Hello :
In hadoop InputFormat are always based on the InputFileFormat ,
But Now I will get data from a web service application. The data will be
wrapped as ResultSet type. Now I am wandering " should I write the
ResultSet to a file And then read out to do mapreduce job. Or How can I
pro
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I run map/reduce job through streaming, and notice that "local bytes
written/read" in my job is always many times higher than the "hdfs
bytes"? but if i run the job straight through java, this problem goes
away.
Why does this happen? Is it because jvm memory is not enough and use the
disk for cach
Thanks ..
I converted the text-->string --> Float.
I am trying to calculate the average of a very large set of numbers. You are
right...I plan to use a dummy key (its not null as i said before) as input to
reduce. Then in reduce when sorted, i will have a single record as
> which i will use to
Each mapper works on only one file split, which is either from file1 or
file2 in your case. So the value for map.input.file gives you the exact
information you need.
Runping
On 10/23/08 11:09 AM, "Steve Gao" <[EMAIL PROTECTED]> wrote:
> Thanks, Amogh. But my case is slightly different. The
Hi,
I have lot's of small jobs and would like to compute the aggregate
running time of all the mappers and reducers in my job history rather
than tally the numbers by hand through the web interface. I know that
the Reporter object can be used to output performance numbers for a
single job
On Oct 26, 2008, at 8:38 AM, chaitanya krishna wrote:
I forgot to mention that although the number of map tasks are set in
the
code as I mentioned before, the actual number of map tasks are not
essentially the same number but is very close to this number.
The number of reduces is precisely
I forgot to mention that although the number of map tasks are set in the
code as I mentioned before, the actual number of map tasks are not
essentially the same number but is very close to this number.
V.V.Chaitanya Krishna
IIIT,Hyderabad
India
On Sun, Oct 26, 2008 at 4:29 PM, chaitanya krishna <
Hi,
In order to have different number of map tasks for each of the jobs, in the
run method of the code , I had the following syntax:
conf.setNumMapTasks(num); // for number of map tasks
conf.setNumReduceTasks(num); // for number of reduce tasks
conf is the JobConf object and num is the number
