键Run As > Run Configurations > Arguments > 在Program arguments输入框中输入: http://127.0.0.1:8983/solr/  data/crawldb -linkdb  data/linkdb  data/segments/*
使用luke重新打开索引就会发现分词起作用了

三、nutch2.0
nutch2.0和二中的nutch1.5.1的步骤相同，但在8、开发调试之前需要做以下配置：
在左部Package Explorer的 nutch2.0文件夹上单击右键 > New > Folder > Folder name: data并指定数据存储方式，选如下之一：
1、使用mysql作为数据存储
  1）、在nutch2.0/conf/nutch-site.xml中加入如下配置：
<property>
  <name>storage.data.store.class</name>
  <value>org.apache.gora.sql.store.SqlStore</value>
</property>
  2）、将nutch2.0/conf/gora.properties文件中的 
  gora.sqlstore.jdbc.driver=org.hsqldb.jdbc.JDBCDriver
gora.sqlstore.jdbc.url=jdbc:hsqldb:hsql://localhost/nutchtest
gora.sqlstore.jdbc.user=sa
gora.sqlstore.jdbc.password=
  修改为
  gora.sqlstore.jdbc.driver=com.mysql.jdbc.Driver
gora.sqlstore.jdbc.url=jdbc:mysql://127.0.0.1:3306/nutch2
gora.sqlstore.jdbc.user=root
gora.sqlstore.jdbc.password=ROOT
  3）、打开nutch2.0/ivy/ivy.xml中的mysql-connector-java依赖
  4）、sudo apt-get install mysql-server
2、使用hbase作为数据存储
  1）、在nutch2.0/conf/nutch-site.xml中加入如下配置：
<property>
  <name>storage.data.store.class</name>
  <value>org.apache.gora.hbase.store.HBaseStore</value>
</property>
  2）、打开nutch2.0/ivy/ivy.xml中的gora-hbase依赖
  3）、cd /home/ysc
  4）、wget http://mirror.bit.edu.cn/apache/hbase/hbase-0.90.5/hbase-0.90.5.tar.gz
  5）、tar -xvf hbase-0.90.5.tar.gz
  6）、vi  hbase-0.90.5/conf/hbase-site.xml
   加入以下配置：
  <property>
    <name>hbase.rootdir</name>
    <value>file:///home/ysc/hbase-0.90.5-database</value>
  </property>
7)、hbase-0.90.5/bin/start-hbase.sh
8)、将/home/ysc/hbase-0.90.5/hbase-0.90.5.jar加入开发环境eclipse的build path

四、配置SSH
三台机器 devcluster01， devcluster02， devcluster03，分别在每一台机器上面执行如下操作：
1、sudo vi /etc/hosts
加入以下配置：
192.168.1.1 devcluster01
192.168.1.2 devcluster02
192.168.1.3 devcluster03
2、安装SSH服务：
  sudo apt-get install openssh-server
3、(有提示的时候回车键确认）
  ssh-keygen -t rsa
  该命令会在用户主目录下创建 .ssh 目录，并在其中创建两个文件：id_rsa 私钥文件。是基于 RSA 算法创建。该私钥文件要妥善保管，不要泄漏。id_rsa.pub 公钥文件。和 id_rsa 文件是一对儿，该文件作为公钥文件，可以公开。
4、cp .ssh/id_rsa.pub .ssh/authorized_keys
把 三台机器 devcluster01， devcluster02， devcluster03 的文件/home/ysc/.ssh/authorized_keys的内容复制出来合并成一个文件并替换每一台机器上的/home/ysc/.ssh/authorized_keys文件
在devcluster01上面执行时，以下两条命令的主机为02和03
在devcluster02上面执行时，以下两条命令的主机为01和03
在devcluster03上面执行时，以下两条命令的主机为01和02
5、ssh-copy-id -i .ssh/id_rsa.pub ysc@ devcluster02
6、ssh-copy-id -i .ssh/id_rsa.pub ysc@ devcluster03
以上两条命令实际上是将 .ssh/id_rsa.pub 公钥文件追加到远程主机 server 的 user 主目录下的 .ssh/authorized_keys 文件中。

五、安装Hadoop Cluster（伪分布式运行模式）并运行Nutch
步骤和四大同小异，只需要1台机器 devcluster01，所以黄色背景部分全部设置为devcluster01，不需要第11步

六、安装Hadoop Cluster（分布式运行模式）并运行Nutch
三台机器 devcluster01， devcluster02， devcluster03(vi /etc/hostname)
使用用户ysc登陆 devcluster01：
1、cd /home/ysc
2、wget http://mirrors.tuna.tsinghua.edu.cn/apache/hadoop/common/hadoop-1.1.1/hadoop-1.1.1-bin.tar.gz
3、tar -xvf hadoop-1.1.1-bin.tar.gz
4、cd  hadoop-1.1.1
5、vi conf/masters
  替换内容为 ：
  devcluster01
6、vi conf/slaves
  替换内容为 ：
  devcluster02
  devcluster03
7、vi conf/core-site.xml
  加入配置：
  <property>
    <name>fs.default.name</name>
    <value>hdfs://devcluster01:9000</value>
    <description>
       Where to find the Hadoop Filesystem through the network.
       Note 9000 is not the default port.
       (This is slightly changed from previous versions which didnt have "hdfs")
    </description>
  </property>
    <property>
     <name>hadoop.security.authorization</name>
      <value>true</value>
    </property>
编辑conf/hadoop-policy.xml
8、vi conf/hdfs-site.xml
  加入配置：
<property>
  <name>dfs.name.dir</name>
  <value>/home/ysc/dfs/filesystem/name</value>
</property>

<property>
  <name>dfs.data.dir</name>
  <value>/home/ysc/dfs/filesystem/data</value>
</property>

<property>
  <name>dfs.replication</name>
  <value>1</value>
</property>

<property>
  <name>dfs.block.size</name>
  <value>671088640</value>
  <description>The default block size for new files.</description>
</property>
9、vi conf/mapred-site.xml
  加入配置：
<property>
  <name>mapred.job.tracker</name>
  <value>devcluster01:9001</value>
  <description>
    The host and port that the MapReduce job tracker runs at. If
    "local", then jobs are run in-process as a single map and
    reduce task.
    Note 9001 is not the default port.
  </description>
</property>

<property>
  <name>mapred.reduce.tasks.speculative.execution</name>
  <value>false</value>
  <description>If true, then multiple instances of some reduce tasks
               may be executed in parallel.</description>
</property>

<property>
  <name>mapred.map.tasks.speculative.execution</name>
  <value>false</value>
  <description>If true, then multiple instances of some map tasks
               may be executed in parallel.</description>
</property>

<property>
  <name>mapred.child.java.opts</name>
  <value>-Xmx2000m</value>
</property>

<property>
  <name>mapred.tasktracker.map.tasks.maximum</name>
  <value>4</value>
  <description>
    the core number of host
  </description>
</property>

<property>
  <name>mapred.map.tasks</name>
  <value>4</value>
</property>

<property>
  <name>mapred.tasktracker.reduce.tasks.maximum</name>
  <value>4</value>
    <description>
    define mapred.map tasks to be number of slave hosts.the best number is the  number of slave hosts plus the core numbers of per host
    </description>
</property>

<property>
  <name>mapred.reduce.tasks</name>
  <value>4</value>
  <description>
    define mapred.reduce tasks to be number of slave hosts.the best number is the  number of slave hosts plus the core numbers of per host
  </description>
</property>

<property>
  <name>mapred.output.compression.type</name>
  <value>BLOCK</value>
  <description>If the job outputs are to compressed as SequenceFiles, how should they be compressed? Should be one of NONE, RECORD or BLOCK.
  </description>
</property>

<property>
  <name>mapred.output.compress</name>
  <value>true</value>
  <description>Should the job outputs be compressed?
  </description>
</property>

<property>
  <name>mapred.compress.map.output</name>
  <value>true</value>
  <description>Should the outputs of the maps be compressed before being                sent across the network. Uses SequenceFile compression.
  </description>
</property>

