I am using the mapred API of Hadoop 1.0.  I want to make a job that does
not really depend on any input (the job conf supplies all the info needed
in Mapper).  What is a good way to do this?

What I have done so far is write a job in which MyMapper.configure(..)
reads all the real input from the JobConf, and MyMapper.map(..) ignores
the given key and value, writing the output implied by the JobConf.  I set
the InputFormat to TextInputFormat and the input paths to be a list of one
filename; the named file contains one line of text (the word "one"),
terminated by a newline.  When I run this job (on Linux, hadoop-1.0.0), I
find it has two map tasks --- one reads the first two bytes of my
non-input file, and other reads the last two bytes of my non-input file!
How can I make a job with just one map task?

Thanks,
Mike

On closer inspection, I see that of my two tasks: the first processes 1
input record and the other processes 0 input records.  So I think this
solution is correct.  But perhaps it is not the most direct way to get the
job done?
From:   Mike Spreitzer/Watson/IBM@IBMUS
To:     [EMAIL PROTECTED],
Date:   02/28/2013 04:18 PM
Subject:        How to make a MapReduce job with no input?

I am using the mapred API of Hadoop 1.0.  I want to make a job that does
not really depend on any input (the job conf supplies all the info needed
in Mapper).  What is a good way to do this?

What I have done so far is write a job in which MyMapper.configure(..)
reads all the real input from the JobConf, and MyMapper.map(..) ignores
the given key and value, writing the output implied by the JobConf.  I set
the InputFormat to TextInputFormat and the input paths to be a list of one
filename; the named file contains one line of text (the word "one"),
terminated by a newline.  When I run this job (on Linux, hadoop-1.0.0), I
find it has two map tasks --- one reads the first two bytes of my
non-input file, and other reads the last two bytes of my non-input file!
How can I make a job with just one map task?

Thanks,
Mike

Below is some code I use.  Basically, the number of iterations
is the number of fake records to supply to each mapper.  You control
the number of mappers via the jobconf.
>  public static class EmptySplit implements InputSplit {
>     public void write(DataOutput out) throws IOException { }
>     public void readFields(DataInput in) throws IOException { }
>     public long getLength() { return 0L; }
>     public String[] getLocations() { return new String[0]; }
>   }
>
>   public static class FFTBenchInputFormat extends Configured
>       implements InputFormat<IntWritable,IntWritable> {
>     public InputSplit[] getSplits(JobConf conf, int numSplits) {
>       InputSplit[] ret = new InputSplit[numSplits];
>       for (int i = 0; i < numSplits; ++i) {
>         ret[i] = new EmptySplit();
>       }
>       return ret;
>     }
>     public RecordReader<IntWritable,IntWritable> getRecordReader(
>         InputSplit ignored, JobConf conf, Reporter reporter)
>         throws IOException {
>       final int size = conf.getInt("fftbench.map.size", 1);
>       if (size < 0) throw new IOException("Invalid map size: " + size);
>       final int iterations = conf.getInt("fftbench.map.iterations", 1);
>       if (iterations < 0) throw new IOException("Invalid map iterations: " + size);
>     return new RecordReader<IntWritable,IntWritable>() {
>         private int records = 0;
>         private int emitCount = 0;
>
>         public boolean next(IntWritable key, IntWritable value)
>             throws IOException {
>           key.set(size);
>           int emit = emitCount++;
>           value.set(emit);
>           return records++ < iterations;
>         }
>         public IntWritable createKey() { return new IntWritable(); }
>         public IntWritable createValue() { return new IntWritable(); }
>         public long getPos() throws IOException { return records; }
>         public void close() throws IOException { }
>         public float getProgress() throws IOException {
>           return records / ((float)iterations);
>         }
>       };
>     }
>   }
On 2/28/2013 4:16 PM, Mike Spreitzer wrote:
> I am using the mapred API of Hadoop 1.0.  I want to make a job that does
> not really depend on any input (the job conf supplies all the info
> needed in Mapper).  What is a good way to do this?
>
> What I have done so far is write a job in which MyMapper.configure(..)
> reads all the real input from the JobConf, and MyMapper.map(..) ignores
> the given key and value, writing the output implied by the JobConf.  I
> set the InputFormat to TextInputFormat and the input paths to be a list
> of one filename; the named file contains one line of text (the word
> "one"), terminated by a newline.  When I run this job (on Linux,
> hadoop-1.0.0), I find it has two map tasks --- one reads the first two
> bytes of my non-input file, and other reads the last two bytes of my
> non-input file!  How can I make a job with just one map task?
>
> Thanks,
> Mike

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Mike,

To do this for the more general case of creating N map jobs with each job
receiving the one record <i, n>, where i ranges from 0 to n-1, I wrote
an InputFormat, InputSplit, and RecordReader Hadoop class. The sample code
is here <http://goo.gl/npKfP>. I think I wrote those for Hadoop 0.19, so
they may need some tweaking for subsequent versions.

