1 weekend110的复习 + hadoop中的序列化机制 + 流量求和mr程序开发-低调大师

1 weekend110的复习 + hadoop中的序列化机制 + 流量求和mr程序开发

2017-11-12 643

以上是，weekend110的yarn的job提交流程源码分析的复习总结

下面呢，来讲weekend110的hadoop中的序列化机制

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1363157993044 18211575961 94-71-AC-CD-E6-18:CMCC-EASY 120.196.100.99 iface.qiyi.com 视频网站 15 12 1527 2106 200

1363157995074 84138413 5C-0E-8B-8C-E8-20:7DaysInn 120.197.40.4 122.72.52.12 20 16 4116 1432 200

1363157993055 13560439658 C4-17-FE-BA-DE-D9:CMCC 120.196.100.99 18 15 1116 954 200

1363157995033 15920133257 5C-0E-8B-C7-BA-20:CMCC 120.197.40.4 sug.so.360.cn 信息安全 20 20 3156 2936 200

1363157983019 13719199419 68-A1-B7-03-07-B1:CMCC-EASY 120.196.100.82 4 0 240 0 200

1363157984041 13660577991 5C-0E-8B-92-5C-20:CMCC-EASY 120.197.40.4 s19.cnzz.com 站点统计 24 9 6960 690 200

1363157973098 15013685858 5C-0E-8B-C7-F7-90:CMCC 120.197.40.4 rank.ie.sogou.com 搜索引擎 28 27 3659 3538 200

1363157986029 15989002119 E8-99-C4-4E-93-E0:CMCC-EASY 120.196.100.99 www.umeng.com 站点统计 3 3 1938 180 200

1363157992093 13560439658 C4-17-FE-BA-DE-D9:CMCC 120.196.100.99 15 9 918 4938 200

1363157986041 13480253104 5C-0E-8B-C7-FC-80:CMCC-EASY 120.197.40.4 3 3 180 180 200

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1363157982040 13502468823 5C-0A-5B-6A-0B-D4:CMCC-EASY 120.196.100.99 y0.ifengimg.com 综合门户 57 102 7335 110349 200

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手机号码时间戳 Ip 网站上行流量下行流量总的流量

LongWritable的源码

 

/**

 * Licensed to the Apache Software Foundation (ASF) under one

 * or more contributor license agreements.  See the NOTICE file

 * distributed with this work for additional information

 * regarding copyright ownership.  The ASF licenses this file

 * to you under the Apache License, Version 2.0 (the

 * "License"); you may not use this file except in compliance

 * with the License.  You may obtain a copy of the License at

 *

 *     http://www.apache.org/licenses/LICENSE-2.0

 *

 * Unless required by applicable law or agreed to in writing, software

 * distributed under the License is distributed on an "AS IS" BASIS,

 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

 * See the License for the specific language governing permissions and

 * limitations under the License.

 */

 

package org.apache.hadoop.io;

 

 

import java.io.DataInput;

import java.io.DataOutput;

import java.io.IOException;

 

import org.apache.hadoop.classification.InterfaceAudience;

import org.apache.hadoop.classification.InterfaceStability;

 

/** A WritableComparable for longs. */

@InterfaceAudience.Public

@InterfaceStability.Stable

public class LongWritable implements WritableComparable<LongWritable> {

  private long value;

 

  public LongWritable() {}

 

  public LongWritable(long value) { set(value); }

 

  /** Set the value of this LongWritable. */

  public void set(long value) { this.value = value; }

 

  /** Return the value of this LongWritable. */

  public long get() { return value; }

 

  @Override

  public void readFields(DataInput in) throws IOException {

    value = in.readLong();

  }

 

  @Override

  public void write(DataOutput out) throws IOException {

    out.writeLong(value);

  }

 

  /** Returns true iff <code>o</code> is a LongWritable with the same value. */

  @Override

  public boolean equals(Object o) {

    if (!(o instanceof LongWritable))

      return false;

    LongWritable other = (LongWritable)o;

    return this.value == other.value;

  }

 

  @Override

  public int hashCode() {

    return (int)value;

  }

 

  /** Compares two LongWritables. */

  @Override

  public int compareTo(LongWritable o) {

    long thisValue = this.value;

    long thatValue = o.value;

    return (thisValue<thatValue ? -1 : (thisValue==thatValue ? 0 : 1));

