[jira] [Comment Edited] (HADOOP-18291) S3A prefetch - Implement LRU cache for SingleFilePerBlockCache

2023-07-14 Thread Quan Li (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18291?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743347#comment-17743347
 ] 

Quan Li edited comment on HADOOP-18291 at 7/15/23 5:57 AM:
---

the tests are failing in our internal, can't follow the code, tons of review 
comments, not sure if  reviewers wrote code via review this much comments.

[~mthakur] [~mehakmeet] [~ayushsaxena] [~hexiaoqiao] [~inigoiri] 

Can someone fix/revert this

 ticket -> let reviewer fix it via review -> still break -> addendum

very tough backporting such


was (Author: quanli):
the tests are failing in our internal, can't follow the code, tons of review 
comments, not sure if  reviewers wrote code via review this much comments.

[~mthakur] [~mehakmeet] [~ayushsaxena] [~hexiaoqiao] [~inigoiri] 

Can someone fix/revert this

> S3A prefetch - Implement LRU cache for SingleFilePerBlockCache
> --
>
> Key: HADOOP-18291
> URL: https://issues.apache.org/jira/browse/HADOOP-18291
> Project: Hadoop Common
>  Issue Type: Sub-task
>Affects Versions: 3.4.0
>Reporter: Ahmar Suhail
>Assignee: Viraj Jasani
>Priority: Major
>  Labels: pull-request-available
> Fix For: 3.3.9
>
>
> Currently there is no limit on the size of disk cache. This means we could 
> have a large number of files on files, especially for access patterns that 
> are very random and do not always read the block fully. 
>  
> eg:
> in.seek(5);
> in.read(); 
> in.seek(blockSize + 10) // block 0 gets saved to disk as it's not fully read
> in.read();
> in.seek(2 * blockSize + 10) // block 1 gets saved to disk
> .. and so on
>  
> The in memory cache is bounded, and by default has a limit of 72MB (9 
> blocks). When a block is fully read, and a seek is issued it's released 
> [here|https://github.com/apache/hadoop/blob/feature-HADOOP-18028-s3a-prefetch/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/read/S3CachingInputStream.java#L109].
>  We can also delete the on disk file for the block here if it exists. 
>  
> Also maybe add an upper limit on disk space, and delete the file which stores 
> data of the block furthest from the current block (similar to the in memory 
> cache) when this limit is reached. 



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[jira] [Commented] (HADOOP-18291) S3A prefetch - Implement LRU cache for SingleFilePerBlockCache

2023-07-14 Thread Quan Li (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18291?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743347#comment-17743347
 ] 

Quan Li commented on HADOOP-18291:
--

the tests are failing in our internal, can't follow the code, tons of review 
comments, not sure if  reviewers wrote code via review this much comments.

[~mthakur] [~mehakmeet] [~ayushsaxena] [~hexiaoqiao] [~inigoiri] 

Can someone fix/revert this

> S3A prefetch - Implement LRU cache for SingleFilePerBlockCache
> --
>
> Key: HADOOP-18291
> URL: https://issues.apache.org/jira/browse/HADOOP-18291
> Project: Hadoop Common
>  Issue Type: Sub-task
>Affects Versions: 3.4.0
>Reporter: Ahmar Suhail
>Assignee: Viraj Jasani
>Priority: Major
>  Labels: pull-request-available
> Fix For: 3.3.9
>
>
> Currently there is no limit on the size of disk cache. This means we could 
> have a large number of files on files, especially for access patterns that 
> are very random and do not always read the block fully. 
>  
> eg:
> in.seek(5);
> in.read(); 
> in.seek(blockSize + 10) // block 0 gets saved to disk as it's not fully read
> in.read();
> in.seek(2 * blockSize + 10) // block 1 gets saved to disk
> .. and so on
>  
> The in memory cache is bounded, and by default has a limit of 72MB (9 
> blocks). When a block is fully read, and a seek is issued it's released 
> [here|https://github.com/apache/hadoop/blob/feature-HADOOP-18028-s3a-prefetch/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/read/S3CachingInputStream.java#L109].
>  We can also delete the on disk file for the block here if it exists. 
>  
> Also maybe add an upper limit on disk space, and delete the file which stores 
> data of the block furthest from the current block (similar to the in memory 
> cache) when this limit is reached. 



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[jira] [Updated] (HADOOP-18806) Document missing property (ipc.server.read.threadpool.size) in core-default.xml

2023-07-14 Thread ASF GitHub Bot (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18806?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

ASF GitHub Bot updated HADOOP-18806:

Labels: pull-request-available  (was: )

> Document missing property (ipc.server.read.threadpool.size) in 
> core-default.xml
> ---
>
> Key: HADOOP-18806
> URL: https://issues.apache.org/jira/browse/HADOOP-18806
> Project: Hadoop Common
>  Issue Type: Improvement
>Reporter: YUBI LEE
>Priority: Minor
>  Labels: pull-request-available
>




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[jira] [Commented] (HADOOP-18806) Document missing property (ipc.server.read.threadpool.size) in core-default.xml

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18806?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743346#comment-17743346
 ] 

ASF GitHub Bot commented on HADOOP-18806:
-

eubnara opened a new pull request, #5844:
URL: https://github.com/apache/hadoop/pull/5844

   
   
   
   ### Description of PR
   
   I think `ipc.server.read.threadpool.size` is quite important configuration 
tuning point. But there is no mention about it in core-default.xml.
   There are some articles about hadoop tuning configuration with it. (e.g. 
https://support.huawei.com/enterprise/en/knowledge/EKB1100015760)
   
   
   
   ### How was this patch tested?
   
   It is just changed documentation.
   
