我尝试在一个简单的mapreduce任务中从arraywritable获取输出。我发现了一些类似问题的问题,但我无法用自己的代码解决这个问题。所以我期待着你的帮助。谢谢:)!
输入:文本文件和一些句子。
输出应为:
<Word, <length, number of same words in Textfile>>
Example: Hello 5 2
我在工作中得到的结果是:
hello WordLength_V01$IntArrayWritable@221cf05
test WordLength_V01$IntArrayWritable@799e525a
我认为问题出在intarraywritable的子类中,但是我没有得到正确的更正来解决这个问题。顺便说一下,我们有hadoop 2.5,我使用以下代码得到这个结果:
主要方法:
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
Job job = Job.getInstance(conf, "word length V1");
// Set Classes
job.setJarByClass(WordLength_V01.class);
job.setMapperClass(MyMapper.class);
// job.setCombinerClass(MyReducer.class);
job.setReducerClass(MyReducer.class);
// Set Output and Input Parameters
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntArrayWritable.class);
// Number of Reducers
job.setNumReduceTasks(1);
// Set FileDestination
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
Map器:
public static class MyMapper extends Mapper<Object, Text, Text, IntWritable> {
// Initialize Variables
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
// Map Method
public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
// Use Tokenizer
StringTokenizer itr = new StringTokenizer(value.toString());
// Select each word
while (itr.hasMoreTokens()) {
word.set(itr.nextToken());
// Output Pair
context.write(word, one);
}
}
}
减速器:
public static class MyReducer extends Reducer<Text, IntWritable, Text, IntArrayWritable> {
// Initialize Variables
private IntWritable count = new IntWritable();
private IntWritable length = new IntWritable();
// Reduce Method
public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
// Count Words
int sum = 0;
for (IntWritable val : values) {
sum += val.get();
}
count.set(sum);
// Wordlength
length.set(key.getLength());
// Define Output
IntWritable[] temp = new IntWritable[2];
IntArrayWritable output = new IntArrayWritable(temp);
temp[0] = count;
temp[1] = length;
// Output
output.set(temp);
context.write(key, new IntArrayWritable(output.get()));
}
}
子类
public static class IntArrayWritable extends ArrayWritable {
public IntArrayWritable(IntWritable[] intWritables) {
super(IntWritable.class);
}
@Override
public IntWritable[] get() {
return (IntWritable[]) super.get();
}
@Override
public void write(DataOutput arg0) throws IOException {
for(IntWritable data : get()){
data.write(arg0);
}
}
}
我使用以下链接找到解决方案:
可写接口(hadoop.apache.org)
类arraywritable(hadoop.apache.org)
stackoverflow.com(1)
stackoverflow.com(2)
我真的很感激你的任何想法!
--------解决方案--------
新建子类:
public static class IntArrayWritable extends ArrayWritable {
public IntArrayWritable(IntWritable[] values) {
super(IntWritable.class, values);
}
@Override
public IntWritable[] get() {
return (IntWritable[]) super.get();
}
@Override
public String toString() {
IntWritable[] values = get();
return values[0].toString() + ", " + values[1].toString();
}
}
新reduce方法:
public void reduce(Text key, Iterable<IntWritable> values,
Context context) throws IOException, InterruptedException {
// Count Words
int sum = 0;
for (IntWritable val : values) {
sum += val.get();
}
count.set(sum);
// Wordlength
length.set(key.getLength());
// Define Output
IntWritable[] temp = new IntWritable[2];
temp[0] = count;
temp[1] = length;
context.write(key, new IntArrayWritable(temp));
}
1条答案
按热度按时间9bfwbjaz1#
一切看起来都很完美。只需在子类中再编写一个方法printstrings(),返回字符串而不是数组。inbuildtoString()将返回字符串数组,这就是它在输出中提供地址而不是值的原因。