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From "Chandra Mohan, Ananda Vel Murugan" <Ananda.Muru...@honeywell.com>
Subject RE: Large number of small files
Date Fri, 24 Apr 2015 09:03:19 GMT
Apart from databases like Cassandra, you may check serialization formats like Avro or Parquet


-----Original Message-----
From: Marko Dinic [mailto:marko.dinic@nissatech.com] 
Sent: Friday, April 24, 2015 2:23 PM
To: user@hadoop.apache.org
Subject: Large number of small files


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.


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