   ### For code changes:
   
   - [x] Does the title or this PR starts with the corresponding JIRA issue id 
(e.g. 'HADOOP-17799. Your PR title ...')?
   
   




> Document missing property (ipc.server.read.threadpool.size) in 
> core-default.xml
> ---
>
> Key: HADOOP-18806
> URL: https://issues.apache.org/jira/browse/HADOOP-18806
> Project: Hadoop Common
>  Issue Type: Improvement
>Reporter: YUBI LEE
>Priority: Minor
>




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[GitHub] [hadoop] eubnara opened a new pull request, #5844: HADOOP-18806. Document missing property (ipc.server.read.threadpool.size) in core-default.xml

2023-07-14 Thread via GitHub


eubnara opened a new pull request, #5844:
URL: https://github.com/apache/hadoop/pull/5844

   
   
   
   ### Description of PR
   
   I think `ipc.server.read.threadpool.size` is quite important configuration 
tuning point. But there is no mention about it in core-default.xml.
   There are some articles about hadoop tuning configuration with it. (e.g. 
https://support.huawei.com/enterprise/en/knowledge/EKB1100015760)
   
   
   
   ### How was this patch tested?
   
   It is just changed documentation.
   
   ### For code changes:
   
   - [x] Does the title or this PR starts with the corresponding JIRA issue id 
(e.g. 'HADOOP-17799. Your PR title ...')?
   
   


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[jira] [Updated] (HADOOP-18806) Document missing property (ipc.server.read.threadpool.size) in core-default.xml

2023-07-14 Thread YUBI LEE (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18806?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

YUBI LEE updated HADOOP-18806:
--
Summary: Document missing property (ipc.server.read.threadpool.size) in 
core-default.xml  (was: Document missing property 
(ipc.server.read.threadpool.size) in core-site.xml)

> Document missing property (ipc.server.read.threadpool.size) in 
> core-default.xml
> ---
>
> Key: HADOOP-18806
> URL: https://issues.apache.org/jira/browse/HADOOP-18806
> Project: Hadoop Common
>  Issue Type: Improvement
>Reporter: YUBI LEE
>Priority: Minor
>




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[jira] [Created] (HADOOP-18806) Document missing property (ipc.server.read.threadpool.size) in core-site.xml

2023-07-14 Thread YUBI LEE (Jira)
YUBI LEE created HADOOP-18806:
-

 Summary: Document missing property 
(ipc.server.read.threadpool.size) in core-site.xml
 Key: HADOOP-18806
 URL: https://issues.apache.org/jira/browse/HADOOP-18806
 Project: Hadoop Common
  Issue Type: Improvement
Reporter: YUBI LEE






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[jira] [Commented] (HADOOP-18805) s3a large file prefetch tests are too slow, don't validate data

2023-07-14 Thread Viraj Jasani (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18805?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743344#comment-17743344
 ] 

Viraj Jasani commented on HADOOP-18805:
---

sorry Steve, i was not aware you already created this Jira, i created addendum 
for letting LRU test depend on small file rather than large one: 
[https://github.com/apache/hadoop/pull/5843]
{quote}also, and this is very, very important, they can't validate the data
{quote}
i was about to create a sub-task for this as i am planning to refactor Entry to 
it's own class and have the contents of the linked list data tested in UT 
(discussed with Mehakmeet in the earlier part of the review). maybe i can do 
the work as part of this Jira.

 

are you fine with the above addendum PR taking care of using small file in the 
test (so that we don't need to put the test under -scale) and this Jira being 
used for refactoring Entry and allowing a UT to test the contents of the linked 
list?

> s3a large file prefetch tests are too slow, don't validate data
> ---
>
> Key: HADOOP-18805
> URL: https://issues.apache.org/jira/browse/HADOOP-18805
> Project: Hadoop Common
>  Issue Type: Sub-task
>  Components: fs/s3, test
>Affects Versions: 3.3.9
>Reporter: Steve Loughran
>Priority: Major
>
> the large file prefetch tests (including LRU cache eviction) are really slow.
> moving under -scale may hide the problem for most runs, but they are still 
> too slow, can time out, etc etc.
> also, and this is very, very important, they can't validate the data.
> Better: 
> * test on smaller files by setting a very small block size (1k bytes or less) 
> just to force paged reads of a small 16k file.
> * with known contents to the values of all forms of read can be validated
> * maybe the LRU tests can work with a fake remote object which can then be 
> used in a unit test
> * extend one of the huge file tests to read from there -including s3-CSE 
> encryption coverage.



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[jira] [Assigned] (HADOOP-18805) s3a large file prefetch tests are too slow, don't validate data

2023-07-14 Thread Viraj Jasani (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18805?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Viraj Jasani reassigned HADOOP-18805:
-

Assignee: (was: Viraj Jasani)

> s3a large file prefetch tests are too slow, don't validate data
> ---
>
> Key: HADOOP-18805
> URL: https://issues.apache.org/jira/browse/HADOOP-18805
> Project: Hadoop Common
>  Issue Type: Sub-task
>  Components: fs/s3, test
>Affects Versions: 3.3.9
>Reporter: Steve Loughran
>Priority: Major
>
> the large file prefetch tests (including LRU cache eviction) are really slow.
> moving under -scale may hide the problem for most runs, but they are still 
> too slow, can time out, etc etc.
> also, and this is very, very important, they can't validate the data.
> Better: 
> * test on smaller files by setting a very small block size (1k bytes or less) 
> just to force paged reads of a small 16k file.
> * with known contents to the values of all forms of read can be validated
> * maybe the LRU tests can work with a fake remote object which can then be 
> used in a unit test
> * extend one of the huge file tests to read from there -including s3-CSE 
> encryption coverage.



