1 weekend110的复习 + hadoop中的序列化机制 + 流量求和mr程序开发
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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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 < 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 >>> 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。
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[hadoop@weekend110 ~]$ /home/hadoop/app/hadoop-2.4.1/bin/hadoop jar flow.jar cn.itcast.hadoop.mr.flowsum.FlowSumRunner /flow/data /flow/output
以上是weekend110的流量求和mr程序开发
本文转自大数据躺过的坑博客园博客,原文链接:http://www.cnblogs.com/zlslch/p/5896395.html,如需转载请自行联系原作者





























































































































































































