<property>
  <name>mapred.system.dir</name>
  <value>/home/ysc/mapreduce/system</value>
</property>

<property>
  <name>mapred.local.dir</name>
  <value>/home/ysc/mapreduce/local</value>
</property>
10、vi conf/hadoop-env.sh
  追加：
export JAVA_HOME=/home/ysc/jdk1.7.0_05
  export HADOOP_HEAPSIZE=2000
  #替换掉默认的垃圾回收器，因为默认的垃圾回收器在多线程环境下会有更多的wait等待
  export HADOOP_OPTS="-server -Xmn256m -XX:+UseParNewGC -XX:+UseConcMarkSweepGC -XX:CMSInitiatingOccupancyFraction=70"
11、复制HADOOP文件
  scp -r /home/ysc/hadoop-1.1.1 ysc@devcluster02:/home/ysc/hadoop-1.1.1
  scp -r /home/ysc/hadoop-1.1.1 ysc@devcluster03:/home/ysc/hadoop-1.1.1
12、sudo vi /etc/profile
  追加并重启系统：
  export PATH=/home/ysc/hadoop-1.1.1/bin:$PATH
13、格式化名称节点并启动集群
  hadoop namenode -format
  start-all.sh
14、cd /home/ysc/workspace/nutch1.5.1/runtime/deploy
  mkdir urls
  echo http://news.163.com > urls/url
  hadoop dfs -put urls urls
  bin/nutch crawl urls -dir data -depth 2 -topN 100
15、访问 http://localhost:50030 可以查看 JobTracker 的运行状态。访问 http://localhost:50060 可以查看 TaskTracker 的运行状态。访问 http://localhost:50070 可以查看 NameNode 以及整个分布式文件系统的状态，浏览分布式文件系统中的文件以及 log 等
16、通过stop-all.sh停止集群
17、如果NameNode和SecondaryNameNode不在同一台机器上，则在SecondaryNameNode的conf/hdfs-site.xml文件中加入配置：
   <property>
     <name>dfs.http.address</name>
     <value>namenode:50070</value>
   </property>

七、配置Ganglia监控Hadoop集群和HBase集群
1、服务器端（安装到master devcluster01上）
  1）、ssh devcluster01
  2）、addgroup ganglia
           adduser --ingroup ganglia ganglia
  3）、sudo apt-get install  ganglia-monitor ganglia-webfront gmetad
   //补充：在Ubuntu10.04上，ganglia-webfront这个package名字叫ganglia-webfrontend
   //如果install出错，则运行sudo apt-get update，如果update出错，则删除出错路径
  4）、vi /etc/ganglia/gmond.conf
   先找到setuid = yes,改成setuid =no;
   在找到cluster块中的name，改成name =”hadoop-cluster”;
  5）、sudo apt-get install rrdtool
  6)、vi /etc/ganglia/gmetad.conf
   在这个配置文件中增加一些datasource，即其他2个被监控的节点，增加以下内容：
   data_source “hadoop-cluster” devcluster01:8649 devcluster02:8649 devcluster03:8649
   gridname "Hadoop"
2、数据源端（安装到所有slaves上）
  1)、ssh devcluster02
   addgroup ganglia
   adduser --ingroup ganglia ganglia
   sudo apt-get install  ganglia-monitor

  2)、ssh devcluster03
   addgroup ganglia
   adduser --ingroup ganglia ganglia
   sudo apt-get install  ganglia-monitor

  3）、ssh devcluster01
   scp /etc/ganglia/gmond.conf devcluster02:/etc/ganglia/gmond.conf
   scp /etc/ganglia/gmond.conf devcluster03:/etc/ganglia/gmond.conf
3、配置WEB
  1）、ssh devcluster01
  2）、sudo ln -s /usr/share/ganglia-webfrontend /var/www/ganglia
  3）、vi /etc/apache2/apache2.conf
   添加：
   ServerName devcluster01
4、重启服务
  1）、ssh devcluster02
   sudo /etc/init.d/ganglia-monitor restart
   ssh devcluster03
   sudo /etc/init.d/ganglia-monitor restart
  2）、ssh devcluster01
   sudo /etc/init.d/ganglia-monitor restart
   sudo /etc/init.d/gmetad restart
   sudo /etc/init.d/apache2 restart
5、访问页面
  http:// devcluster01/ganglia
6、集成hadoop
  1）、ssh devcluster01
  2）、cd /home/ysc/hadoop-1.1.1
  3）、vi conf/hadoop-metrics2.properties
  # 大于0.20以后的版本用ganglia31  *.sink.ganglia.class=org.apache.hadoop.metrics2.sink.ganglia.GangliaSink31
  *.sink.ganglia.period=10
  # default for supportsparse is false
  *.sink.ganglia.supportsparse=true
*.sink.ganglia.slope=jvm.metrics.gcCount=zero,jvm.metrics.memHeapUsedM=both
*.sink.ganglia.dmax=jvm.metrics.threadsBlocked=70,jvm.metrics.memHeapUsedM=40
  #广播IP地址，这是缺省的，统一设该值(只能用组播地址239.2.11.71)
  namenode.sink.ganglia.servers=239.2.11.71:8649
  datanode.sink.ganglia.servers=239.2.11.71:8649
  jobtracker.sink.ganglia.servers=239.2.11.71:8649
  tasktracker.sink.ganglia.servers=239.2.11.71:8649
  maptask.sink.ganglia.servers=239.2.11.71:8649
  reducetask.sink.ganglia.servers=239.2.11.71:8649
  dfs.class=org.apache.hadoop.metrics.ganglia.GangliaContext31
  dfs.period=10
  dfs.servers=239.2.11.71:8649
  mapred.class=org.apache.hadoop.metrics.ganglia.GangliaContext31
  mapred.period=10
  mapred.servers=239.2.11.71:8649
  jvm.class=org.apache.hadoop.metrics.ganglia.GangliaContext31
  jvm.period=10
  jvm.servers=239.2.11.71:8649
  4）、scp conf/hadoop-metrics2.properties root@devcluster02:/home/ysc/hadoop-1.1.1/conf/hadoop-metrics2.properties
  5）、scp conf/hadoop-metrics2.properties root@devcluster03:/home/ysc/hadoop-1.1.1/conf/hadoop-metrics2.properties
  6）、stop-all.sh
  7）、start-all.sh
7、集成hbase
  1）、ssh devcluster01
  2）、cd /home/ysc/hbase-0.92.2
  3）、vi conf/hadoop-metrics.properties(只能用组播地址239.2.11.71)
   hbase.extendedperiod = 3600
   hbase.class=org.apache.hadoop.metrics.ganglia.GangliaContext31
   hbase.period=10
   hbase.servers=239.2.11.71:8649
   jvm.class=org.apache.hadoop.metrics.ganglia.GangliaContext31
   jvm.period=10
   jvm.servers=239.2.11.71:8649
   rpc.class=org.apache.hadoop.metrics.ganglia.GangliaContext31
   rpc.period=10
   rpc.servers=239.2.11.71:8649
  4）、scp conf/hadoop-metrics.properties root@devcluster02:/home/ysc/ hbase-0.92.2/conf/hadoop-metrics.properties
  5）、scp conf/hadoop-metrics.properties root@devcluster03:/home/ysc/ hbase-0.92.2/conf/hadoop-metrics.properties
  6）、stop-hbase.sh
  7）、start-hbase.sh

八、Hadoop配置Snappy压缩
1、wget http://snappy.googlecode.com/files/snappy-1.0.5.tar.gz
2、tar -xzvf snappy-1.0.5.tar.gz
3、cd snappy-1.0.5
4、./configure
5、make
6、make install
7、scp /usr/local/lib/libsnappy* devcluster01:/home/ysc/hadoop-1.1.1/lib/native/Linux-amd64-64/
scp /usr/local/lib/libsnappy* devcluster02:/home/ysc/hadoop-1.1.1/lib/native/Linux-amd64-64/
scp /usr/local/lib/libsnappy* devcluster03:/home/ysc/hadoop-1.1.1/lib/native/Linux-amd64-64/
8、vi /etc/profile
  追加：
  export LD_LIBRARY_PATH=/home/ysc/hadoop-1.1.1/lib/native/Linux-amd64-64
9、修改mapred-site.xml
  <property>
    <name>mapred.output.compression.type</name>
    <value>BLOCK</value>
    <description>If the job outputs are to compressed as SequenceFiles, how should
        they be compressed? Should be one of NONE, RECORD or BLOCK.
    </description>
  </property>