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[jira] [Assigned] (HADOOP-18805) s3a large file prefetch tests are too slow, don't validate data

2023-07-14 Thread Viraj Jasani (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18805?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Viraj Jasani reassigned HADOOP-18805:
-

Assignee: Viraj Jasani

> s3a large file prefetch tests are too slow, don't validate data
> ---
>
> Key: HADOOP-18805
> URL: https://issues.apache.org/jira/browse/HADOOP-18805
> Project: Hadoop Common
>  Issue Type: Sub-task
>  Components: fs/s3, test
>Affects Versions: 3.3.9
>Reporter: Steve Loughran
>Assignee: Viraj Jasani
>Priority: Major
>
> the large file prefetch tests (including LRU cache eviction) are really slow.
> moving under -scale may hide the problem for most runs, but they are still 
> too slow, can time out, etc etc.
> also, and this is very, very important, they can't validate the data.
> Better: 
> * test on smaller files by setting a very small block size (1k bytes or less) 
> just to force paged reads of a small 16k file.
> * with known contents to the values of all forms of read can be validated
> * maybe the LRU tests can work with a fake remote object which can then be 
> used in a unit test
> * extend one of the huge file tests to read from there -including s3-CSE 
> encryption coverage.



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[jira] [Commented] (HADOOP-18291) S3A prefetch - Implement LRU cache for SingleFilePerBlockCache

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18291?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743334#comment-17743334
 ] 

ASF GitHub Bot commented on HADOOP-18291:
-

virajjasani commented on PR #5843:
URL: https://github.com/apache/hadoop/pull/5843#issuecomment-1636603969

   not sure, what is going wrong with jenkins env
   
   https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5843/1/console
   
   ```
   Error when executing cleanup post condition:
   org.jenkinsci.plugins.workflow.steps.MissingContextVariableException: 
Required context class hudson.FilePath is missing
   Perhaps you forgot to surround the code with a step that provides this, such 
as: node
at 
org.jenkinsci.plugins.workflow.steps.StepDescriptor.checkContextAvailability(StepDescriptor.java:265)
at org.jenkinsci.plugins.workflow.cps.DSL.invokeStep(DSL.java:299)
at org.jenkinsci.plugins.workflow.cps.DSL.invokeMethod(DSL.java:196)
at 
org.jenkinsci.plugins.workflow.cps.CpsScript.invokeMethod(CpsScript.java:124)
   ```
   
   ```
   Also:   hudson.remoting.Channel$CallSiteStackTrace: Remote call to hadoop2
at 
hudson.remoting.Channel.attachCallSiteStackTrace(Channel.java:1784)
at 
hudson.remoting.UserRequest$ExceptionResponse.retrieve(UserRequest.java:356)
at hudson.remoting.Channel.call(Channel.java:1000)
at hudson.FilePath.act(FilePath.java:1194)
at hudson.FilePath.act(FilePath.java:1183)
at hudson.FilePath.mkdirs(FilePath.java:1374)
at hudson.plugins.git.GitSCM.createClient(GitSCM.java:844)
at hudson.plugins.git.GitSCM.checkout(GitSCM.java:1296)
at 
org.jenkinsci.plugins.workflow.steps.scm.SCMStep.checkout(SCMStep.java:129)
at 
org.jenkinsci.plugins.workflow.steps.scm.SCMStep$StepExecutionImpl.run(SCMStep.java:97)
at 
org.jenkinsci.plugins.workflow.steps.scm.SCMStep$StepExecutionImpl.run(SCMStep.java:84)
   java.nio.file.FileSystemException: 
/home/jenkins/jenkins-home/workspace/hadoop-multibranch: Read-only file system
at 
java.base/sun.nio.fs.UnixException.translateToIOException(UnixException.java:100)
at 
java.base/sun.nio.fs.UnixException.rethrowAsIOException(UnixException.java:111)
at 
java.base/sun.nio.fs.UnixException.rethrowAsIOException(UnixException.java:116)
at 
java.base/sun.nio.fs.UnixFileSystemProvider.createDirectory(UnixFileSystemProvider.java:389)
at java.base/java.nio.file.Files.createDirectory(Files.java:690)
at 
java.base/java.nio.file.Files.createAndCheckIsDirectory(Files.java:797)
   ```




> S3A prefetch - Implement LRU cache for SingleFilePerBlockCache
> --
>
> Key: HADOOP-18291
> URL: https://issues.apache.org/jira/browse/HADOOP-18291
> Project: Hadoop Common
>  Issue Type: Sub-task
>Affects Versions: 3.4.0
>Reporter: Ahmar Suhail
>Assignee: Viraj Jasani
>Priority: Major
>  Labels: pull-request-available
> Fix For: 3.3.9
>
>
> Currently there is no limit on the size of disk cache. This means we could 
> have a large number of files on files, especially for access patterns that 
> are very random and do not always read the block fully. 
>  
> eg:
> in.seek(5);
> in.read(); 
> in.seek(blockSize + 10) // block 0 gets saved to disk as it's not fully read
> in.read();
> in.seek(2 * blockSize + 10) // block 1 gets saved to disk
> .. and so on
>  
> The in memory cache is bounded, and by default has a limit of 72MB (9 
> blocks). When a block is fully read, and a seek is issued it's released 
> [here|https://github.com/apache/hadoop/blob/feature-HADOOP-18028-s3a-prefetch/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/read/S3CachingInputStream.java#L109].
>  We can also delete the on disk file for the block here if it exists. 
>  
> Also maybe add an upper limit on disk space, and delete the file which stores 
> data of the block furthest from the current block (similar to the in memory 
> cache) when this limit is reached. 



