hadoop-hdfs-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Harsh J <ha...@cloudera.com>
Subject Re: How to combine input files for a MapReduce job
Date Mon, 13 May 2013 07:32:37 GMT
For "control number of mappers" question: You can use
which is designed to solve similar cases. However, you cannot beat the
speed you get out of a single large file (or a few large files), as
you'll still have file open/close overheads which will bog you down.

For "which file is being submitted to which" question: Having
https://issues.apache.org/jira/browse/MAPREDUCE-3678 in the
version/distribution of Apache Hadoop you use would help.

On Mon, May 13, 2013 at 12:50 PM, Agarwal, Nikhil
<Nikhil.Agarwal@netapp.com> wrote:
> Hi,
> I  have a 3-node cluster, with JobTracker running on one machine and
> TaskTrackers on other two. Instead of using HDFS, I have written my own
> FileSystem implementation. As an experiment, I kept 1000 text files (all of
> same size) on both the slave nodes and ran a simple Wordcount MR job. It
> took around 50 mins to complete the task. Afterwards, I concatenated all the
> 1000 files into a single file and then ran a Wordcount MR job, it took 35
> secs. From the JobTracker UI I could make out that the problem is because of
> the number of mappers that JobTracker is creating. For 1000 files it creates
> 1000 maps and for 1 file it creates 1 map (irrespective of file size).
> Thus, is there a way to reduce the number of mappers i.e. can I control the
> number of mappers through some configuration parameter so that Hadoop would
> club all the files until it reaches some specified size (say, 64 MB) and
> then make 1 map per 64 MB block?
> Also, I wanted to know how to see which file is being submitted to which
> TaskTracker or if that is not possible then how do I check if some data
> transfer is happening in between my slave nodes during a MR job?
> Sorry for so many questions and Thank you for your time.
> Regards,
> Nikhil

Harsh J

View raw message