  <property>
    <name>mapred.output.compress</name>
    <value>true</value>
    <description>Should the job outputs be compressed?
    </description>
  </property>

  <property>
    <name>mapred.compress.map.output</name>
    <value>true</value>
    <description>Should the outputs of the maps be compressed before being
        sent across the network. Uses SequenceFile compression.
    </description>
  </property>

  <property>
    <name>mapred.map.output.compression.codec</name>
    <value>org.apache.hadoop.io.compress.SnappyCodec</value>
    <description>If the map outputs are compressed, how should they be
        compressed?
    </description>
  </property>

  <property>
    <name>mapred.output.compression.codec</name>
    <value>org.apache.hadoop.io.compress.SnappyCodec</value>
    <description>If the job outputs are compressed, how should they be compressed?
    </description>
  </property>

九、Hadoop配置Lzo压缩
1、wget http://www.oberhumer.com/opensource/lzo/download/lzo-2.06.tar.gz
2、tar -zxvf lzo-2.06.tar.gz
3、cd lzo-2.06
4、./configure --enable-shared
5、make
6、make install
7、scp /usr/local/lib/liblzo2.* devcluster01:/lib/x86_64-linux-gnu
scp /usr/local/lib/liblzo2.* devcluster02:/lib/x86_64-linux-gnu
scp /usr/local/lib/liblzo2.* devcluster03:/lib/x86_64-linux-gnu
8、wget http://hadoop-gpl-compression.apache-extras.org.codespot.com/files/hadoop-gpl-compression-0.1.0-rc0.tar.gz
9、tar -xzvf hadoop-gpl-compression-0.1.0-rc0.tar.gz
10、cd hadoop-gpl-compression-0.1.0
11、cp lib/native/Linux-amd64-64/* /home/ysc/hadoop-1.1.1/lib/native/Linux-amd64-64/
12、cp hadoop-gpl-compression-0.1.0.jar /home/ysc/hadoop-1.1.1/lib/(这里hadoop集群的版本要和compression使用的版本一致)
13、scp -r /home/ysc/hadoop-1.1.1/lib devcluster02:/home/ysc/hadoop-1.1.1/
scp -r /home/ysc/hadoop-1.1.1/lib devcluster03:/home/ysc/hadoop-1.1.1/
14、vi /etc/profile
  追加：
  export LD_LIBRARY_PATH=/home/ysc/hadoop-1.1.1/lib/native/Linux-amd64-64
15、修改core-site.xml
  <property>
    <name>io.compression.codecs</name>
    <value>com.hadoop.compression.lzo.LzoCodec,org.apache.hadoop.io.compress.DefaultCodec,org.apache.hadoop.io.compress.GzipCodec,org.apache.hadoop.io.compress.BZip2Codec,org.apache.hadoop.io.compress.SnappyCodec</value>
    <description>A list of the compression codec classes that can be used
        for compression/decompression.</description>
  </property>

  <property>
    <name>io.compression.codec.lzo.class</name>
    <value>com.hadoop.compression.lzo.LzoCodec</value>
  </property>

  <property>
    <name>fs.trash.interval</name>
    <value>1440</value>
    <description>Number of minutes between trash checkpoints.
    If zero, the trash feature is disabled.
    </description>
  </property>
16、修改mapred-site.xml
  <property>
    <name>mapred.output.compression.type</name>
    <value>BLOCK</value>
    <description>If the job outputs are to compressed as SequenceFiles, how should
        they be compressed? Should be one of NONE, RECORD or BLOCK.
    </description>
  </property>

  <property>
    <name>mapred.output.compress</name>
    <value>true</value>
    <description>Should the job outputs be compressed?
    </description>
  </property>

  <property>
    <name>mapred.compress.map.output</name>
    <value>true</value>
    <description>Should the outputs of the maps be compressed before being
        sent across the network. Uses SequenceFile compression.
    </description>
  </property>

  <property>
    <name>mapred.map.output.compression.codec</name>
    <value>com.hadoop.compression.lzo.LzoCodec</value>
    <description>If the map outputs are compressed, how should they be
        compressed?
    </description>
  </property>

  <property>
    <name>mapred.output.compression.codec</name>
    <value>com.hadoop.compression.lzo.LzoCodec</value>
    <description>If the job outputs are compressed, how should they be compressed?
    </description>
  </property>

十、配置zookeeper集群以运行hbase
1、ssh devcluster01
2、cd /home/ysc
3、wget http://mirror.bjtu.edu.cn/apache/zookeeper/stable/zookeeper-3.4.5.tar.gz
4、tar -zxvf  zookeeper-3.4.5.tar.gz
5、cd zookeeper-3.4.5
6、cp conf/zoo_sample.cfg  conf/zoo.cfg
7、vi conf/zoo.cfg
  修改：dataDir=/home/ysc/zookeeper
  添加：
   server.1=devcluster01:2888:3888
   server.2=devcluster02:2888:3888
   server.3=devcluster03:2888:3888
   maxClientCnxns=100
8、scp -r  zookeeper-3.4.5  devcluster01:/home/ysc
scp -r  zookeeper-3.4.5  devcluster02:/home/ysc
scp -r  zookeeper-3.4.5  devcluster03:/home/ysc
9、分别在三台机器上面执行：
  ssh devcluster01
  mkdir /home/ysc/zookeeper（注：dataDir是zookeeper的数据目录，需要手动创建）
  echo 1 > /home/ysc/zookeeper/myid
  ssh devcluster02
  mkdir /home/ysc/zookeeper
  echo 2 > /home/ysc/zookeeper/myid
  ssh devcluster03
  mkdir /home/ysc/zookeeper
  echo 3 > /home/ysc/zookeeper/myid
10、分别在三台机器上面执行：
  cd /home/ysc/zookeeper-3.4.5
  bin/zkServer.sh start
  bin/zkCli.sh -server devcluster01:2181
  bin/zkServer.sh status