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[GitHub] [hadoop] virajjasani commented on pull request #5843: HADOOP-18291. (ADDENDUM) S3A prefetch LRU test to work with small file

2023-07-14 Thread via GitHub


virajjasani commented on PR #5843:
URL: https://github.com/apache/hadoop/pull/5843#issuecomment-1636603969

   not sure, what is going wrong with jenkins env
   
   https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5843/1/console
   
   ```
   Error when executing cleanup post condition:
   org.jenkinsci.plugins.workflow.steps.MissingContextVariableException: 
Required context class hudson.FilePath is missing
   Perhaps you forgot to surround the code with a step that provides this, such 
as: node
at 
org.jenkinsci.plugins.workflow.steps.StepDescriptor.checkContextAvailability(StepDescriptor.java:265)
at org.jenkinsci.plugins.workflow.cps.DSL.invokeStep(DSL.java:299)
at org.jenkinsci.plugins.workflow.cps.DSL.invokeMethod(DSL.java:196)
at 
org.jenkinsci.plugins.workflow.cps.CpsScript.invokeMethod(CpsScript.java:124)
   ```
   
   ```
   Also:   hudson.remoting.Channel$CallSiteStackTrace: Remote call to hadoop2
at 
hudson.remoting.Channel.attachCallSiteStackTrace(Channel.java:1784)
at 
hudson.remoting.UserRequest$ExceptionResponse.retrieve(UserRequest.java:356)
at hudson.remoting.Channel.call(Channel.java:1000)
at hudson.FilePath.act(FilePath.java:1194)
at hudson.FilePath.act(FilePath.java:1183)
at hudson.FilePath.mkdirs(FilePath.java:1374)
at hudson.plugins.git.GitSCM.createClient(GitSCM.java:844)
at hudson.plugins.git.GitSCM.checkout(GitSCM.java:1296)
at 
org.jenkinsci.plugins.workflow.steps.scm.SCMStep.checkout(SCMStep.java:129)
at 
org.jenkinsci.plugins.workflow.steps.scm.SCMStep$StepExecutionImpl.run(SCMStep.java:97)
at 
org.jenkinsci.plugins.workflow.steps.scm.SCMStep$StepExecutionImpl.run(SCMStep.java:84)
   java.nio.file.FileSystemException: 
/home/jenkins/jenkins-home/workspace/hadoop-multibranch: Read-only file system
at 
java.base/sun.nio.fs.UnixException.translateToIOException(UnixException.java:100)
at 
java.base/sun.nio.fs.UnixException.rethrowAsIOException(UnixException.java:111)
at 
java.base/sun.nio.fs.UnixException.rethrowAsIOException(UnixException.java:116)
at 
java.base/sun.nio.fs.UnixFileSystemProvider.createDirectory(UnixFileSystemProvider.java:389)
at java.base/java.nio.file.Files.createDirectory(Files.java:690)
at 
java.base/java.nio.file.Files.createAndCheckIsDirectory(Files.java:797)
   ```


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[jira] [Commented] (HADOOP-18184) s3a prefetching stream to support unbuffer()

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18184?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=1774#comment-1774
 ] 

ASF GitHub Bot commented on HADOOP-18184:
-

virajjasani commented on PR #5832:
URL: https://github.com/apache/hadoop/pull/5832#issuecomment-1636601526

   > the solution here shouldn't be "add a bigger timeout" it should be "make 
these tests faster by working with smaller files and smaller blocks"
   
   PR #5843




> s3a prefetching stream to support unbuffer()
> 
>
> Key: HADOOP-18184
> URL: https://issues.apache.org/jira/browse/HADOOP-18184
> Project: Hadoop Common
>  Issue Type: Sub-task
>  Components: fs/s3
>Affects Versions: 3.4.0
>Reporter: Steve Loughran
>Assignee: Steve Loughran
>Priority: Minor
>  Labels: pull-request-available
>
> Apache Impala uses unbuffer() to free up all client side resources held by a 
> stream, so allowing it to have a map of available (path -> stream) objects, 
> retained across queries.
> This saves on having to reopen the files, with the cost of HEAD checks etc. 
> S3AInputStream just closes its http connection. here there is a lot more 
> state to discard, but all memory and file storage must be freed.
> until this done, ITestS3AContractUnbuffer must skip when the prefetch stream 
> is used.
> its notable that the other tests don't fail, even though the stream doesn't 
> implement the interface; the graceful degradation handles that. it should 
> fail if the test xml resource says the stream does it, but that the stream 
> capabilities say it doesn't.



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[GitHub] [hadoop] virajjasani commented on pull request #5832: HADOOP-18184. S3A Prefetching unbuffer.

2023-07-14 Thread via GitHub


virajjasani commented on PR #5832:
URL: https://github.com/apache/hadoop/pull/5832#issuecomment-1636601526

   > the solution here shouldn't be "add a bigger timeout" it should be "make 
these tests faster by working with smaller files and smaller blocks"
   
   PR #5843


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[jira] [Commented] (HADOOP-18291) S3A prefetch - Implement LRU cache for SingleFilePerBlockCache

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18291?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743332#comment-17743332
 ] 

