我正在尝试创建一个自定义分区程序,以将每个唯一键分配给单个reducer。这是在默认的 HashPartioner 失败之后 Alternative to the default hashpartioner provided with hadoop
我一直收到以下错误。它与构造函数没有接收到它的参数有关,我可以从做一些研究中得知。但在这种情况下,使用hadoop,不是框架自动传递的参数吗?我无法在代码中找到错误
18/04/20 17:06:51 INFO mapred.JobClient: Task Id : attempt_201804201340_0007_m_000000_1, Status : FAILED
java.lang.RuntimeException: java.lang.NoSuchMethodException: biA3pipepart$parti.<init>()
at org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:131)
at org.apache.hadoop.mapred.MapTask$NewOutputCollector.<init>(MapTask.java:587)
这是我的分区:
public class Parti extends Partitioner<Text, Text> {
String partititonkey;
int result=0;
@Override
public int getPartition(Text key, Text value, int numPartitions) {
String partitionKey = key.toString();
if(numPartitions >= 9){
if(partitionKey.charAt(0) =='0' ){
if(partitionKey.charAt(2)=='0' )
result= 0;
else
if(partitionKey.charAt(2)=='1' )
result= 1;
else
result= 2;
}else
if(partitionKey.charAt(0)=='1'){
if(partitionKey.charAt(2)=='0' )
result= 3;
else
if(partitionKey.charAt(2)=='1' )
result= 4;
else
result= 5;
}else
if(partitionKey.charAt(0)=='2' ){
if(partitionKey.charAt(2)=='0' )
result= 6;
else
if(partitionKey.charAt(2)=='1' )
result= 7;
else
result= 8;
}
} //
else
result= 0;
return result;
}// close method
}// close class
我的映射器签名
public static class JoinsMap extends Mapper<LongWritable,Text,Text,Text>{
public void Map(LongWritable key, Text value, Context context) throws IOException, InterruptedException{
我的减速机标志
public static class JoinsReduce extends Reducer<Text,Text,Text,Text>{
public void Reduce (Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
主要课程:
public static void main( String[] args ) throws Exception {
Configuration conf1 = new Configuration();
Job job1 = new Job(conf1, "biA3pipepart");
job1.setJarByClass(biA3pipepart.class);
job1.setNumReduceTasks(9);//***
job1.setOutputKeyClass(Text.class);
job1.setOutputValueClass(Text.class);
job1.setMapperClass(JoinsMap.class);
job1.setReducerClass(JoinsReduce.class);
job1.setInputFormatClass(TextInputFormat.class);
job1.setOutputFormatClass(TextOutputFormat.class);
job1.setPartitionerClass(Parti.class); //+++
// inputs to map.
FileInputFormat.addInputPath(job1, new Path(args[0]));
// single output from reducer.
FileOutputFormat.setOutputPath(job1, new Path(args[1]));
job1.waitForCompletion(true);
}
Mapper发出的键如下:
0,0
0,1
0,2
1,0
1,1
1,2
2,0
2,1
2,2
并且Reducer仅写入它接收的键和值。
答案 0 :(得分:1)
解决
我刚刚将static
添加到我的Parti
类,就像注释(user238607)所建议的mapper和reducer类一样。
public static class Parti extends Partitioner<Text, Text> {