  }

 

  @Override

  public String toString() {

    return Long.toString(value);

  }

 

  /** A Comparator optimized for LongWritable. */

  public static class Comparator extends WritableComparator {

    public Comparator() {

      super(LongWritable.class);

    }

 

    @Override

    public int compare(byte[] b1, int s1, int l1,

                       byte[] b2, int s2, int l2) {

      long thisValue = readLong(b1, s1);

      long thatValue = readLong(b2, s2);

      return (thisValue<thatValue ? -1 : (thisValue==thatValue ? 0 : 1));

    }

  }

 

  /** A decreasing Comparator optimized for LongWritable. */

  public static class DecreasingComparator extends Comparator {

   

    @Override

    public int compare(WritableComparable a, WritableComparable b) {

      return -super.compare(a, b);

    }

    @Override

    public int compare(byte[] b1, int s1, int l1, byte[] b2, int s2, int l2) {

      return -super.compare(b1, s1, l1, b2, s2, l2);

    }

  }

 

  static {                                       // register default comparator

    WritableComparator.define(LongWritable.class, new Comparator());

  }

 

}

WritableComparable的源码

/**

 * Licensed to the Apache Software Foundation (ASF) under one

 * or more contributor license agreements.  See the NOTICE file

 * distributed with this work for additional information

 * regarding copyright ownership.  The ASF licenses this file

 * to you under the Apache License, Version 2.0 (the

 * "License"); you may not use this file except in compliance

 * with the License.  You may obtain a copy of the License at

 *

 *     http://www.apache.org/licenses/LICENSE-2.0

 *

 * Unless required by applicable law or agreed to in writing, software

 * distributed under the License is distributed on an "AS IS" BASIS,

 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

 * See the License for the specific language governing permissions and

 * limitations under the License.

 */

 

package org.apache.hadoop.io;

 

import org.apache.hadoop.classification.InterfaceAudience;

import org.apache.hadoop.classification.InterfaceStability;

 

/**

 * A {@link Writable} which is also {@link Comparable}.

 *

 * <p><code>WritableComparable</code>s can be compared to each other, typically

 * via <code>Comparator</code>s. Any type which is to be used as a

 * <code>key</code> in the Hadoop Map-Reduce framework should implement this

 * interface.</p>

 *

 * <p>Note that <code>hashCode()</code> is frequently used in Hadoop to partition

 * keys. It's important that your implementation of hashCode() returns the same

 * result across different instances of the JVM. Note also that the default

 * <code>hashCode()</code> implementation in <code>Object</code> does <b>not</b>

 * satisfy this property.</p>

 * 

 * <p>Example:</p>

 * <p><blockquote><pre>

 *     public class MyWritableComparable implements WritableComparable<MyWritableComparable> {

 *       // Some data

 *       private int counter;

 *       private long timestamp;

 *      

 *       public void write(DataOutput out) throws IOException {

 *         out.writeInt(counter);

 *         out.writeLong(timestamp);

 *       }

 *      

 *       public void readFields(DataInput in) throws IOException {

 *         counter = in.readInt();

 *         timestamp = in.readLong();

 *       }

 *      

 *       public int compareTo(MyWritableComparable o) {

 *         int thisValue = this.value;

 *         int thatValue = o.value;

 *         return (thisValue &lt; thatValue ? -1 : (thisValue==thatValue ? 0 : 1));

 *       }

 *

 *       public int hashCode() {

 *         final int prime = 31;

 *         int result = 1;

 *         result = prime * result + counter;

 *         result = prime * result + (int) (timestamp ^ (timestamp &gt;&gt;&gt; 32));

 *         return result

 *       }

 *     }

 * </pre></blockquote></p>

 */

@InterfaceAudience.Public

@InterfaceStability.Stable

public interface WritableComparable<T> extends Writable, Comparable<T> {

}

这样可以减少网络带宽，所以，为什么hadoop用到自己的序列化机制。

以上是weekend110的hadoop中的序列化机制

//将对象数据序列化到数据流中

@Override

public void write(DataOutput out) throws IOException {

// TODO Auto-generated method stub

}

序列化里，是要把数据写出去

//从数据流中反序列出对象数据

@Override

public void readFields(DataInput in) throws IOException {

// TODO Auto-generated method stub

}

反序列化，是要读入数据。

至此，FlowBean.java代码已经写完。