Anand,
Thank you for your answer, but wouldn't that mean that I would have to
serialize the files each time I need to run the job? And I would still
need to save the original files, so the NameNode still needs to take
care of them?
Please correct me if I'm missing something, I'm not very experienced
with Hadoop.
What do you think about using Cassandra?
Thanks
On Fri 24 Apr 2015 11:03:19 AM CEST, Chandra Mohan, Ananda Vel Murugan
wrote:
Apart from databases like Cassandra, you may check serialization formats like
Avro or Parquet
Regards,
Anand
-----Original Message-----
From: Marko Dinic [mailto:[email protected]]
Sent: Friday, April 24, 2015 2:23 PM
To: [email protected]
Subject: Large number of small files
Hello,
I'm not sure if this is the place to ask this question, but I'm still hopping
for an answer/advice.
Large number of small files are uploaded, about 8KB. I am aware that this is
not something that you're hopping for when working with Hadoop.
I was thinking about using HAR files and combined input, or sequence files. The
problem is, files are timestamped, and I need different subset in different
time, for example - one job needs to run on files that are uploaded during last
3 months, while next job might consider last 6 months. Naturally, as time
passes different subset of files is needed.
This means that I would need to make a sequence file (or a HAR) each time I run
a job, to have smaller number of mappers. On the other hand, I need the
original files so I could subset them. This means that DataNode is at constant
pressure, saving all of this in its memory.
How can I solve this problem?
I was also considering using Cassandra, or something like that, and to save the
file content inside of it, instead of saving it to files on HDFS. FIle content
is actually some measurement, that is, a vector of numbers, with some metadata.
Thanks