ASF GitHub Bot commented on HADOOP-18291:
-

virajjasani commented on PR #5754:
URL: https://github.com/apache/hadoop/pull/5754#issuecomment-1636598987

   created addendum PR for dealing with small file #5843




> S3A prefetch - Implement LRU cache for SingleFilePerBlockCache
> --
>
> Key: HADOOP-18291
> URL: https://issues.apache.org/jira/browse/HADOOP-18291
> Project: Hadoop Common
>  Issue Type: Sub-task
>Affects Versions: 3.4.0
>Reporter: Ahmar Suhail
>Assignee: Viraj Jasani
>Priority: Major
>  Labels: pull-request-available
> Fix For: 3.3.9
>
>
> Currently there is no limit on the size of disk cache. This means we could 
> have a large number of files on files, especially for access patterns that 
> are very random and do not always read the block fully. 
>  
> eg:
> in.seek(5);
> in.read(); 
> in.seek(blockSize + 10) // block 0 gets saved to disk as it's not fully read
> in.read();
> in.seek(2 * blockSize + 10) // block 1 gets saved to disk
> .. and so on
>  
> The in memory cache is bounded, and by default has a limit of 72MB (9 
> blocks). When a block is fully read, and a seek is issued it's released 
> [here|https://github.com/apache/hadoop/blob/feature-HADOOP-18028-s3a-prefetch/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/read/S3CachingInputStream.java#L109].
>  We can also delete the on disk file for the block here if it exists. 
>  
> Also maybe add an upper limit on disk space, and delete the file which stores 
> data of the block furthest from the current block (similar to the in memory 
> cache) when this limit is reached. 



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[GitHub] [hadoop] virajjasani commented on pull request #5754: HADOOP-18291. S3A prefetch - Implement thread-safe LRU cache for SingleFilePerBlockCache

2023-07-14 Thread via GitHub


virajjasani commented on PR #5754:
URL: https://github.com/apache/hadoop/pull/5754#issuecomment-1636598987

   created addendum PR for dealing with small file #5843


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[jira] [Commented] (HADOOP-18291) S3A prefetch - Implement LRU cache for SingleFilePerBlockCache

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18291?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743331#comment-17743331
 ] 

ASF GitHub Bot commented on HADOOP-18291:
-

virajjasani opened a new pull request, #5843:
URL: https://github.com/apache/hadoop/pull/5843

   (no comment)




> S3A prefetch - Implement LRU cache for SingleFilePerBlockCache
> --
>
> Key: HADOOP-18291
> URL: https://issues.apache.org/jira/browse/HADOOP-18291
> Project: Hadoop Common
>  Issue Type: Sub-task
>Affects Versions: 3.4.0
>Reporter: Ahmar Suhail
>Assignee: Viraj Jasani
>Priority: Major
>  Labels: pull-request-available
> Fix For: 3.3.9
>
>
> Currently there is no limit on the size of disk cache. This means we could 
> have a large number of files on files, especially for access patterns that 
> are very random and do not always read the block fully. 
>  
> eg:
> in.seek(5);
> in.read(); 
> in.seek(blockSize + 10) // block 0 gets saved to disk as it's not fully read
> in.read();
> in.seek(2 * blockSize + 10) // block 1 gets saved to disk
> .. and so on
>  
> The in memory cache is bounded, and by default has a limit of 72MB (9 
> blocks). When a block is fully read, and a seek is issued it's released 
> [here|https://github.com/apache/hadoop/blob/feature-HADOOP-18028-s3a-prefetch/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/read/S3CachingInputStream.java#L109].
>  We can also delete the on disk file for the block here if it exists. 
>  
> Also maybe add an upper limit on disk space, and delete the file which stores 
> data of the block furthest from the current block (similar to the in memory 
> cache) when this limit is reached. 



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[GitHub] [hadoop] virajjasani opened a new pull request, #5843: HADOOP-18291. (ADDENDUM) S3A prefetch LRU test to work with small file

2023-07-14 Thread via GitHub


virajjasani opened a new pull request, #5843:
URL: https://github.com/apache/hadoop/pull/5843

   (no comment)


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[jira] [Commented] (HADOOP-18184) s3a prefetching stream to support unbuffer()

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18184?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743280#comment-17743280
 ] 

ASF GitHub Bot commented on HADOOP-18184:
-

hadoop-yetus commented on PR #5832:
URL: https://github.com/apache/hadoop/pull/5832#issuecomment-1636399060

   :broken_heart: **-1 overall**
   
   
   
   
   
   
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Binary files and potentially other changes not applied. Please rebase and 
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[/results-javadoc-javadoc-hadoop-tools_hadoop-aws-jdkPrivateBuild-1.8.0_362-8u372-ga~us1-0ubuntu1~20.04-b09.txt](https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5832/4/artifact/out/results-javadoc-javadoc-hadoop-tools_hadoop-aws-jdkPrivateBuild-1.8.0_362-8u372-ga~us1-0ubuntu1~20.04-b09.txt)
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[/patch-unit-hadoop-tools_hadoop-aws.txt](https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5832/4/artifact/out/patch-unit-hadoop-tools_hadoop-aws.txt)
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   |  |   | 260m 39s |  |  |
   
   
   | Reason | Tests |
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   | Failed junit tests | hadoop.fs.s3a.prefetch.TestS3ARemoteInputStream |
   |   | hadoop.fs.s3a.prefetch.TestS3ACachingBlockManager |
   
   
   | Subsystem | Report/Notes |
   |--:|:-|
   | Docker | ClientAPI=1.43 ServerAPI=1.43 base: 

[GitHub] [hadoop] hadoop-yetus commented on pull request #5832: HADOOP-18184. S3A Prefetching unbuffer.

