<configuration>

<property>

  <name>fs.defaultFS</name>

  <value>hdfs://master:9000</value>

  <description>The name of the default file system.  A URI whose

  scheme and authority determine the FileSystem implementation.  The

  uri's scheme determines the config property (fs.SCHEME.impl) naming

  the FileSystem implementation class.  The uri's authority is used to

  determine the host, port, etc. for a filesystem.</description>

</property>

<property>

  <name>hadoop.tmp.dir</name>

  <value>/usr/program/hadoop-2.5.2/tmp</value>

  <description>A base for other temporary directories.</description>

</property>

<!-- i/o properties -->

<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>

</configuration>

<configuration>

<property>

  <name>dfs.namenode.name.dir</name>

  <value>/usr/program/hadoop-2.5.2/hdfs/name</value>

  <description>Determines where on the local filesystem the DFS name node

      should store the name table(fsimage).  If this is a comma-delimited list

      of directories then the name table is replicated in all of the

      directories, for redundancy. </description>

</property>

<property>

  <name>dfs.datanode.data.dir</name>

  <value>/usr/program/hadoop-2.5.2/hdfs/data</value>

  <description>Determines where on the local filesystem an DFS data node

  should store its blocks.  If this is a comma-delimited

  list of directories, then data will be stored in all named

  directories, typically on different devices.

  Directories that do not exist are ignored.

  </description>

</property>

<property>

  <name>dfs.replication</name>

  <value>2</value>

  <description>Default block replication.

  The actual number of replications can be specified when the file is created.

  The default is used if replication is not specified in create time.

  </description>

</property>

<property>

  <name>dfs.blocksize</name>

  <value>134217728</value>

  <description>

      The default block size for new files, in bytes.

      You can use the following suffix (case insensitive):

      k(kilo), m(mega), g(giga), t(tera), p(peta), e(exa) to specify the size (such as 128k, 512m, 1g, etc.),

      Or provide complete size in bytes (such as 134217728 for 128 MB).

  </description>

</property>

<property>

  <name>dfs.namenode.handler.count</name>

  <value>10</value>

  <description>The number of server threads for the namenode.</description>

</property>

</configuration>

<configuration>

<property>

  <name>mapreduce.framework.name</name>

  <value>yarn</value>

  <description>The runtime framework for executing MapReduce jobs.

  Can be one of local, classic or yarn.

  </description>

</property>

<!-- jobhistory properties -->

<property>

  <name>mapreduce.jobhistory.address</name>

  <value>master:10020</value>

  <description>MapReduce JobHistory Server IPC host:port</description>

</property>

<property>

  <name>mapreduce.jobhistory.webapp.address</name>

  <value>master:19888</value>

  <description>MapReduce JobHistory Server Web UI host:port</description>

</property>

</configuration>

configuration>

<!-- Site specific YARN configuration properties -->

<property>

    <description>The hostname of the RM.</description>

    <name>yarn.resourcemanager.hostname</name>

    <value>master</value>

  </property>

<property>

    <name>yarn.resourcemanager.address</name>

    <value>${yarn.resourcemanager.hostname}:8032</value>

    <description>The address of the applications manager interface in the RM.</description>

</property>

<property>

    <description>The address of the scheduler interface.</description>

    <name>yarn.resourcemanager.scheduler.address</name>

    <value>${yarn.resourcemanager.hostname}:8030</value>

  </property>

<property>

    <name>yarn.resourcemanager.resource-tracker.address</name>

    <value>${yarn.resourcemanager.hostname}:8031</value>

  </property>

<property>

    <description>The address of the RM admin interface.</description>

    <name>yarn.resourcemanager.admin.address</name>

    <value>${yarn.resourcemanager.hostname}:8033</value>

  </property>

<property>

    <description>The http address of the RM web application.</description>

    <name>yarn.resourcemanager.webapp.address</name>

    <value>${yarn.resourcemanager.hostname}:8088</value>

  </property>

<property>

    <description>The minimum allocation for every container request at the RM,

    in MBs. Memory requests lower than this won't take effect,

    and the specified value will get allocated at minimum.

        default is 1024

    </description>

    <name>yarn.scheduler.minimum-allocation-mb</name>

    <value>512</value>

  </property>

<property>

    <description>The maximum allocation for every container request at the RM,

    in MBs. Memory requests higher than this won't take effect,

    and will get capped to this value.

    default value is 8192</description>

    <name>yarn.scheduler.maximum-allocation-mb</name>

    <value>2048</value>

  </property>

<property>

    <description>Amount of physical memory, in MB, that can be allocated

    for containers.default value is 8192</description>

    <name>yarn.nodemanager.resource.memory-mb</name>

    <value>2048</value>

  </property>

<property>

    <description>Whether to enable log aggregation. Log aggregation collects

      each container's logs and moves these logs onto a file-system, for e.g.

      HDFS, after the application completes. Users can configure the

      "yarn.nodemanager.remote-app-log-dir" and

      "yarn.nodemanager.remote-app-log-dir-suffix" properties to determine

      where these logs are moved to. Users can access the logs via the

      Application Timeline Server.

    </description>

    <name>yarn.log-aggregation-enable</name>

    <value>true</value>

  </property>

</configuration>

这样基本搭建已经完成，形成节点之间的连接。接下来开始配置hadoop和eclipse之间的联系，同时会解决遇到的困难。进行相关的配置问题