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From "Subramanyam Pattipaka (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HADOOP-13403) AzureNativeFileSystem rename/delete performance improvements
Date Sat, 30 Jul 2016 07:31:20 GMT

    [ https://issues.apache.org/jira/browse/HADOOP-13403?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15400516#comment-15400516
] 

Subramanyam Pattipaka commented on HADOOP-13403:
------------------------------------------------

[~cnauroth], thanks for your comments. I have incorporated your comments. I have fixed issues
showed by findbugs and also fixed new errors shown with checkstyle.

Regarding you questions on thread pools, I have removed null check for thread pool. I have
retained other checks. getThreadPool may be called with very large value. It could be a naive
mistake from user application. Hive script may pass this user configuration dynamically and
the current thread may fail to allocate memory for thread pool. We don't want to fail the
operation in this case. Instead we want to do serial processing which could go through and
operation can be success. I have added unit tests to verify the behavior in case of any exception
raised while creating thread pool.

Not sure why you are seeing this assertion while running tests. I have modified these test
cases as per your recommendation. If you still see the issue then I can take a look. I have
verified that test cases are passing with latest changes (patch 003).


> AzureNativeFileSystem rename/delete performance improvements
> ------------------------------------------------------------
>
>                 Key: HADOOP-13403
>                 URL: https://issues.apache.org/jira/browse/HADOOP-13403
>             Project: Hadoop Common
>          Issue Type: Bug
>          Components: azure
>    Affects Versions: 2.7.2
>            Reporter: Subramanyam Pattipaka
>            Assignee: Subramanyam Pattipaka
>             Fix For: 2.9.0
>
>         Attachments: HADOOP-13403-001.patch, HADOOP-13403-002.patch
>
>
> WASB Performance Improvements
> Problem
> -----------
> Azure Native File system operations like rename/delete which has large number of directories
and/or files in the source directory are experiencing performance issues. Here are possible
reasons
> a)	We first list all files under source directory hierarchically. This is a serial operation.

> b)	After collecting the entire list of files under a folder, we delete or rename files
one by one serially.
> c)	There is no logging information available for these costly operations even in DEBUG
mode leading to difficulty in understanding wasb performance issues.
> Proposal
> -------------
> Step 1: Rename and delete operations will generate a list all files under the source
folder. We need to use azure flat listing option to get list with single request to azure
store. We have introduced config fs.azure.flatlist.enable to enable this option. The default
value is 'false' which means flat listing is disabled.
> Step 2: Create thread pool and threads dynamically based on user configuration. These
thread pools will be deleted after operation is over.  We are introducing introducing two
new configs
> 	a)	fs.azure.rename.threads : Config to set number of rename threads. Default value is
0 which means no threading.
> 	b)	fs.azure.delete.threads: Config to set number of delete threads. Default value is
0 which means no threading.
> 	We have provided debug log information on number of threads not used for the operation
which can be useful .
> 	Failure Scenarios:
> 	If we fail to create thread pool due to ANY reason (for example trying create with thread
count with large value such as 1000000), we fall back to serialization operation. 
> Step 3: Bob operations can be done in parallel using multiple threads executing following
snippet
> 	while ((currentIndex = fileIndex.getAndIncrement()) < files.length) {
> 		FileMetadata file = files[currentIndex];
> 		Rename/delete(file);
> 	}
> 	The above strategy depends on the fact that all files are stored in a final array and
each thread has to determine synchronized next index to do the job. The advantage of this
strategy is that even if user configures large number of unusable threads, we always ensure
that work doesn’t get serialized due to lagging threads. 
> 	We are logging following information which can be useful for tuning number of threads
> 	a) Number of unusable threads
> 	b) Time taken by each thread
> 	c) Number of files processed by each thread
> 	d) Total time taken for the operation
> 	Failure Scenarios:
> 	Failure to queue a thread execute request shouldn’t be an issue if we can ensure at
least one thread has completed execution successfully. If we couldn't schedule one thread
then we should take serialization path. Exceptions raised while executing threads are still
considered regular exceptions and returned to client as operation failed. Exceptions raised
while stopping threads and deleting thread pool shouldn't can be ignored if operation all
files are done with out any issue.



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