2023-07-14 Thread via GitHub


hadoop-yetus commented on PR #5832:
URL: https://github.com/apache/hadoop/pull/5832#issuecomment-1636399060

   :broken_heart: **-1 overall**
   
   
   
   
   
   
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Binary files and potentially other changes not applied. Please rebase and 
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[/results-javadoc-javadoc-hadoop-tools_hadoop-aws-jdkPrivateBuild-1.8.0_362-8u372-ga~us1-0ubuntu1~20.04-b09.txt](https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5832/4/artifact/out/results-javadoc-javadoc-hadoop-tools_hadoop-aws-jdkPrivateBuild-1.8.0_362-8u372-ga~us1-0ubuntu1~20.04-b09.txt)
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   |  |   | 260m 39s |  |  |
   
   
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   |---:|:--|
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   |--:|:-|
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   | Optional Tests | dupname asflicense compile javac javadoc mvninstall 
mvnsite unit 

[jira] [Commented] (HADOOP-18795) s3a DelegationToken plugin to expand return type of deploy/binding

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18795?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743279#comment-17743279
 ] 

ASF GitHub Bot commented on HADOOP-18795:
-

hadoop-yetus commented on PR #5821:
URL: https://github.com/apache/hadoop/pull/5821#issuecomment-1636368868

   :broken_heart: **-1 overall**
   
   
   
   
   
   
   | Vote | Subsystem | Runtime |  Logfile | Comment |
   |::|--:|:|::|:---:|
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|
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[GitHub] [hadoop] hadoop-yetus commented on pull request #5821: HADOOP-18795. S3A DelegationToken plugin to expand return type of binding

2023-07-14 Thread via GitHub


hadoop-yetus commented on PR #5821:
URL: https://github.com/apache/hadoop/pull/5821#issuecomment-1636368868

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[jira] [Commented] (HADOOP-18801) Delete path directly when it can not be parsed in trash

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18801?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743271#comment-17743271
 ] 

ASF GitHub Bot commented on HADOOP-18801:
-

hadoop-yetus commented on PR #5744:
URL: https://github.com/apache/hadoop/pull/5744#issuecomment-1636344146

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[GitHub] [hadoop] hadoop-yetus commented on pull request #5744: HADOOP-18801. Delete path directly when it can not be parsed in trash.

2023-07-14 Thread via GitHub


hadoop-yetus commented on PR #5744:
URL: https://github.com/apache/hadoop/pull/5744#issuecomment-1636344146

   :confetti_ball: **+1 overall**
   
   
   
   
   
   
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[GitHub] [hadoop] hadoop-yetus commented on pull request #5842: HDFS-17086. Fix the parameter settings in TestDiskspaceQuotaUpdate#updateCountForQuota

2023-07-14 Thread via GitHub


hadoop-yetus commented on PR #5842:
URL: https://github.com/apache/hadoop/pull/5842#issuecomment-1636259839

   :broken_heart: **-1 overall**
   
   
   
   
   
   
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[jira] [Created] (HADOOP-18805) s3a large file prefetch tests are too slow, don't validate data

2023-07-14 Thread Steve Loughran (Jira)
Steve Loughran created HADOOP-18805:
---

 Summary: s3a large file prefetch tests are too slow, don't 
validate data
 Key: HADOOP-18805
 URL: https://issues.apache.org/jira/browse/HADOOP-18805
 Project: Hadoop Common
  Issue Type: Sub-task
  Components: fs/s3, test
Affects Versions: 3.3.9
Reporter: Steve Loughran


the large file prefetch tests (including LRU cache eviction) are really slow.

moving under -scale may hide the problem for most runs, but they are still too 
slow, can time out, etc etc.


also, and this is very, very important, they can't validate the data.

Better: 
* test on smaller files by setting a very small block size (1k bytes or less) 
just to force paged reads of a small 16k file.
* with known contents to the values of all forms of read can be validated
* maybe the LRU tests can work with a fake remote object which can then be used 
in a unit test
* extend one of the huge file tests to read from there -including s3-CSE 
encryption coverage.





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[jira] [Updated] (HADOOP-18291) S3A prefetch - Implement LRU cache for SingleFilePerBlockCache

2023-07-14 Thread Steve Loughran (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18291?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Steve Loughran updated HADOOP-18291:

Fix Version/s: 3.3.9
   Resolution: Fixed
   Status: Resolved  (was: Patch Available)

> S3A prefetch - Implement LRU cache for SingleFilePerBlockCache
> --
>
> Key: HADOOP-18291
> URL: https://issues.apache.org/jira/browse/HADOOP-18291
> Project: Hadoop Common
>  Issue Type: Sub-task
>Affects Versions: 3.4.0
>Reporter: Ahmar Suhail
>Assignee: Viraj Jasani
>Priority: Major
>  Labels: pull-request-available
> Fix For: 3.3.9
>
>
> Currently there is no limit on the size of disk cache. This means we could 
> have a large number of files on files, especially for access patterns that 
> are very random and do not always read the block fully. 
>  
> eg:
> in.seek(5);
> in.read(); 
> in.seek(blockSize + 10) // block 0 gets saved to disk as it's not fully read
> in.read();
> in.seek(2 * blockSize + 10) // block 1 gets saved to disk
> .. and so on
>  
> The in memory cache is bounded, and by default has a limit of 72MB (9 
> blocks). When a block is fully read, and a seek is issued it's released 
> [here|https://github.com/apache/hadoop/blob/feature-HADOOP-18028-s3a-prefetch/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/read/S3CachingInputStream.java#L109].
>  We can also delete the on disk file for the block here if it exists. 
>  
> Also maybe add an upper limit on disk space, and delete the file which stores 
> data of the block furthest from the current block (similar to the in memory 
> cache) when this limit is reached. 



