Yes.
The hadoop is very flexible for underline storage system. It is in your
control, how to utilize the cluster's resource, include CPU, memory, IO and
network bandwidth.
Check out hadoop NLineInportFormat, it maybe the right choice for your case.
You can put all the metadata of your files (data) into one text file, and send
this text file to your MR job.
Each mapper will get one line text from the above file, and start to process
data representing by this one line text.
Is it a good solution for you? You have to judge it by yourself. Keep in mind
followings:
1) Normally, the above case is good for a MR job to load data from a third
party system, for CPU intensive jobs.2) You do utilize the cluster, as if you
have 100 mapper tasks, and 100 files to be processed, you get pretty good
concurrency.
But:
1) Are your files (or data) equally split around the third party system? In the
above example, for 100 files (or chunks of data), if one file is 10G, and the
rest are only 100M, then one mapper will take MUCH longer than the rest. You
will have lone tail problem, and hurt overall performance.2) NO data locality
advantage compared to HDFS. All the mappers need to load the data from a third
party system remotely.3) If each file (or chunk data) are very large, what
about fail over? For example, if you have 100 mapper task slots, but only 20
files, with 10G data each, then you under-utilize your cluster resource, as
only 20 mappers will handle them, the rest 80 mapper tasks will be just idle.
More important, if one mapper failed, all the already processed data has to be
discard. Another mapper has to restart from beginning for this chunk of data.
Your overall performance is hurt.
As you can see, you get a lot of benefits from the HDFS. You lost all of them.
Sometimes you have no other choices, but have to load the data on the fly from
some 3rd party system. But you need to think above, and try to seek all the
benefits which HDFS can provide to you, from the 3rd party system, if you can.
Yong
Date: Fri, 10 Jan 2014 01:21:19 -0800
Subject: Reading multiple input files.
From: kchew...@gmail.com
To: user@hadoop.apache.org
How does a MR job read multiple input files from different locations?
What if the input files are not in hdfs and located on different servers? Do I
have to copy them to hdfs first and instruct my MR job to read from them? Can I
instruct my MR job to read directly from those servers?
Thanks.
Kim