Jeff

On Thu, Feb 28, 2013 at 4:25 PM, Mike Spreitzer <[EMAIL PROTECTED]> wrote:

> On closer inspection, I see that of my two tasks: the first processes 1
> input record and the other processes 0 input records.  So I think this
> solution is correct.  But perhaps it is not the most direct way to get the
> job done?
>
>
>
>
> From:        Mike Spreitzer/Watson/IBM@IBMUS
> To:        [EMAIL PROTECTED],
> Date:        02/28/2013 04:18 PM
> Subject:        How to make a MapReduce job with no input?
> ------------------------------
>
>
>
> I am using the mapred API of Hadoop 1.0.  I want to make a job that does
> not really depend on any input (the job conf supplies all the info needed
> in Mapper).  What is a good way to do this?
>
> What I have done so far is write a job in which MyMapper.configure(..)
> reads all the real input from the JobConf, and MyMapper.map(..) ignores the
> given key and value, writing the output implied by the JobConf.  I set the
> InputFormat to TextInputFormat and the input paths to be a list of one
> filename; the named file contains one line of text (the word "one"),
> terminated by a newline.  When I run this job (on Linux, hadoop-1.0.0), I
> find it has two map tasks --- one reads the first two bytes of my non-input
> file, and other reads the last two bytes of my non-input file!  How can I
> make a job with just one map task?
>
> Thanks,
> Mike
>

I made a https://github.com/edwardcapriolo/DualInputFormat for hive.
Always returns 1 split with 1 run. You can write the same type of
thing to create N splits.

On Thu, Feb 28, 2013 at 8:41 PM, Jeff Kubina <[EMAIL PROTECTED]> wrote:
> Mike,
>
> To do this for the more general case of creating N map jobs with each job
> receiving the one record <i, n>, where i ranges from 0 to n-1, I wrote an
> InputFormat, InputSplit, and RecordReader Hadoop class. The sample code is
> here. I think I wrote those for Hadoop 0.19, so they may need some tweaking
> for subsequent versions.
>
> Jeff
>
> On Thu, Feb 28, 2013 at 4:25 PM, Mike Spreitzer <[EMAIL PROTECTED]> wrote:
>>
>> On closer inspection, I see that of my two tasks: the first processes 1
>> input record and the other processes 0 input records.  So I think this
>> solution is correct.  But perhaps it is not the most direct way to get the
>> job done?
>>
>>
>>
>>
>> From:        Mike Spreitzer/Watson/IBM@IBMUS
>> To:        [EMAIL PROTECTED],
>> Date:        02/28/2013 04:18 PM
>> Subject:        How to make a MapReduce job with no input?
>> ________________________________
>>
>>
>>
>> I am using the mapred API of Hadoop 1.0.  I want to make a job that does
>> not really depend on any input (the job conf supplies all the info needed in
>> Mapper).  What is a good way to do this?
>>
>> What I have done so far is write a job in which MyMapper.configure(..)
>> reads all the real input from the JobConf, and MyMapper.map(..) ignores the
>> given key and value, writing the output implied by the JobConf.  I set the
>> InputFormat to TextInputFormat and the input paths to be a list of one
>> filename; the named file contains one line of text (the word "one"),
>> terminated by a newline.  When I run this job (on Linux, hadoop-1.0.0), I
>> find it has two map tasks --- one reads the first two bytes of my non-input
>> file, and other reads the last two bytes of my non-input file!  How can I
>> make a job with just one map task?
>>
>> Thanks,
>> Mike
>
>

The default # of map tasks is set to 2 (via mapred.map.tasks from
mapred-default.xml) - which explains your 2-map run for even one line
of text.

For running with no inputs, take a look at Sleep Job's EmptySplits
technique on trunk:
http://svn.apache.org/viewvc/hadoop/common/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/SleepJob.java?view=markup
(~line 70)

On Fri, Mar 1, 2013 at 2:46 AM, Mike Spreitzer <[EMAIL PROTECTED]> wrote:
> I am using the mapred API of Hadoop 1.0.  I want to make a job that does not
> really depend on any input (the job conf supplies all the info needed in
> Mapper).  What is a good way to do this?
>
> What I have done so far is write a job in which MyMapper.configure(..) reads
> all the real input from the JobConf, and MyMapper.map(..) ignores the given
> key and value, writing the output implied by the JobConf.  I set the
> InputFormat to TextInputFormat and the input paths to be a list of one
> filename; the named file contains one line of text (the word "one"),
> terminated by a newline.  When I run this job (on Linux, hadoop-1.0.0), I
> find it has two map tasks --- one reads the first two bytes of my non-input
> file, and other reads the last two bytes of my non-input file!  How can I
> make a job with just one map task?
>
> Thanks,
> Mike

--
Harsh J