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[GitHub] [hadoop] hadoop-yetus commented on pull request #5823: HDFS-17075. Reconfig disk balancer parameters for datanode

2023-07-14 Thread via GitHub


hadoop-yetus commented on PR #5823:
URL: https://github.com/apache/hadoop/pull/5823#issuecomment-1636170310

   :confetti_ball: **+1 overall**
   
   
   
   
   
   
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[jira] [Commented] (HADOOP-18291) S3A prefetch - Implement LRU cache for SingleFilePerBlockCache

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18291?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743235#comment-17743235
 ] 

ASF GitHub Bot commented on HADOOP-18291:
-

virajjasani commented on PR #5754:
URL: https://github.com/apache/hadoop/pull/5754#issuecomment-1636141106

   i see, i was thinking, perhaps small file with prefetch of multiple blocks 
might be too small for the test?
   
   but on the other hand, i agree that we don't need such long running test 
either, let me at least remove "3" and "4" from block size array and have the 
test time duration reduce by half for now in an addendum?




> S3A prefetch - Implement LRU cache for SingleFilePerBlockCache
> --
>
> Key: HADOOP-18291
> URL: https://issues.apache.org/jira/browse/HADOOP-18291
> Project: Hadoop Common
>  Issue Type: Sub-task
>Affects Versions: 3.4.0
>Reporter: Ahmar Suhail
>Assignee: Viraj Jasani
>Priority: Major
>  Labels: pull-request-available
>
> Currently there is no limit on the size of disk cache. This means we could 
> have a large number of files on files, especially for access patterns that 
> are very random and do not always read the block fully. 
>  
> eg:
> in.seek(5);
> in.read(); 
> in.seek(blockSize + 10) // block 0 gets saved to disk as it's not fully read
> in.read();
> in.seek(2 * blockSize + 10) // block 1 gets saved to disk
> .. and so on
>  
> The in memory cache is bounded, and by default has a limit of 72MB (9 
> blocks). When a block is fully read, and a seek is issued it's released 
> [here|https://github.com/apache/hadoop/blob/feature-HADOOP-18028-s3a-prefetch/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/read/S3CachingInputStream.java#L109].
>  We can also delete the on disk file for the block here if it exists. 
>  
> Also maybe add an upper limit on disk space, and delete the file which stores 
> data of the block furthest from the current block (similar to the in memory 
> cache) when this limit is reached. 



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[GitHub] [hadoop] virajjasani commented on pull request #5754: HADOOP-18291. S3A prefetch - Implement thread-safe LRU cache for SingleFilePerBlockCache

2023-07-14 Thread via GitHub


virajjasani commented on PR #5754:
URL: https://github.com/apache/hadoop/pull/5754#issuecomment-1636141106

   i see, i was thinking, perhaps small file with prefetch of multiple blocks 
might be too small for the test?
   
   but on the other hand, i agree that we don't need such long running test 
either, let me at least remove "3" and "4" from block size array and have the 
test time duration reduce by half for now in an addendum?


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[jira] [Commented] (HADOOP-18384) ITestS3AFileSystemStatistic failure in prefetch feature branch

2023-07-14 Thread Steve Loughran (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18384?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743232#comment-17743232
 ] 

Steve Loughran commented on HADOOP-18384:
-

not seen for a while

> ITestS3AFileSystemStatistic failure in prefetch feature branch
> --
>
> Key: HADOOP-18384
> URL: https://issues.apache.org/jira/browse/HADOOP-18384
> Project: Hadoop Common
>  Issue Type: Sub-task
>  Components: fs/s3, test
>Affects Versions: 3.4.0
>Reporter: Steve Loughran
>Assignee: Samrat Deb
>Priority: Minor
>
> testing the rebased prefetch feature branch; got a failure in 
> ITestS3AFileSystemStatistic
>  
> {code}
> tics.ITestS3AFileSystemStatistic
> [ERROR] Tests run: 1, Failures: 1, Errors: 0, Skipped: 0, Time elapsed: 1.489 
> s <<< FAILURE! - in 
> org.apache.hadoop.fs.s3a.statistics.ITestS3AFileSystemStatistic
> [ERROR] 
> testBytesReadWithStream(org.apache.hadoop.fs.s3a.statistics.ITestS3AFileSystemStatistic)
>   Time elapsed: 1.489 s  <<< FAILURE!
> java.lang.AssertionError: Mismatch in number of FS bytes read by InputStreams 
> expected:<2048> but was:<69537130>
> at 
> org.apache.hadoop.fs.s3a.statistics.ITestS3AFileSystemStatistic.testBytesReadWithStream(ITestS3AFileSystemStatistic.java:72)
> {code}
> that;s 64MB + ~237 kb, the kind of values you would get from prefetching
> but, prefetch was disabled in this test run.
> maybe its just the fs stats aren't being reset between test cases



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[jira] [Commented] (HADOOP-18184) s3a prefetching stream to support unbuffer()

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18184?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743230#comment-17743230
 ] 

ASF GitHub Bot commented on HADOOP-18184:
-

steveloughran commented on PR #5832:
URL: https://github.com/apache/hadoop/pull/5832#issuecomment-1636115561

   tested, s3 london, with `-Dparallel-tests -DtestsThreadCount=8 -Dprefetch 
-Dscale` and no VPN in the way. This is getting back to as slow as it used to 
be -and so needs work. 
   
