Hi - Check the logs first.
-----Original message-----
From: Bin Wang<binwang...@gmail.com>
Sent: Saturday 4th January 2014 21:47
To: dev@nutch.apache.org
Subject: Re: Independent Map Reduce to parse Nutch content (Cont.)
Hi Tejas,
I started an AWS instance and run hadoop in single node mode.
When I do..
hadoop -jar example.jar hdfsinput/ hdfsoutput/
Everything works perfect as I expected: a bunch of staff got printed to the
screen and both mappers and reducers got finished without question. In the end,
the expected output sits in the hdfs output directory.
However, when I tried to run the jar file without hadoop:
java -jar example.jar localinput/ localoutput/
It will finish all the mappers without problem but still.. errored out after
all the mappers....
Exception in thread "main" java.io.IOException: Job failed!
at org.apache.hadoop.mapred.JobClient.runJob(JobClient.java:784)
at arrow.ParseMapred.run(ParseMapred.java:70)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)
at arrow.ParseMapred.main(ParseMapred.java:18)
I am so confused now why my code doesnt work locally...
Based on my understanding, I can see Nutch constantly uses Hadoop API without
hadoop pre-installed.. why cant my code work..
Well, any hint or directional guidance will be appreciated, many thanks!
/usr/bin
On Sat, Jan 4, 2014 at 12:38 AM, Tejas Patil <tejas.patil...@gmail.com
<mailto:tejas.patil...@gmail.com>> wrote:
Hi Bin Wang,
I would suggest you to NOT use eclipse and run your code over command line. Use
logger statements and see the logs for full stack traces of the failure. In my
personal experience, logs are the best way to debug hadoop code compared to
Eclipse debugger.
Thanks,
Tejas
On Fri, Jan 3, 2014 at 8:56 PM, Bin Wang <binwang...@gmail.com
<mailto:binwang...@gmail.com>> wrote:
Hi,
I tried to modify the code here to parse the nutch content data...
http://svn.apache.org/viewvc/nutch/trunk/src/java/org/apache/nutch/parse/ParseSegment.java?view=markup
<http://svn.apache.org/viewvc/nutch/trunk/src/java/org/apache/nutch/parse/ParseSegment.java?view=markup>
And in the end of this email is a prototype that I have written to run map
reduce to calculate the HTML content length of each URL that I have scraped.
The mapper part runs perfectly fine as expected, however, the whole program
stops after all the mappers finished and the reducer did not get a chance to
run: (I am sure there are certain number of pages got scraped and in the
Eclipse console, there are same number of Mapper.. so I assume all the mapper
finished.)
Can anyone, who is pretty into writing java map reduce job take a look at my
code and see what the error might be... I am not a Java developer at all so any
debug trick or common sense will be appreciated!
(I heard that it is fairly hard to debug code written using hadoop API... is
that true?)
Many thanks!
/usr/bin
_____________________________________________________
Eclipse Console Info
Starting Mapper ...
Key: http://url1 <http://url1>
Result: 134943
Starting Mapper ...
Key: http://url2 <http://url2>
Result: 258588
Exception in thread "main" java.io.IOException: Job failed!
at org.apache.hadoop.mapred.JobClient.runJob(JobClient.java:784)
at arrow.ParseMapred.run(ParseMapred.java:68)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)
at arrow.ParseMapred.main(ParseMapred.java:18)
_____________________________________________________
// my code
package example;
import ...;
public class ParseMapred extends Configured implements Tool,
Mapper<WritableComparable<?>, Content, Text, IntWritable>,
Reducer<Text, IntWritable, Text, IntWritable> {
public static void main(String[] args) throws Exception {
int res = ToolRunner.run(NutchConfiguration.create(),
new ParseMapred(), args);
System.exit(res);
}
public void configure(JobConf job) {
setConf(job);
}
public void close() throws IOException {}
public void reduce(Text key, Iterator<IntWritable> values,
OutputCollector<Text, IntWritable> output, Reporter
reporter)
throws IOException {
System.out.println("Starting Reducer ...");
System.out.println("Reducer: " + "key" + key);
output.collect(key, values.next()); // collect first value
}
public void map(WritableComparable<?> key, Content content,
OutputCollector<Text, IntWritable> output, Reporter
reporter)
throws IOException {
Text url = new Text();
IntWritable result = new IntWritable();
url.set("fail");
result = new IntWritable(1);
try {
System.out.println("Starting Mapper ...");
url.set(key.toString());
result = new IntWritable(content.getContent().length);
System.out.println("Key: " + url);
System.out.println("Result: " + result);
output.collect(url, result);
} catch (Exception e) {
// TODO Auto-generated catch block
output.collect(url, result);
}
}
public int run(String[] args) throws Exception {
JobConf job = new NutchJob(getConf());
job.setJobName("ParseData");
FileInputFormat.addInputPath(job, new Path("/Users/.../data/"));
FileOutputFormat.setOutputPath(job, new Path("/Users/.../result"));
job.setInputFormat(SequenceFileInputFormat.class);
job.setOutputFormat(TextOutputFormat.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
job.setMapperClass(ParseMapred.class);
job.setReducerClass(ParseMapred.class);
JobClient.runJob(job);
return 0;
}
}
