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From "Taylor, Ronald C" <ronald.tay...@pnl.gov>
Subject What is the fastest way to get a large amount of data into the Hadoop HDFS file system (or Hbase)?
Date Tue, 28 Dec 2010 22:04:48 GMT

Folks,

We plan on uploading large amounts of data on a regular basis onto a Hadoop cluster, with
Hbase operating on top of Hadoop. Figure eventually on the order of multiple terabytes per
week. So - we are concerned about doing the uploads themselves as fast as possible from our
native Linux file system into HDFS. Figure files will be in, roughly, the 1 to 300 GB range.


Off the top of my head, I'm thinking that doing this in parallel using a Java MapReduce program
would work fastest. So my idea would be to have a file listing all the data files (full paths)
to be uploaded, one per line, and then use that listing file as input to a MapReduce program.


Each Mapper would then upload one of the data files (using "hadoop fs -copyFromLocal <source>
<dest>") in parallel with all the other Mappers, with the Mappers operating on all the
nodes of the cluster, spreading out the file upload across the nodes.

Does that sound like a wise way to approach this? Are there better methods? Anything else
out there for doing automated upload in parallel? We would very much appreciate advice in
this area, since we believe upload speed might become a bottleneck.

  - Ron Taylor

___________________________________________
Ronald Taylor, Ph.D.
Computational Biology & Bioinformatics Group

Pacific Northwest National Laboratory
902 Battelle Boulevard
P.O. Box 999, Mail Stop J4-33
Richland, WA  99352 USA
Office:  509-372-6568
Email: ronald.taylor@pnl.gov



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