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From "Gopal V (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (HADOOP-11867) FS API: Add a high-performance vectored Read to FSDataInputStream API
Date Mon, 05 Feb 2018 18:44:01 GMT

     [ https://issues.apache.org/jira/browse/HADOOP-11867?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Gopal V updated HADOOP-11867:
-----------------------------
    Affects Version/s:     (was: 2.8.0)
                       3.0.0

> FS API: Add a high-performance vectored Read to FSDataInputStream API
> ---------------------------------------------------------------------
>
>                 Key: HADOOP-11867
>                 URL: https://issues.apache.org/jira/browse/HADOOP-11867
>             Project: Hadoop Common
>          Issue Type: New Feature
>          Components: hdfs-client
>    Affects Versions: 3.0.0
>            Reporter: Gopal V
>            Assignee: Gopal V
>            Priority: Major
>              Labels: performance
>
> The most significant way to read from a filesystem in an efficient way is to let the
FileSystem implementation handle the seek behaviour underneath the API to be the most efficient
as possible.
> A better approach to the seek problem is to provide a sequence of read locations as part
of a single call, while letting the system schedule/plan the reads ahead of time.
> This is exceedingly useful for seek-heavy readers on HDFS, since this allows for potentially
optimizing away the seek-gaps within the FSDataInputStream implementation.
> For seek+read systems with even more latency than locally-attached disks, something like
a {{readFully(long[] offsets, ByteBuffer[] chunks)}} would take of the seeks internally while
reading chunk.remaining() bytes into each chunk (which may be {{slice()}}ed off a bigger buffer).
> The base implementation can stub in this as a sequence of seeks + read() into ByteBuffers,
without forcing each FS implementation to override this in any way.



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