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https://issues.apache.org/jira/browse/HADOOP-5795?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12707768#action_12707768
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dhruba borthakur commented on HADOOP-5795:
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If we adopt the approach that Doug has suggested, then the namenode still has
to search for each input path in the file system namespace. This approach still
has the advantage that the number of RPC calls are reduced. If we adopt Arun's
proposal that specifies a directory and the RPC-call returns the splits of all
the files in that directory, then it reduces the number of searches in the FS
namespace as well as the number of RPC calls. I was kind-of leaning towards
Arun's proposal, but Doug's approach is a little more flexible in nature, isn't
it?
> Add a bulk FIleSystem.getFileBlockLocations
> -------------------------------------------
>
> Key: HADOOP-5795
> URL: https://issues.apache.org/jira/browse/HADOOP-5795
> Project: Hadoop Core
> Issue Type: New Feature
> Components: dfs
> Affects Versions: 0.20.0
> Reporter: Arun C Murthy
> Assignee: Jakob Homan
> Fix For: 0.21.0
>
>
> Currently map-reduce applications (specifically file-based input-formats) use
> FileSystem.getFileBlockLocations to compute splits. However they are forced
> to call it once per file.
> The downsides are multiple:
> # Even with a few thousand files to process the number of RPCs quickly
> starts getting noticeable
> # The current implementation of getFileBlockLocations is too slow since
> each call results in 'search' in the namesystem. Assuming a few thousand
> input files it results in that many RPCs and 'searches'.
> It would be nice to have a FileSystem.getFileBlockLocations which can take in
> a directory, and return the block-locations for all files in that directory.
> We could eliminate both the per-file RPC and also the 'search' by a 'scan'.
> When I tested this for terasort, a moderate job with 8000 input files the
> runtime halved from the current 8s to 4s. Clearly this is much more important
> for latency-sensitive applications...
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