Thank you all. In fact, I don't expect that this way can help to enhance
the performance.
I need to process 3 different logs (with different format). I just want
to sart all these 3 logs processing at the same time , all in just this one
program. but I can give different separator to each thread to create maps
to handle different logs.
2012/12/13 Yang <teddyyyy...@gmail.com>
> but I do have run across some situations where I could benefit from
> multi-threading: if your hadoop mapper is prone to random access IO (such
> as looking up a TFile, or HBase, which ultimately makes a network call and
> then looks into a file segment), having multiple threads could utilize the
> CPU while IO is going on
>
>
> On Wed, Dec 12, 2012 at 10:47 AM, Harsh J <ha...@cloudera.com> wrote:
>
>> Exactly - A job is already designed to be properly parallel w.r.t. its
>> input, and this would just add additional overheads of job setup and
>> scheduling. If your per-record processing requires threaded work,
>> consider using the MultithreadedMapper/Reducer classes instead.
>>
>> On Wed, Dec 12, 2012 at 10:53 PM, Yang <teddyyyy...@gmail.com> wrote:
>> > I think it won't help much, since in a hadoop cluster, people already
>> > allocate "SLOTS" to be the number of cores, supposedly the inherent
>> > parallelism can be already exploited, since different mappers/reducers
>> are
>> > completely independent.
>> >
>> >
>> > On Wed, Dec 12, 2012 at 2:09 AM, Yu Yang <clouder...@gmail.com> wrote:
>> >>
>> >> Dears,
>> >>
>> >> I suddenly got this idea to do mapreduce job in a muti-thread way.
>> >> I don't know if it can work. Could anyone give me some advices?
>> >> Here is the java code:
>> >>
>> >>
>> >> import java.io.IOException;
>> >> import org.apache.hadoop.conf.Configuration;
>> >> import org.apache.hadoop.fs.Path;
>> >> import org.apache.hadoop.io.LongWritable;
>> >> import org.apache.hadoop.io.Text;
>> >> import org.apache.hadoop.mapreduce.Job;
>> >> import org.apache.hadoop.mapreduce.Mapper;
>> >> import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
>> >> import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
>> >> import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
>> >> import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
>> >>
>> >> public class LogProcessApp extends Thread {
>> >>
>> >> private static String sep;
>> >> private String x2;
>> >> private String x3;
>> >>
>> >> public LogProcessApp(String arg1,String arg2,String arg3){
>> >> sep=arg1;
>> >> x2=arg2;
>> >> x3=arg3;
>> >> }
>> >>
>> >> public static class CM extends Mapper<LongWritable, Text, Text, Text>{
>> >> private Text keyvar = new Text();
>> >> private Text valvar = new Text();
>> >> public void map(LongWritable key, Text value, Context context)
>> >> throws IOException, InterruptedException {
>> >> String line = value.toString();
>> >> try{
>> >> String data[] = line.split(sep);
>> >> keyvar.set(data[0]);
>> >> valvar.set(data[1]);
>> >> context.write(keyvar,valvar);
>> >> } catch (Exception e) {
>> >> return;
>> >> }
>> >> }
>> >> }
>> >>
>> >> public void run(){
>> >> Configuration conf = new Configuration();
>> >> Job job = null;
>> >> try {
>> >> job = new Job(conf);
>> >> } catch (IOException e1) {
>> >> // TODO Auto-generated catch block
>> >> e1.printStackTrace();
>> >> }
>> >>
>> >> job.setJobName("XXXJob");
>> >> job.setJarByClass(CMR.class);
>> >>
>> >> job.setOutputKeyClass(Text.class);
>> >> job.setOutputValueClass(Text.class);
>> >>
>> >> job.setMapperClass(CM.class);
>> >>
>> >> job.setInputFormatClass(TextInputFormat.class);
>> >> job.setOutputFormatClass(TextOutputFormat.class);
>> >>
>> >> try {
>> >> FileInputFormat.addInputPath(job, new Path(x2));
>> >> } catch (IOException e) {
>> >> // TODO Auto-generated catch block
>> >> e.printStackTrace();
>> >> }
>> >> FileOutputFormat.setOutputPath(job, new Path(x3));
>> >>
>> >> try {
>> >> job.submit();
>> >> } catch (IOException e) {
>> >> // TODO Auto-generated catch block
>> >> e.printStackTrace();
>> >> } catch (InterruptedException e) {
>> >> // TODO Auto-generated catch block
>> >> e.printStackTrace();
>> >> } catch (ClassNotFoundException e) {
>> >> // TODO Auto-generated catch block
>> >> e.printStackTrace();
>> >> }
>> >>
>> >> }
>> >>
>> >>
>> >> public static void main(String args[]){
>> >> LogProcessApp lpa1=new LogProcessApp(args[0],args[1],args[3]);
>> >> LogProcessApp lpa2=new LogProcessApp(args[4],args[5],args[6]);
>> >> LogProcessApp lpa3=new LogProcessApp(args[7],args[8],args[9]);
>> >> lpa1.start();
>> >> lpa2.start();
>> >> lpa3.start();
>> >> }
>> >> }
>> >
>> >
>>
>>
>>
>> --
>> Harsh J
>>
>
>