十一、配置Hbase集群以运行nutch-2.1(Region Servers会因为内存的问题宕机)
1、nutch-2.1使用gora-0.2.1， gora-0.2.1使用hbase-0.90.4，hbase-0.90.4和hadoop-1.1.1不兼容，hbase-0.94.4和gora-0.2.1不兼容，hbase-0.92.2没问题。hbase存在系统时间同步的问题，并且误差要再30s以内。
sudo apt-get install ntp
sudo ntpdate -u 210.72.145.44
2、HBase是数据库，会在同一时间使用很多的文件句柄。大多数linux系统使用的默认值1024是不能满足的。还需要修改 hbase 用户的 nproc，在压力下，如果过低会造成 OutOfMemoryError异常。
vi /etc/security/limits.conf
添加：
   ysc soft nproc 32000
   ysc hard nproc 32000
   ysc soft nofile 32768
   ysc hard nofile 32768
vi /etc/pam.d/common-session
添加：
   session required  pam_limits.so
3、登陆master，下载并解压hbase
  ssh devcluster01
  cd /home/ysc
  wget http://apache.etoak.com/hbase/hbase-0.92.2/hbase-0.92.2.tar.gz
  tar -zxvf hbase-0.92.2.tar.gz
  cd hbase-0.92.2
4、修改配置文件hbase-env.sh
  vi conf/hbase-env.sh
  追加：
  export JAVA_HOME=/home/ysc/jdk1.7.0_05
  export HBASE_MANAGES_ZK=false
  export HBASE_HEAPSIZE=10000
  #替换掉默认的垃圾回收器，因为默认的垃圾回收器在多线程环境下会有更多的wait等待
  export HBASE_OPTS="-server -Xmn256m -XX:+UseParNewGC -XX:+UseConcMarkSweepGC -XX:CMSInitiatingOccupancyFraction=70"
5、修改配置文件hbase-site.xml
  vi conf/hbase-site.xml
  <property> 
   <name>hbase.rootdir</name> 
   <value>hdfs://devcluster01:9000/hbase</value>    
  </property>
  <property> 
   <name>hbase.cluster.distributed</name> 
   <value>true</value> 
  </property> 
  <property>  
   <name>hbase.zookeeper.quorum</name>       
   <value>devcluster01,devcluster02,devcluster03</value>  
  </property>
  <property>
   <name>hfile.block.cache.size</name>
   <value>0.25</value>
   <description>
    Percentage of maximum heap (-Xmx setting) to allocate to block cache
    used by HFile/StoreFile. Default of 0.25 means allocate 25%.
    Set to 0 to disable but it's not recommended.
   </description>
  </property>
  <property>
   <name>hbase.regionserver.global.memstore.upperLimit</name>
   <value>0.4</value>
   <description>Maximum size of all memstores in a region server before new
     updates are blocked and flushes are forced. Defaults to 40% of heap
   </description>
  </property>
    <property>
   <name>hbase.regionserver.global.memstore.lowerLimit</name>
   <value>0.35</value>
   <description>When memstores are being forced to flush to make room in
    memory, keep flushing until we hit this mark. Defaults to 35% of heap.
    This value equal to hbase.regionserver.global.memstore.upperLimit causes
    the minimum possible flushing to occur when updates are blocked due to
    memstore limiting.
   </description>
    </property>
  <property>
   <name>hbase.hregion.majorcompaction</name>
   <value>0</value>
   <description>The time (in miliseconds) between 'major' compactions of all
    HStoreFiles in a region.  Default: 1 day.
    Set to 0 to disable automated major compactions.
   </description>
  </property>
6、修改配置文件regionservers
  vi conf/regionservers
  devcluster01
  devcluster02
  devcluster03
7、因为HBase建立在Hadoop之上，Hadoop使用的hadoop*.jar和HBase使用的 必须 一致。所以要将 HBase lib 目录下的hadoop*.jar替换成Hadoop里面的那个，防止版本冲突。
  cp  /home/ysc/hadoop-1.1.1/hadoop-core-1.1.1.jar  /home/ysc/hbase-0.92.2/lib
  rm  /home/ysc/hbase-0.92.2/lib/hadoop-core-1.0.3.jar
8、复制文件到regionservers
  scp -r /home/ysc/hbase-0.92.2 devcluster01:/home/ysc
  scp -r /home/ysc/hbase-0.92.2 devcluster02:/home/ysc
  scp -r /home/ysc/hbase-0.92.2 devcluster03:/home/ysc
9、启动hadoop并创建目录
  hadoop fs -mkdir /hbase
10、管理HBase集群:
  启动初始 HBase 集群：
   bin/start-hbase.sh
  停止HBase 集群：
   bin/stop-hbase.sh
  启动额外备份主服务器，可以启动到 9 个备份服务器 (总数10 个)：
   bin/local-master-backup.sh start 1
   bin/local-master-backup.sh start 2 3
  启动更多 regionservers, 支持到 99 个额外regionservers (总100个)：
   bin/local-regionservers.sh start 1
   bin/local-regionservers.sh start 2 3 4 5
  停止备份主服务器:
   cat /tmp/hbase-ysc-1-master.pid |xargs kill -9
  停止单独 regionserver：
   bin/local-regionservers.sh stop 1
  使用HBase命令行模式:
   bin/hbase shell
11、web界面
  http://devcluster01:60010
  http://devcluster01:60030
12、如运行nutch2.1则方法一：
  cp conf/hbase-site.xml /home/ysc/nutch-2.1/conf
  cd /home/ysc/nutch-2.1
  ant
  cd runtime/deploy
  unzip -d apache-nutch-2.1 apache-nutch-2.1.job
  rm  apache-nutch-2.1.job
  cd apache-nutch-2.1
  rm lib/hbase-0.90.4.jar
  cp /home/ysc/hbase-0.92.2/hbase-0.92.2.jar  lib
  zip -r ../apache-nutch-2.1.job ./*
  cd ..
  rm -r apache-nutch-2.1
13、如运行nutch2.1则方法二：
  cp conf/hbase-site.xml /home/ysc/nutch-2.1/conf
  cd /home/ysc/nutch-2.1
  cp /home/ysc/hbase-0.92.2/hbase-0.92.2.jar  lib
  ant
  cd runtime/deploy
  zip -d apache-nutch-2.1.job lib/hbase-0.90.4.jar

启用snappy压缩：
1、vi conf/gora-hbase-mapping.xml
  在family上面添加属性：compression="SNAPPY"
2、mkdir /home/ysc/hbase-0.92.2/lib/native/Linux-amd64-64
3、cp /home/ysc/hadoop-1.1.1/lib/native/Linux-amd64-64/* /home/ysc/hbase-0.92.2/lib/native/Linux-amd64-64
4、vi /home/ysc/hbase-0.92.2/conf/hbase-site.xml
  增加：
                <property>
                        <name>hbase.regionserver.codecs</name>
                        <value>snappy</value>
                </property>



十二、配置Accumulo集群以运行nutch-2.1(gora存在BUG)
1、wget http://apache.etoak.com/accumulo/1.4.2/accumulo-1.4.2-dist.tar.gz
2、tar -xzvf accumulo-1.4.2-dist.tar.gz
3、cd accumulo-1.4.2
4、cp conf/examples/3GB/standalone/* conf
5、vi conf/accumulo-env.sh
  export HADOOP_HOME=/home/ysc/cluster3
  export ZOOKEEPER_HOME=/home/ysc/zookeeper-3.4.5
  export JAVA_HOME=/home/jdk1.7.0_01
  export ACCUMULO_HOME=/home/ysc/accumulo-1.4.2
6、vi conf/slaves
  devcluster01
  devcluster02
  devcluster03
7、vi conf/masters
  devcluster01
8、vi conf/accumulo-site.xml
  <property>
    <name>instance.zookeeper.host</name>
    <value>host6:2181,host8:2181</value>
    <description>comma separated list of zookeeper servers</description>
  </property>

  <property>
    <name>logger.dir.walog</name>
    <value>walogs</value>
    <description>The directory used to store write-ahead logs on the local filesystem. It is possible to specify a comma-separated list of directories.</description>
  </property>

  <property>
    <name>instance.secret</name>
    <value>ysc</value>
    <description>A secret unique to a given instance that all servers must know in order to communicate with one another.
        Change it before initialization. To change it later use ./bin/accumulo org.apache.accumulo.server.util.ChangeSecret [oldpasswd] [newpasswd],
        and then update this file.
    </description>
  </property>

  <property>
    <name>tserver.memory.maps.max</name>
    <value>3G</value>
  </property>

  <property>
    <name>tserver.cache.data.size</name>
    <value>50M</value>
  </property>

  <property>
    <name>tserver.cache.index.size</name>
    <value>512M</value>
  </property>

  <property>
    <name>trace.password</name>
    <!--
   change this to the root user's password, and/or change the user below
     -->
    <value>ysc</value>
  </property>

  <property>
    <name>trace.user</name>
    <value>root</value>
  </property>
9、bin/accumulo init
10、bin/start-all.sh
11、bin/stop-all.sh
12、web访问：http://devcluster01:50095/

