Thank you a lot for your answer Jean-Daniel. I think now I understand how
that scenario works.
I have another scenario (probably not doable with mapred thing though) - I
need to get total rows count for whole table. I think I could use Reporter
to increment a counter in map phase, but how can I get the counter value
saved into 'results' table after all? Can you please advice how can I
achieve that? Also, what is preferred way to get table row count?
Thank you for your help!
Pavel
2008/8/1 Jean-Daniel Cryans <[EMAIL PROTECTED]>
> Pavel,
>
> Since each map processes only one region, that a row is only stored in one
> region and that all intermediate keys from a given mapper goes to a single
> reducer, there will be no stale data in this situation.
>
> J-D
>
> On Wed, Jul 30, 2008 at 10:09 AM, Pavel <[EMAIL PROTECTED]> wrote:
>
> > Hi,
> >
> > I feel lack of mapreduce approach understanding and would like to ask
> some
> > questions (mainly on its reduce part). Below is reduce job that gets
> values
> > count for given row key and inserts resulting value into other table
> using
> > the same row key.
> >
> > What makes me doubt is that I cannot figure out how would that code work
> if
> > there're several redurers are running. Is it possible that they will
> > process
> > values for same row key and as consequence write stale data into the
> table?
> > Say reducerA has counted total for 5 messages while reducerB for 3
> > messages,
> > would that all end up with 8 value in resulting table?
> >
> > Thank you.
> > Pavel
> >
> > public class MessagesTableReduce extends TableReduce<Text, LongWritable>
> {
> >
> > public void reduce(Text key, Iterator<LongWritable> values,
> > OutputCollector<Text, MapWritable> output, Reporter reporter)
> > throws IOException {
> >
> > System.out.println("REDUCE: processing messages for author: " +
> > key.toString());
> >
> > int total = 0;
> > while (values.hasNext()) {
> > values.next();
> > total++;
> > }
> >
> > MapWritable map = new MapWritable();
> > map.put(new Text("messages:sent"), new
> > ImmutableBytesWritable(String.valueOf(total).getBytes()));
> > output.collect(key, map);
> > }
> > }
> >
>
