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https://issues.apache.org/jira/browse/HADOOP-11794?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16566294#comment-16566294
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smarthan edited comment on HADOOP-11794 at 8/2/18 7:42 AM:
-----------------------------------------------------------
Hi [~yzhangal], I have a doubt that whether there is a bug in
RetriableFileCopyCommand.copyBytes( ) when enable blocksperchunk .
{code:java}
int bytesRead = readBytes(inStream, buf, sourceOffset);
while (bytesRead >= 0) {
if (chunkLength > 0 &&
(totalBytesRead + bytesRead) >= chunkLength) {
bytesRead = (int)(chunkLength - totalBytesRead);
finished = true;
}
totalBytesRead += bytesRead;
//action == FileAction.APPEND always false when blocksperchunk >= 1,
//the sourceOffset will never been change
//readBytes(inStream, buf, sourceOffset) will always start from the same
position 'sourceOffset'
//so the buf[] always read same data, and result in wrong split copy finally
if (action == FileAction.APPEND) {
sourceOffset += bytesRead;
}
outStream.write(buf, 0, bytesRead);
updateContextStatus(totalBytesRead, context, source2);
if (finished) {
break;
}
bytesRead = readBytes(inStream, buf, sourceOffset);
}
{code}
I merge this patch to branch *cdh5.10*, and when I set blocksperchunk >= 1, the
copy of data will be different form source.
I debug and find this problem, and when I modify the condition as follow, it
works.
{code:java}
if (action == FileAction.APPEND || (source2.isSplit() && sourceOffset > 0)) {
sourceOffset += bytesRead;
}{code}
I am not sure whether it is a bug or just caused by version, please look at it
if possible, thanks.
was (Author: smarthan):
Hi [~yzhangal], I have a doubt that whether there is a bug in
RetriableFileCopyCommand.copyBytes( ) when enable blocksperchunk .
{code:java}
int bytesRead = readBytes(inStream, buf, sourceOffset);
while (bytesRead >= 0) {
if (chunkLength > 0 &&
(totalBytesRead + bytesRead) >= chunkLength) {
bytesRead = (int)(chunkLength - totalBytesRead);
finished = true;
}
totalBytesRead += bytesRead;
//action == FileAction.APPEND always false when blocksperchunk >= 1,
//the sourceOffset will never been change
//readBytes(inStream, buf, sourceOffset) will always start from the same
position 'sourceOffset'
//so the buf[] always read same data, and result in wrong split copy finally
if (action == FileAction.APPEND) {
sourceOffset += bytesRead;
}
outStream.write(buf, 0, bytesRead);
updateContextStatus(totalBytesRead, context, source2);
if (finished) {
break;
}
bytesRead = readBytes(inStream, buf, sourceOffset);
}
{code}
I merge this patch to branch cdh5.10, and when I set blocksperchunk >= 1, the
copy of data will be different form source.
I debug and find this problem, and when I modify the condition as follow, it
works.
{code:java}
if (action == FileAction.APPEND || (source2.isSplit() && sourceOffset > 0)) {
sourceOffset += bytesRead;
}{code}
I am not sure whether it is a bug or just caused by version, please look at it
if possible, thanks.
> Enable distcp to copy blocks in parallel
> ----------------------------------------
>
> Key: HADOOP-11794
> URL: https://issues.apache.org/jira/browse/HADOOP-11794
> Project: Hadoop Common
> Issue Type: Improvement
> Components: tools/distcp
> Affects Versions: 0.21.0
> Reporter: dhruba borthakur
> Assignee: Yongjun Zhang
> Priority: Major
> Fix For: 2.9.0, 3.0.0-alpha4
>
> Attachments: HADOOP-11794.001.patch, HADOOP-11794.002.patch,
> HADOOP-11794.003.patch, HADOOP-11794.004.patch, HADOOP-11794.005.patch,
> HADOOP-11794.006.patch, HADOOP-11794.007.patch, HADOOP-11794.008.patch,
> HADOOP-11794.009.patch, HADOOP-11794.010.branch2.002.patch,
> HADOOP-11794.010.branch2.patch, HADOOP-11794.010.patch, MAPREDUCE-2257.patch
>
>
> The minimum unit of work for a distcp task is a file. We have files that are
> greater than 1 TB with a block size of 1 GB. If we use distcp to copy these
> files, the tasks either take a long long long time or finally fails. A better
> way for distcp would be to copy all the source blocks in parallel, and then
> stich the blocks back to files at the destination via the HDFS Concat API
> (HDFS-222)
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