修改nutch2.1：
1、cd  /home/ysc/nutch-2.1
2、vi  conf/gora.properties
  增加：
  gora.datastore.default=org.apache.gora.accumulo.store.AccumuloStore
  gora.datastore.accumulo.mock=false
  gora.datastore.accumulo.instance=accumulo
  gora.datastore.accumulo.zookeepers=host6,host8
  gora.datastore.accumulo.user=root
  gora.datastore.accumulo.password=ysc
3、vi  conf/nutch-site.xml
  增加：
  <property>
    <name>storage.data.store.class</name>
    <value>org.apache.gora.accumulo.store.AccumuloStore</value>
  </property>
4、vi ivy/ivy.xml
  增加：
  <dependency org="org.apache.gora" name="gora-accumulo" rev="0.2.1" conf="*->default" />
5、升级accumulo
  cp /home/ysc/accumulo-1.4.2/lib/accumulo-core-1.4.2.jar  /home/ysc/nutch-2.1/lib
  cp /home/ysc/accumulo-1.4.2/lib/accumulo-start-1.4.2.jar  /home/ysc/nutch-2.1/lib
  cp /home/ysc/accumulo-1.4.2/lib/cloudtrace-1.4.2.jar  /home/ysc/nutch-2.1/lib
6、ant
7、cd runtime/deploy
8、删除旧jar
  zip -d apache-nutch-2.1.job lib/accumulo-core-1.4.0.jar
  zip -d apache-nutch-2.1.job lib/accumulo-start-1.4.0.jar
  zip -d apache-nutch-2.1.job lib/cloudtrace-1.4.2.jar

十三、配置Cassandra 集群以运行nutch-2.1（Cassandra 采用去中心化结构）
1、vi /etc/hosts（注意：需要登录到每一台机器上面，将localhost解析到实际地址）
  192.168.1.1       localhost
2、wget http://labs.mop.com/apache-mirror/cassandra/1.2.0/apache-cassandra-1.2.0-bin.tar.gz
3、tar -xzvf  apache-cassandra-1.2.0-bin.tar.gz
4、cd apache-cassandra-1.2.0
5、vi conf/cassandra-env.sh
  增加：
  MAX_HEAP_SIZE="4G"
  HEAP_NEWSIZE="800M"
6、vi conf/log4j-server.properties
  修改：
  log4j.appender.R.File=/home/ysc/cassandra/system.log
7、vi conf/cassandra.yaml
  修改：
  cluster_name: 'Cassandra  Cluster'
  data_file_directories:
      - /home/ysc/cassandra/data
  commitlog_directory: /home/ysc/cassandra/commitlog
  saved_caches_directory: /home/ysc/cassandra/saved_caches

  - seeds: "192.168.1.1"
  listen_address: 192.168.1.1
  rpc_address: 192.168.1.1

  thrift_framed_transport_size_in_mb: 1023
  thrift_max_message_length_in_mb: 1024
8、vi bin/stop-server
  增加：
  user=`whoami`
  pgrep -u $user -f cassandra | xargs kill -9
9、复制cassandra到其他节点：
  cd ..
  scp -r apache-cassandra-1.2.0 devcluster02:/home/ysc
  scp -r apache-cassandra-1.2.0 devcluster03:/home/ysc
  分别在devcluster02和devcluster03上面修改：
  vi conf/cassandra.yaml
   listen_address: 192.168.1.2
   rpc_address: 192.168.1.2
  vi conf/cassandra.yaml
   listen_address: 192.168.1.3
   rpc_address: 192.168.1.3
10、分别在3个节点上面运行
  bin/cassandra
  bin/cassandra -f   参数 -f 的作用是让 Cassandra 以前端程序方式运行，这样有利于调试和观察日志信息，而在实际生产环境中这个参数是不需要的（即 Cassandra 会以 daemon 方式运行）
11、bin/nodetool -host devcluster01 ring
        bin/nodetool -host devcluster01 info
12、bin/stop-server
13、bin/cassandra-cli

修改nutch2.1：
1、cd  /home/ysc/nutch-2.1
2、vi  conf/gora.properties
  增加：
  gora.cassandrastore.servers=host2:9160,host6:9160,host8:9160
3、vi  conf/nutch-site.xml
  增加：
  <property>
    <name>storage.data.store.class</name>
    <value>org.apache.gora.cassandra.store.CassandraStore</value>
  </property>
4、vi ivy/ivy.xml
  增加：
  <dependency org="org.apache.gora" name="gora-cassandra" rev="0.2.1" conf="*->default" />
5、升级cassandra
  cp /home/ysc/apache-cassandra-1.2.0/lib/apache-cassandra-1.2.0.jar  /home/ysc/nutch-2.1/lib
  cp /home/ysc/apache-cassandra-1.2.0/lib/apache-cassandra-thrift-1.2.0.jar  /home/ysc/nutch-2.1/lib
  cp /home/ysc/apache-cassandra-1.2.0/lib/jline-1.0.jar  /home/ysc/nutch-2.1/lib
6、ant
7、cd runtime/deploy
8、删除旧jar
  zip -d apache-nutch-2.1.job lib/cassandra-thrift-1.1.2.jar
  zip -d apache-nutch-2.1.job lib/jline-0.9.1.jar

十四、配置MySQL 单机服务器以运行nutch-2.1
1、apt-get install mysql-server mysql-client
2、vi /etc/mysql/my.cnf
  修改：
  bind-address            = 221.194.43.2
  在[client]下增加：
  default-character-set=utf8
  在[mysqld]下增加：
  default-character-set=utf8
3、mysql –uroot –pysc
  SHOW VARIABLES LIKE '%character%';
4、service mysql restart
5、mysql –uroot –pysc
  GRANT ALL PRIVILEGES ON *.* TO root@"%" IDENTIFIED BY "ysc";
6、vi conf/gora-sql-mapping.xml
  修改字段的长度
  <primarykey column="id" length="333"/>
  <field name="content" column="content" />
  <field name="text" column="text" length="19892"/>
7、启动nutch之后登陆mysql
   ALTER TABLE webpage MODIFY COLUMN content MEDIUMBLOB;
   ALTER TABLE webpage MODIFY COLUMN text MEDIUMTEXT;
   ALTER TABLE webpage MODIFY COLUMN title MEDIUMTEXT;
   ALTER TABLE webpage MODIFY COLUMN reprUrl MEDIUMTEXT;
   ALTER TABLE webpage MODIFY COLUMN baseUrl MEDIUMTEXT;
   ALTER TABLE webpage MODIFY COLUMN typ MEDIUMTEXT;
   ALTER TABLE webpage MODIFY COLUMN inlinks MEDIUMBLOB;
   ALTER TABLE webpage MODIFY COLUMN outlinks MEDIUMBLOB;

修改nutch2.1：
1、cd  /home/ysc/nutch-2.1
2、vi  conf/gora.properties
  增加：
   gora.sqlstore.jdbc.driver=com.mysql.jdbc.Driver
gora.sqlstore.jdbc.url=jdbc:mysql://host2:3306/nutch?createDatabaseIfNotExist=true&useUnicode=true&characterEncoding=utf8
  gora.sqlstore.jdbc.user=root
  gora.sqlstore.jdbc.password=ysc
3、vi  conf/nutch-site.xml
  增加：
  <property>
    <name>storage.data.store.class</name>
    <value>org.apache.gora.sql.store.SqlStore </value>
  </property>

  <property>
    <name>encodingdetector.charset.min.confidence</name>
    <value>1</value>
    <description>A integer between 0-100 indicating minimum confidence value
    for charset auto-detection. Any negative value disables auto-detection.
    </description>
  </property>
4、vi ivy/ivy.xml
  增加：
  <dependency org="mysql" name="mysql-connector-java" rev="5.1.18" conf="*->default"/>

十五、nutch2.1 使用DataFileAvroStore作为数据源
1、cd  /home/ysc/nutch-2.1
2、vi  conf/gora.properties
  增加：
  gora.datafileavrostore.output.path=datafileavrostore
  gora.datafileavrostore.input.path=datafileavrostore
3、vi  conf/nutch-site.xml
  增加：
  <property>
    <name>storage.data.store.class</name>
    <value>org.apache.gora.avro.store.DataFileAvroStore</value>
  </property>

  <property>
    <name>encodingdetector.charset.min.confidence</name>
    <value>1</value>
    <description>A integer between 0-100 indicating minimum confidence value
    for charset auto-detection. Any negative value disables auto-detection.
    </description>
  </property>



