In some scenarios you have gzipped files as input for your map reduce
job (apache logfiles is a common example).
Now some of those files are several hundred megabytes and as such will
be split by HDFS in several blocks.
When looking at a real 116MiB file on HDFS I see this (4 nodes, replication = 2)
Total number of blocks: 2
25063947863662497: 10.10.138.62:50010 10.10.138.61:50010
1014249434553595747: 10.10.138.64:50010 10.10.138.63:50010
As you can see the file has been distributed over all 4 nodes.
When actually reading those files they are unsplittable due to the
nature of the Gzip codec.
So a job will (in the above example) ALWAYS need to pull "the other
half" of the file over the network, if a file is bigger and the
cluster is bigger then the percentage of the file that goes over the
network will probably increase.
Now if I can tell HDFS that a ".gz" file should always be "100% local"
for the node that will be doing the processing this would reduce the
network IO during the job dramatically.
Especially if you want to run several jobs against the same input.
So my question is: Is there a way to force/tell HDFS to make sure that
a datanode that has blocks of this file must always have ALL blocks of