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https://issues.apache.org/jira/browse/HADOOP-14520?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16149691#comment-16149691
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Georgi Chalakov edited comment on HADOOP-14520 at 8/31/17 10:08 PM:
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Thank you for adding all these fixes. Stream capabilities looks like an useful
feature.
Re:flush()
FSDataOutputStream doesn't overwrite flush() and a normal flush() call on
application level would not execute BlockBlobAppendStream::flush(). When the
compaction is disabled hflush/hsync are nop and the performance of
BlockBlobAppendStream for all operations is the same (or better) than before.
Re:more than one append stream
We take a lease on the blob, that means at any point of time you can have one
append stream only. If we had more than one append stream opened at the same
time, we couldn't guarantee the order of write operations.
I have added hsync() call and made isclosed volatile.
Re:close()
I think the first exception is the best indication what went wrong. After an
exception, close() is just best effort. I don't know how useful for a client
would be to continue after IO related exception, but if that is necessary, the
client can continue. If block compaction is enabled, the client can go and read
all the data until the last successful hflush()/hsync(). When the block
compaction is disabled, we grantee nothing. We may or may not have the data
stored in the service.
was (Author: georgi):
Thank you for adding all these fixes. Stream capabilities looks like an useful
feature.
Re:flush()
FSDataOutputStream doesn't overwrite flush() and a normal flush() call on
application level would not execute BlockBlobAppendStream::flush(). When the
compaction is disabled hflush/hsync are nop and the performance of
BlockBlobAppendStream for all operations is the same (or better) than before.
Re:more than one append stream
We take a lease on the blob, that means at any point of time you can have one
append stream only. If we had more than one append stream opened at the same
time, we couldn't guarantee the order of write operations.
I have added hsync() call and made isclosed volatile.
Re:close()
I think the first exception is the best indication what went wrong. After an
exception, close() is just best effort. I don't know how useful for a client
would be to continue after IO related exception, but if that is necessary, the
client can continue. If block compaction is enabled, the client can go and read
all the data until last hflush()/hsync(). When the block compaction is
disabled, we grantee nothing. We may or may not have the data stored in the
service.
> WASB: Block compaction for Azure Block Blobs
> --------------------------------------------
>
> Key: HADOOP-14520
> URL: https://issues.apache.org/jira/browse/HADOOP-14520
> Project: Hadoop Common
> Issue Type: Improvement
> Components: fs/azure
> Affects Versions: 3.0.0-alpha3
> Reporter: Georgi Chalakov
> Assignee: Georgi Chalakov
> Attachments: HADOOP-14520-006.patch, HADOOP-14520-008.patch,
> HADOOP-14520-009.patch, HADOOP-14520-05.patch, HADOOP_14520_07.patch,
> HADOOP_14520_08.patch, HADOOP_14520_09.patch, HADOOP_14520_10.patch,
> HADOOP-14520-patch-07-08.diff, HADOOP-14520-patch-07-09.diff
>
>
> Block Compaction for WASB allows uploading new blocks for every hflush/hsync
> call. When the number of blocks is above 32000, next hflush/hsync triggers
> the block compaction process. Block compaction replaces a sequence of blocks
> with one block. From all the sequences with total length less than 4M,
> compaction chooses the longest one. It is a greedy algorithm that preserve
> all potential candidates for the next round. Block Compaction for WASB
> increases data durability and allows using block blobs instead of page blobs.
> By default, block compaction is disabled. Similar to the configuration for
> page blobs, the client needs to specify HDFS folders where block compaction
> over block blobs is enabled.
> Results for HADOOP_14520_07.patch
> tested endpoint: fs.azure.account.key.hdfs4.blob.core.windows.net
> Tests run: 777, Failures: 0, Errors: 0, Skipped: 155
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