十六、nutch2.1 使用AvroStore作为数据源
1、cd  /home/ysc/nutch-2.1
2、vi  conf/gora.properties
  增加：
  gora.avrostore.codec.type=BINARY
  gora.avrostore.input.path=avrostore
  gora.avrostore.output.path=avrostore
3、vi  conf/nutch-site.xml
  增加：
  <property>
    <name>storage.data.store.class</name>
    <value>org.apache.gora.avro.store.AvroStore</value>
  </property>

  <property>
    <name>encodingdetector.charset.min.confidence</name>
    <value>1</value>
    <description>A integer between 0-100 indicating minimum confidence value
    for charset auto-detection. Any negative value disables auto-detection.
    </description>
  </property>



十七、配置SOLR
配置tomcat：
1、wget http://www.fayea.com/apache-mirror/tomcat/tomcat-7/v7.0.35/bin/apache-tomcat-7.0.35.tar.gz
2、tar -xzvf apache-tomcat-7.0.35.tar.gz
3、cd apache-tomcat-7.0.35
4、vi conf/server.xml
增加URIEncoding="UTF-8"：
  <Connector port="8080" protocol="HTTP/1.1"
       connectionTimeout="20000"
       redirectPort="8443" URIEncoding="UTF-8"/>
5、mkdir conf/Catalina
6、mkdir conf/Catalina/localhost
7、vi conf/Catalina/localhost/solr.xml
增加：
  <Context path="/solr">
   <Environment name="solr/home" type="java.lang.String" value="/home/ysc/solr/configuration/" override="false"/>
  </Context>
8、cd ..

下载SOLR:
1、wget http://mirrors.tuna.tsinghua.edu.cn/apache/lucene/solr/4.1.0/solr-4.1.0.tgz
2、tar -xzvf solr-4.1.0.tgz

复制资源：
1、mkdir /home/ysc/solr
2、cp -r solr-4.1.0/example/solr  /home/ysc/solr/configuration
3、unzip solr-4.1.0/example/webapps/solr.war -d /home/ysc/apache-tomcat-7.0.35/webapps/solr

配置nutch：
1、复制schema：
  cp /home/ysc/nutch-1.6/conf/schema-solr4.xml /home/ysc/solr/configuration/collection1/conf/schema.xml
2、vi /home/ysc/solr/configuration/collection1/conf/schema.xml
  在<fields>下增加：
  <field name="_version_" type="long" indexed="true" stored="true"/>

配置中文分词：
1、wget http://mmseg4j.googlecode.com/files/mmseg4j-1.9.1.v20130120-SNAPSHOT.zip
2、unzip mmseg4j-1.9.1.v20130120-SNAPSHOT.zip
3、cp mmseg4j-1.9.1-SNAPSHOT/dist/* /home/ysc/apache-tomcat-7.0.35/webapps/solr/WEB-INF/lib
4、unzip mmseg4j-1.9.1-SNAPSHOT/dist/mmseg4j-core-1.9.1-SNAPSHOT.jar -d  mmseg4j-1.9.1-SNAPSHOT/dist/mmseg4j-core-1.9.1-SNAPSHOT
5、mkdir /home/ysc/dic
6、cp   mmseg4j-1.9.1-SNAPSHOT/dist/mmseg4j-core-1.9.1-SNAPSHOT/data/* /home/ysc/dic
7、vi /home/ysc/solr/configuration/collection1/conf/schema.xml
  将文件中的
  <tokenizer class="solr.WhitespaceTokenizerFactory"/>
  和
  <tokenizer class="solr.StandardTokenizerFactory"/>
  替换为
  <tokenizer class="com.chenlb.mmseg4j.solr.MMSegTokenizerFactory" mode="complex" dicPath="/home/ysc/dic"/>

配置tomcat本地库：
1、wget http://apache.spd.co.il/apr/apr-1.4.6.tar.gz
2、tar -xzvf apr-1.4.6.tar.gz
3、cd apr-1.4.6
4、./configure
5、make
6、make  install

1、wget http://mirror.bjtu.edu.cn/apache/apr/apr-util-1.5.1.tar.gz
2、tar -xzvf apr-util-1.5.1.tar.gz
3、cd apr-util-1.5.1
4、./configure --with-apr=/usr/local/apr
5、make
6、make  install

1、wget http://mirror.bjtu.edu.cn/apache//tomcat/tomcat-connectors/native/1.1.24/source/tomcat-native-1.1.24-src.tar.gz
2、tar -zxvf tomcat-native-1.1.24-src.tar.gz
3、cd tomcat-native-1.1.24-src/jni/native
4、./configure --with-apr=/usr/local/apr \
                --with-java-home=/home/ysc/jdk1.7.0_01 \
                --with-ssl=no \
                --prefix=/home/ysc/apache-tomcat-7.0.35
5、make
6、make  install
7、vi /etc/profile
增加：
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/ysc/apache-tomcat-7.0.35/lib:/usr/local/apr/lib
8、source /etc/profile

启动tomcat：
cd apache-tomcat-7.0.35
bin/catalina.sh start
http://devcluster01:8080/solr/

十八、Nagios监控
服务端：
1、apt-get install apache2 nagios3 nagios-nrpe-plugin
  输入密码：nagiosadmin
2、apt-get install nagios3-doc
3、vi /etc/nagios3/conf.d/hostgroups_nagios2.cfg
   define hostgroup {
     hostgroup_name  nagios-servers
     alias           nagios servers
     members         devcluster01,devcluster02,devcluster03
   }
4、cp  /etc/nagios3/conf.d/localhost_nagios2.cfg /etc/nagios3/conf.d/devcluster01_nagios2.cfg
  vi /etc/nagios3/conf.d/devcluster01_nagios2.cfg
  替换：
   g/localhost/s//devcluster01/g
   g/127.0.0.1/s//192.168.1.1/g
5、cp  /etc/nagios3/conf.d/localhost_nagios2.cfg /etc/nagios3/conf.d/devcluster02_nagios2.cfg
  vi /etc/nagios3/conf.d/devcluster02_nagios2.cfg
  替换：
   g/localhost/s//devcluster02/g
   g/127.0.0.1/s//192.168.1.2/g
6、cp  /etc/nagios3/conf.d/localhost_nagios2.cfg /etc/nagios3/conf.d/devcluster03_nagios2.cfg
  vi /etc/nagios3/conf.d/devcluster03_nagios2.cfg
  替换：
   g/localhost/s//devcluster03/g
   g/127.0.0.1/s//192.168.1.3/g

7、vi /etc/nagios3/conf.d/services_nagios2.cfg
  将hostgroup_name改为nagios-servers
  增加：
   # check that web services are running
   define service {
     hostgroup_name                  nagios-servers
     service_description             HTTP
     check_command                   check_http
     use                             generic-service
     notification_interval           0 ; set > 0 if you want to be renotified
   }

   # check that ssh services are running
   define service {
     hostgroup_name                  nagios-servers
     service_description             SSH
     check_command                   check_ssh
     use                             generic-service
     notification_interval           0 ; set > 0 if you want to be renotified
   }
8、vi /etc/nagios3/conf.d/extinfo_nagios2.cfg
  将hostgroup_name改为nagios-servers
  增加：
   define hostextinfo{
     hostgroup_name   nagios-servers
     notes            nagios-servers
   #       notes_url        http://webserver.localhost.localdomain/hostinfo.pl?host=netware1
     icon_image       base/debian.png
     icon_image_alt   Debian GNU/Linux
     vrml_image       debian.png
     statusmap_image  base/debian.gd2
     }
9、sudo /etc/init.d/nagios3 restart
10、访问http://devcluster01/nagios3/
  用户名：nagiosadmin密码：nagiosadmin

监控端：
1、apt-get install nagios-nrpe-server
2、vi /etc/nagios/nrpe.cfg
  替换：
  g/127.0.0.1/s//192.168.1.1/g
3、sudo /etc/init.d/nagios-nrpe-server restart

