我有交通数据分析的输入数据。其中一些列是:
事故id、事故日期、星期几
1979年1月1日,5日(星期四)
1979年1月2日,6日(星期五)
.......
1980年1月1日,0(星期日)
我试图解决以下问题:
找出每年每天发生的事故数量
所以输出应该是这样的:
其中键是(年,星期几)
值=1号线所代表的当天的事故数,年=1979天=周日,事故数=500,以此类推。
1979,1 500
1979,2 1500
1979,3 2500
1979,4 3500
1979,5 4500
1979,6 5500
1979,7 6500
1980,1 500
1980,2 1500
1980,3 2500
1980,4 3500
1980,5 4500
在这个场景中,我尝试使用二次排序方法来解决它。这是解决这个问题的正确方法吗?
如果二次排序是正确的方式,它不适合我。下面是关键类mapper和reducer。但是我的输出没有达到预期。请帮忙。。
public class DOW implements WritableComparable<DOW> {
private Text year;
private Text day;
// private final Text count;
// private int count;
public DOW() {
this.year = new Text();
this.day = new Text();
// this.count = count;
}
public DOW(Text year, Text day) {
this.year = year;
this.day = day;
// this.count = count;
}
public Text getYear() {
return this.year;
}
public void setYear(Text year) {
this.year = year;
}
public Text getDay() {
return this.day;
}
public void setDay(Text day) {
this.day = day;
}
@Override
public void readFields(DataInput in) throws IOException {
// TODO Auto-generated method stub
year.readFields(in);
day.readFields(in);
}
@Override
public void write(DataOutput out) throws IOException {
// TODO Auto-generated method stub
year.write(out);
day.write(out);
}
@Override
public int compareTo(DOW o) {
// TODO Auto-generated method stub
int cmp = year.compareTo(o.year);
if (cmp != 0) {
return cmp;
}
return o.day.compareTo(this.day);
}
@Override
public String toString() {
// TODO Auto-generated method stub
return year + "," + day;
}
@Override
public boolean equals(Object o) {
// TODO Auto-generated method stub
if (o instanceof DOW) {
DOW tp = (DOW) o;
return year.equals(tp.year) && day.equals(tp.day);
}
return false;
}
@Override
public int hashCode() {
// TODO Auto-generated method stub
return year.hashCode() * 163 + day.hashCode();
}
}
public class AccidentDowDemo extends Configured implements Tool {
public static class DOWMapper extends Mapper<LongWritable, Text, DOW, IntWritable> {
private static final Logger sLogger = Logger.getLogger(DOWMapper.class);
@Override
protected void map(LongWritable key, Text value, Context context)
throws java.io.IOException, InterruptedException {
if (value.toString().contains(",")) {
String[] array = value.toString().split(",");
if (!array[9].equals("Date")) {
Date dt = null;
try {
dt = new SimpleDateFormat("dd/mm/yyyy").parse(array[9]);
} catch (ParseException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
int year = dt.getYear();
int day = Integer.parseInt(array[10].toString());
context.write(new DOW(new Text(Integer.toString(year)),
new Text(Integer.toString(day))),
new IntWritable(1));
}
}
};
}
public static class DOWReducer extends Reducer<DOW, IntWritable, DOW, IntWritable> {
private static final Logger sLogger = Logger
.getLogger(DOWReducer.class);
@Override
protected void reduce(DOW key, Iterable<IntWritable> values,
Context context) throws java.io.IOException,
InterruptedException {
int count = 0;
sLogger.info("key =" + key);
for (IntWritable x : values) {
int val = Integer.parseInt(x.toString());
count = count + val;
}
context.write(key, new IntWritable(count));
};
}
public static class FirstPartitioner extends Partitioner<DOW, IntWritable> {
@Override
public int getPartition(DOW key, IntWritable value, int numPartitions) {
// TODO Auto-generated method stub
return Math.abs(Integer.parseInt(key.getYear().toString()) * 127)
% numPartitions;
}
}
public static class KeyComparator extends WritableComparator {
protected KeyComparator() {
super(DOW.class, true);
}
@Override
public int compare(WritableComparable w1, WritableComparable w2) {
// TODO Auto-generated method stub
DOW ip1 = (DOW) w1;
DOW ip2 = (DOW) w2;
int cmp = ip1.getYear().compareTo(ip2.getYear());
if (cmp == 0) {
cmp = -1 * ip1.getDay().compareTo(ip2.getDay());
}
return cmp;
}
}
public static class GroupComparator extends WritableComparator {
protected GroupComparator() {
super(DOW.class, true);
}
@Override
public int compare(WritableComparable w1, WritableComparable w2) {
// TODO Auto-generated method stub
DOW ip1 = (DOW) w1;
DOW ip2 = (DOW) w2;
return ip1.getYear().compareTo(ip2.getYear());
}
}
}
2条答案
按热度按时间2guxujil1#
它或多或少是一种二次排序,但不是。问题在于groupcomparator,必须在年和日进行比较。groupcomparator的思想是确保同一年进入同一个reducer,但这里我们不需要,相反,如果数据具有同一年和同一天(1979年和周日),则必须进入同一个reducer。应该是这样的。
我也在粘贴我的全部代码。
样本输入:
日期,事故次数,日
01/03/2014,18,2
02/03/2014,19,3
03/03/2014,20,4
01/03/2014,1,2
02/03/2014,2,3
03/03/2014,4,4
01/03/2014,8,2
02/03/2014,9,3
03/03/2014,2,4
输出:
01/03/2014,2,27
02/03/2014,3,30
03/03/2014,4,26
qxgroojn2#
如果你需要基本上模拟
比你不需要二次排序。
但是如果你需要制作一个立方体,你需要计算一份mr工作中每年和每周的总数,那么二次排序就是最好的选择。