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Posted to common-issues@hadoop.apache.org by "Gopal V (JIRA)" <ji...@apache.org> on 2018/02/05 18:44:01 UTC
[jira] [Updated] (HADOOP-11867) FS API: Add a high-performance
vectored Read to FSDataInputStream API
[ https://issues.apache.org/jira/browse/HADOOP-11867?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Gopal V updated HADOOP-11867:
-----------------------------
Labels: performance (was: )
> 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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