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https://issues.apache.org/jira/browse/HADOOP-1470?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#action_12503632
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Raghu Angadi edited comment on HADOOP-1470 at 6/11/07 10:45 PM:
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The code Hairong included in the prev comment :
{quote}
{code:title=genericChecksums2.java}
abstract class Checker extends FSInputStream {
Checksum sum;
/** read a checksum verified chunk into buf at offset
* If there is a Checksum error, it retries a different replica
* If the buf does not have enough space to hold the chunk, throws an
* IllegalArgumentException
* returns the number of bytes read; -1 if end of file
*/
int readVerifiedChunk( byte[] buf, int offset );
/** read a chunk into buf at offset.
* It ends at the a checksum boundary or end of file or at any pos which could
be
* checksum verified, for example, at a block boundary in block-level-crc dfs
* data read have not been checksum verified
* If the buf does not have enough space to hold the chunk, throws an
* IllegalArgumentException
* returns the number of bytes read; -1 if end of file
*/
abstract int readChunk( byte[] buf, int offset, int len) throws IOException;
/** read a checksum */
abstract long readChecksum() throws IOException;
}
{code}
{quote}
This sounds fine. Except that that we don't need to {{extend FSInputStream}}.
This is just a utility. Any one who wants use this can implement this.
was:
The code Hairong included in the prev comment :
{quote}
{code:title=genericChecksums2.java}
abstract class Checker extends FSInputStream {
Checksum sum;
/** read a checksum verified chunk into buf at offset
* If there is a Checksum error, it retries a different replica
* If the buf does not have enough space to hold the chunk, throws an
IllegalArgumentException
* returns the number of bytes read; -1 if end of file
*/
int readVerifiedChunk( byte[] buf, int offset );
/** read a chunk into buf at offset.
* It ends at the a checksum boundary or end of file or at any pos which could
be checksum verified, for example, at a block boundary in block-level-crc dfs
* data read have not been checksum verified
* If the buf does not have enough space to hold the chunk, throws an
IllegalArgumentException
* returns the number of bytes read; -1 if end of file
*/
abstract int readChunk( byte[] buf, int offset, int len) throws IOException;
/** read a checksum */
abstract long readChecksum() throws IOException;
}
{code}
{quote}
This sounds fine. Except that that we don't need to {{extend FSInputStream}}.
This is just a utility. Any one who wants use this can implement this.
> Rework FSInputChecker and FSOutputSummer to support checksum code sharing
> between ChecksumFileSystem and block level crc dfs
> ----------------------------------------------------------------------------------------------------------------------------
>
> Key: HADOOP-1470
> URL: https://issues.apache.org/jira/browse/HADOOP-1470
> Project: Hadoop
> Issue Type: Improvement
> Components: fs
> Affects Versions: 0.12.3
> Reporter: Hairong Kuang
> Assignee: Hairong Kuang
> Fix For: 0.14.0
>
> Attachments: genericChecksum.patch
>
>
> Comment from Doug in HADOOP-1134:
> I'd prefer it if the CRC code could be shared with CheckSumFileSystem. In
> particular, it seems to me that FSInputChecker and FSOutputSummer could be
> extended to support pluggable sources and sinks for checksums, respectively,
> and DFSDataInputStream and DFSDataOutputStream could use these. Advantages of
> this are: (a) single implementation of checksum logic to debug and maintain;
> (b) keeps checksumming as close to possible to data generation and use. This
> patch computes checksums after data has been buffered, and validates them
> before it is buffered. We sometimes use large buffers and would like to guard
> against in-memory errors. The current checksum code catches a lot of such
> errors. So we should compute checksums after minimal buffering (just
> bytesPerChecksum, ideally) and validate them at the last possible moment
> (e.g., through the use of a small final buffer with a larger buffer behind
> it). I do not think this will significantly affect performance, and data
> integrity is a high priority.
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