十九、配置Splunk
1、wget http://download.splunk.com/releases/5.0.2/splunk/linux/splunk-5.0.2-149561-Linux-x86_64.tgz
2、tar -zxvf splunk-5.0.2-149561-Linux-x86_64.tgz
3、cd splunk
4、bin/splunk start --answer-yes --no-prompt --accept-license
5、访问http://devcluster01:8000
  用户名：admin 密码：changeme
6、添加数据 -> 从 UDP 端口 -> UDP 端口 *: 1688 -> 来源类型 从列表 log4j -> 保存
7、配置hadoop
  vi /home/ysc/hadoop-1.1.1/conf/log4j.properties
  修改：
   log4j.rootLogger=${hadoop.root.logger}, EventCounter, SYSLOG
  增加：
   log4j.appender.SYSLOG=org.apache.log4j.net.SyslogAppender 
   log4j.appender.SYSLOG.facility=local1 
   log4j.appender.SYSLOG.layout=org.apache.log4j.PatternLayout 
   log4j.appender.SYSLOG.layout.ConversionPattern=%p %c{2}: %m%n 
   log4j.appender.SYSLOG.SyslogHost=host6:1688
   log4j.appender.SYSLOG.threshold=INFO 
   log4j.appender.SYSLOG.Header=true
   log4j.appender.SYSLOG.FacilityPrinting=true 
8、配置hbase
  vi /home/ysc/hbase-0.92.2/conf/log4j.properties
  修改：
   log4j.rootLogger=${hbase.root.logger},SYSLOG
  增加：
   log4j.appender.SYSLOG=org.apache.log4j.net.SyslogAppender 
   log4j.appender.SYSLOG.facility=local1 
   log4j.appender.SYSLOG.layout=org.apache.log4j.PatternLayout 
   log4j.appender.SYSLOG.layout.ConversionPattern=%p %c{2}: %m%n 
   log4j.appender.SYSLOG.SyslogHost=host6:1688
   log4j.appender.SYSLOG.threshold=INFO 
   log4j.appender.SYSLOG.Header=true
   log4j.appender.SYSLOG.FacilityPrinting=true
9、配置nutch
  vi /home/lanke/ysc/nutch-2.1-hbase/conf/log4j.properties
  修改：
   log4j.rootLogger=INFO,DRFA,SYSLOG
  增加：
   log4j.appender.SYSLOG=org.apache.log4j.net.SyslogAppender 
   log4j.appender.SYSLOG.facility=local1 
   log4j.appender.SYSLOG.layout=org.apache.log4j.PatternLayout 
   log4j.appender.SYSLOG.layout.ConversionPattern=%p %c{2}: %m%n 
   log4j.appender.SYSLOG.SyslogHost=host6:1688
   log4j.appender.SYSLOG.threshold=INFO 
   log4j.appender.SYSLOG.Header=true
   log4j.appender.SYSLOG.FacilityPrinting=true
10、启动hadoop和hbase
  start-all.sh
  start-hbase.sh

二十、配置Pig
1、wget http://labs.mop.com/apache-mirror/pig/pig-0.11.0/pig-0.11.0.tar.gz
2、tar -xzvf pig-0.11.0.tar.gz
3、cd pig-0.11.0
4、vi /etc/profile
  增加：
  export PIG_HOME=/home/ysc/pig-0.11.0
  export PATH=$PIG_HOME/bin:$PATH
5、source /etc/profile
6、cp conf/log4j.properties.template conf/log4j.properties
7、vi conf/log4j.properties
8、pig

二十一、配置Hive
1、wget http://mirrors.cnnic.cn/apache/hive/hive-0.10.0/hive-0.10.0.tar.gz
2、tar -xzvf hive-0.10.0.tar.gz
3、cd hive-0.10.0
4、vi /etc/profile
  增加：
  export HIVE_HOME=/home/ysc/hive-0.10.0
  export PATH=$HIVE_HOME/bin:$PATH
5、source /etc/profile
6、cp conf/hive-log4j.properties.template conf/hive-log4j.properties
7、vi conf/hive-log4j.properties
  替换：
  log4j.appender.EventCounter=org.apache.hadoop.metrics.jvm.EventCounter
  为：
  log4j.appender.EventCounter=org.apache.hadoop.log.metrics.EventCounter


二十二、配置Hadoop2.x集群
1、wget http://labs.mop.com/apache-mirror/hadoop/common/hadoop-2.0.2-alpha/hadoop-2.0.2-alpha.tar.gz
2、tar -xzvf hadoop-2.0.2-alpha.tar.gz
3、cd hadoop-2.0.2-alpha
4、vi etc/hadoop/hadoop-env.sh
  追加：
export JAVA_HOME=/home/ysc/jdk1.7.0_05
  export HADOOP_HEAPSIZE=2000
5、vi etc/hadoop/core-site.xml
  <property>
   <name>fs.defaultFS</name>
   <value>hdfs://devcluster01:9000</value>
   <description>
      Where to find the Hadoop Filesystem through the network.
      Note 9000 is not the default port.
      (This is slightly changed from previous versions which didnt have "hdfs")
   </description>
   </property>
   <property>
    <name>io.file.buffer.size</name>
    <value>131072</value>
    <description>The size of buffer for use in sequence files.
    The size of this buffer should probably be a multiple of hardware
    page size (4096 on Intel x86), and it determines how much data is
    buffered during read and write operations.</description>
  </property>
6、vi etc/hadoop/mapred-site.xml
  <property>
    <name>mapreduce.framework.name</name>
    <value>yarn</value>
  </property>

  <property>
    <name>mapred.job.reduce.input.buffer.percent</name>
    <value>1</value>
    <description>The percentage of memory- relative to the maximum heap size- to
    retain map outputs during the reduce. When the shuffle is concluded, any
    remaining map outputs in memory must consume less than this threshold before
    the reduce can begin.
    </description>
  </property>

  <property>
    <name>mapred.job.shuffle.input.buffer.percent</name>
    <value>1</value>
    <description>The percentage of memory to be allocated from the maximum heap
    size to storing map outputs during the shuffle.
    </description>
  </property>

  <property>
    <name>mapred.inmem.merge.threshold</name>
    <value>0</value>
    <description>The threshold, in terms of the number of files
    for the in-memory merge process. When we accumulate threshold number of files
    we initiate the in-memory merge and spill to disk. A value of 0 or less than
    0 indicates we want to DON'T have any threshold and instead depend only on
    the ramfs's memory consumption to trigger the merge.
    </description>
  </property>

  <property>
    <name>io.sort.factor</name>
    <value>100</value>
    <description>The number of streams to merge at once while sorting
    files.  This determines the number of open file handles.</description>
  </property>

  <property>
    <name>io.sort.mb</name>
    <value>240</value>
    <description>The total amount of buffer memory to use while sorting
    files, in megabytes.  By default, gives each merge stream 1MB, which
    should minimize seeks.</description>
  </property>
    <property>
      <name>mapred.map.output.compression.codec</name>
      <value>org.apache.hadoop.io.compress.SnappyCodec</value>
      <description>If the map outputs are compressed, how should they be
          compressed?
      </description>
    </property>

    <property>
      <name>mapred.output.compression.codec</name>
      <value>org.apache.hadoop.io.compress.SnappyCodec</value>
      <description>If the job outputs are compressed, how should they be compressed?
      </description>
    </property>
  <property>
    <name>mapred.output.compression.type</name>
    <value>BLOCK</value>
    <description>If the job outputs are to compressed as SequenceFiles, how should
        they be compressed? Should be one of NONE, RECORD or BLOCK.
    </description>
  </property>
  <property>
    <name>mapred.child.java.opts</name>
    <value>-Xmx2000m</value>
  </property>

  <property>
    <name>mapred.output.compress</name>
    <value>true</value>
    <description>Should the job outputs be compressed?
    </description>
  </property>

  <property>
    <name>mapred.compress.map.output</name>
    <value>true</value>
    <description>Should the outputs of the maps be compressed before being
        sent across the network. Uses SequenceFile compression.
    </description>
  </property>

  <property>
    <name>mapred.tasktracker.map.tasks.maximum</name>
    <value>5</value>
  </property>

  <property>
    <name>mapred.map.tasks</name>
    <value>15</value>
  </property>

  <property>
    <name>mapred.tasktracker.reduce.tasks.maximum</name>
    <value>5</value>
   <description>
   define mapred.map tasks to be number of slave hosts.the best number is the  number of slave hosts plus the core numbers of per host
   </description>
  </property>

  <property>
    <name>mapred.reduce.tasks</name>
    <value>15</value>
    <description>
   define mapred.reduce tasks to be number of slave hosts.the best number is the  number of slave hosts plus the core numbers of per host
    </description>
  </property>
  <property>
    <name>mapred.system.dir</name>
    <value>/home/ysc/mapreduce/system</value>
  </property>

  <property>
    <name>mapred.local.dir</name>
    <value>/home/ysc/mapreduce/local</value>
  </property>

  <property>
    <name>mapreduce.job.counters.max</name>
    <value>12000</value>
    <description>Limit on the number of counters allowed per job.
    </description>
  </property>
7、vi etc/hadoop/yarn-site.xml
  <property>   
    <name>yarn.resourcemanager.resource-tracker.address</name>  
    <value>devcluster01:8031</value>
   </property>  
   <property> 
    <name>yarn.resourcemanager.address</name>    
    <value>devcluster01:8032</value> 
   </property>
   <property>   
    <name>yarn.resourcemanager.scheduler.address</name> 
    <value>devcluster01:8030</value>
   </property>
   <property> 
    <name>yarn.resourcemanager.admin.address</name> 
    <value>devcluster01:8033</value>  
   </property>  
   <property>   
    <name>yarn.resourcemanager.webapp.address</name>   
    <value>devcluster01:8088</value> 
   </property> 
   <property>  
    <description>Classpath for typical applications.</description>
    <name>yarn.application.classpath</name> 
    <value>      
    $HADOOP_CONF_DIR,     
    $HADOOP_COMMON_HOME/*,$HADOOP_COMMON_HOME/lib/*,   
    $HADOOP_HDFS_HOME/*,$HADOOP_HDFS_HOME/lib/*,      
    $HADOOP_MAPRED_HOME/*,$HADOOP_MAPRED_HOME/lib/*,  
    $YARN_HOME/*,$YARN_HOME/lib/*  
    </value> 
   </property>
   <property> 
    <name>yarn.nodemanager.aux-services</name> 
    <value>mapreduce.shuffle</value> 
   </property>  
   <property>   
    <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name> 
    <value>org.apache.hadoop.mapred.ShuffleHandler</value> 
   </property> 
   <property>  
    <name>yarn.nodemanager.local-dirs</name>     <value>/home/ysc/h2/data/1/yarn/local,/home/ysc/h2/data/2/yarn/local,/home/ysc/h2/data/3/yarn/local</value> 
   </property>
   <property>
    <name>yarn.nodemanager.log-dirs</name>      <value>/home/ysc/h2/data/1/yarn/logs,/home/ysc/h2/data/2/yarn/logs,/home/ysc/h2/data/3/yarn/logs</value> 
   </property> 
   <property>  
    <description>Where to aggregate logs</description>
    <name>yarn.nodemanager.remote-app-log-dir</name>   
    <value>/home/ysc/h2/var/log/hadoop-yarn/apps</value>
   </property>   
   <property>   
    <name>mapreduce.jobhistory.address</name>  
    <value>devcluster01:10020</value>
   </property>  
   <property>   
    <name>mapreduce.jobhistory.webapp.address</name>  
    <value>devcluster01:19888</value>
   </property>  
8、vi etc/hadoop/hdfs-site.xml
  <property> 
   <name>dfs.permissions.superusergroup</name> 
   <value>root</value>
  </property>
  <property>
    <name>dfs.name.dir</name>
    <value>/home/ysc/dfs/filesystem/name</value>
  </property>
  <property>
    <name>dfs.data.dir</name>
    <value>/home/ysc/dfs/filesystem/data</value>
  </property>
  <property>
    <name>dfs.replication</name>
    <value>3</value>
  </property>
  <property>
    <name>dfs.block.size</name>
    <value>6710886400</value>
    <description>The default block size for new files.</description>
  </property>
9、启动hadoop
  bin/hdfs namenode -format
  sbin/start-dfs.sh
  sbin/start-yarn.sh
10、访问管理页面
  http://devcluster01:8088
  http://devcluster01:50070

评论

4 楼 yangshangchuan 2014-02-25  

NikolaiBalance 写道

你好，我按照你的步骤，二、nutch1.5.1 ，做到 8、开发调试 报错，我的环境是在win 7下eclipse

Exception in thread "main" java.io.IOException: Failed to set permissions of path: \tmp\hadoop-Administrator\mapred\staging\Administrator1042821926\.staging to 0700
at org.apache.hadoop.fs.FileUtil.checkReturnValue(FileUtil.java:689)
at org.apache.hadoop.fs.FileUtil.setPermission(FileUtil.java:662)
at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:509)
at org.apache.hadoop.fs.RawLocalFileSystem.mkdirs(RawLocalFileSystem.java:344)
at org.apache.hadoop.fs.FilterFileSystem.mkdirs(FilterFileSystem.java:189)
at org.apache.hadoop.mapreduce.JobSubmissionFiles.getStagingDir(JobSubmissionFiles.java:116)
at org.apache.hadoop.mapred.JobClient$2.run(JobClient.java:856)
at org.apache.hadoop.mapred.JobClient$2.run(JobClient.java:850)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Unknown Source)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1121)
at org.apache.hadoop.mapred.JobClient.submitJobInternal(JobClient.java:850)
at org.apache.hadoop.mapred.JobClient.submitJob(JobClient.java:824)
at org.apache.hadoop.mapred.JobClient.runJob(JobClient.java:1261)
at org.apache.nutch.crawl.Injector.inject(Injector.java:217)
at org.apache.nutch.crawl.Crawl.run(Crawl.java:127)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:65)
at org.apache.nutch.crawl.Crawl.main(Crawl.java:55)
想请教一下，问题原因是什么？

参考我的这篇博文：http://yangshangchuan.iteye.com/blog/1839784

3 楼 NikolaiBalance 2014-02-25  

你好，我按照你的步骤，二、nutch1.5.1 ，做到 8、开发调试 报错，我的环境是在win 7下eclipse

Exception in thread "main" java.io.IOException: Failed to set permissions of path: \tmp\hadoop-Administrator\mapred\staging\Administrator1042821926\.staging to 0700
at org.apache.hadoop.fs.FileUtil.checkReturnValue(FileUtil.java:689)
at org.apache.hadoop.fs.FileUtil.setPermission(FileUtil.java:662)
at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:509)
at org.apache.hadoop.fs.RawLocalFileSystem.mkdirs(RawLocalFileSystem.java:344)
at org.apache.hadoop.fs.FilterFileSystem.mkdirs(FilterFileSystem.java:189)
at org.apache.hadoop.mapreduce.JobSubmissionFiles.getStagingDir(JobSubmissionFiles.java:116)
at org.apache.hadoop.mapred.JobClient$2.run(JobClient.java:856)
at org.apache.hadoop.mapred.JobClient$2.run(JobClient.java:850)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Unknown Source)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1121)
at org.apache.hadoop.mapred.JobClient.submitJobInternal(JobClient.java:850)
at org.apache.hadoop.mapred.JobClient.submitJob(JobClient.java:824)
at org.apache.hadoop.mapred.JobClient.runJob(JobClient.java:1261)
at org.apache.nutch.crawl.Injector.inject(Injector.java:217)
at org.apache.nutch.crawl.Crawl.run(Crawl.java:127)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:65)
at org.apache.nutch.crawl.Crawl.main(Crawl.java:55)
想请教一下，问题原因是什么？

2 楼 yangshangchuan 2014-02-19  

liujze 写道

您的文章写的真详细，我又个问题，nutch1和nutch2有哪些不同？

nutch1和nutch2最大的不同在于存储层，nutch1使用文件系统，主要是HDFS，nutch2使用多种数据库，主要是HBASE。

1 楼 liujze 2014-02-17  

您的文章写的真详细，我又个问题，nutch1和nutch2有哪些不同？