   All the landasat tests are going to be long-haul for most people; the 
existing hugefile tests should be extended to do the reading on their files 
which are (a) on the chosen aws region and (b) let you control the filesize
   
   ```
   [INFO] 
   [INFO] 

   [INFO] BUILD SUCCESS
   [INFO] 

   [INFO] Total time:  29:27 min (Wall Clock)
   [INFO] Finished at: 2023-07-14T17:34:02+01:00
   [INFO] 

   [WARNING] 
   
   
   ```
   




> s3a prefetching stream to support unbuffer()
> 
>
> Key: HADOOP-18184
> URL: https://issues.apache.org/jira/browse/HADOOP-18184
> Project: Hadoop Common
>  Issue Type: Sub-task
>  Components: fs/s3
>Affects Versions: 3.4.0
>Reporter: Steve Loughran
>Assignee: Steve Loughran
>Priority: Minor
>  Labels: pull-request-available
>
> Apache Impala uses unbuffer() to free up all client side resources held by a 
> stream, so allowing it to have a map of available (path -> stream) objects, 
> retained across queries.
> This saves on having to reopen the files, with the cost of HEAD checks etc. 
> S3AInputStream just closes its http connection. here there is a lot more 
> state to discard, but all memory and file storage must be freed.
> until this done, ITestS3AContractUnbuffer must skip when the prefetch stream 
> is used.
> its notable that the other tests don't fail, even though the stream doesn't 
> implement the interface; the graceful degradation handles that. it should 
> fail if the test xml resource says the stream does it, but that the stream 
> capabilities say it doesn't.



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[GitHub] [hadoop] steveloughran commented on pull request #5832: HADOOP-18184. S3A Prefetching unbuffer.

2023-07-14 Thread via GitHub


steveloughran commented on PR #5832:
URL: https://github.com/apache/hadoop/pull/5832#issuecomment-1636115561

   tested, s3 london, with `-Dparallel-tests -DtestsThreadCount=8 -Dprefetch 
-Dscale` and no VPN in the way. This is getting back to as slow as it used to 
be -and so needs work. 
   
   All the landasat tests are going to be long-haul for most people; the 
existing hugefile tests should be extended to do the reading on their files 
which are (a) on the chosen aws region and (b) let you control the filesize
   
   ```
   [INFO] 
   [INFO] 

   [INFO] BUILD SUCCESS
   [INFO] 

   [INFO] Total time:  29:27 min (Wall Clock)
   [INFO] Finished at: 2023-07-14T17:34:02+01:00
   [INFO] 

   [WARNING] 
   
   
   ```
   


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[jira] [Commented] (HADOOP-18184) s3a prefetching stream to support unbuffer()

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18184?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743228#comment-17743228
 ] 

ASF GitHub Bot commented on HADOOP-18184:
-

steveloughran commented on PR #5832:
URL: https://github.com/apache/hadoop/pull/5832#issuecomment-1636111884

   timeout in lru tests
   ```
   [ERROR] Tests run: 4, Failures: 0, Errors: 1, Skipped: 0, Time elapsed: 
843.577 s <<< FAILURE! - in 
org.apache.hadoop.fs.s3a.ITestS3APrefetchingLruEviction
   [ERROR] 
testSeeksWithLruEviction[max-blocks-1](org.apache.hadoop.fs.s3a.ITestS3APrefetchingLruEviction)
  Time elapsed: 600.017 s  <<< ERROR!
   org.junit.runners.model.TestTimedOutException: test timed out after 60 
milliseconds
   at sun.misc.Unsafe.park(Native Method)
   at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
   at 
java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:837)
   at 
java.util.concurrent.locks.AbstractQueuedSynchronizer.doAcquireSharedInterruptibly(AbstractQueuedSynchronizer.java:999)
   at 
java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireSharedInterruptibly(AbstractQueuedSynchronizer.java:1308)
   at java.util.concurrent.CountDownLatch.await(CountDownLatch.java:231)
   at 
org.apache.hadoop.fs.s3a.ITestS3APrefetchingLruEviction.testSeeksWithLruEviction(ITestS3APrefetchingLruEviction.java:176)
   at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
   at 
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
   at 
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
   at java.lang.reflect.Method.invoke(Method.java:498)
   at 
org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:59)
   at 
org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
   at 
org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:56)
   at 
org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
   at 
org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:26)
   at 
org.junit.internal.runners.statements.RunAfters.evaluate(RunAfters.java:27)
   at org.junit.rules.TestWatcher$1.evaluate(TestWatcher.java:61)
   at 
org.junit.internal.runners.statements.FailOnTimeout$CallableStatement.call(FailOnTimeout.java:299)
   at 
org.junit.internal.runners.statements.FailOnTimeout$CallableStatement.call(FailOnTimeout.java:293)
   at java.util.concurrent.FutureTask.run(FutureTask.java:266)
   at java.lang.Thread.run(Thread.java:750)
   
   ```
   issue here is having all the different bulk reads in the same test case; if 
it takes too long (> 10 minutes!) then it fails. the solution here shouldn't be 
"add a bigger timeout" it should be "make these tests faster by working with 
smaller files and smaller blocks"
   




> s3a prefetching stream to support unbuffer()
> 
>
> Key: HADOOP-18184
> URL: https://issues.apache.org/jira/browse/HADOOP-18184
> Project: Hadoop Common
>  Issue Type: Sub-task
>  Components: fs/s3
>Affects Versions: 3.4.0
>Reporter: Steve Loughran
>Assignee: Steve Loughran
>Priority: Minor
>  Labels: pull-request-available
>
> Apache Impala uses unbuffer() to free up all client side resources held by a 
> stream, so allowing it to have a map of available (path -> stream) objects, 
> retained across queries.
> This saves on having to reopen the files, with the cost of HEAD checks etc. 
> S3AInputStream just closes its http connection. here there is a lot more 
> state to discard, but all memory and file storage must be freed.
> until this done, ITestS3AContractUnbuffer must skip when the prefetch stream 
> is used.
> its notable that the other tests don't fail, even though the stream doesn't 
> implement the interface; the graceful degradation handles that. it should 
> fail if the test xml resource says the stream does it, but that the stream 
> capabilities say it doesn't.



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[GitHub] [hadoop] steveloughran commented on pull request #5832: HADOOP-18184. S3A Prefetching unbuffer.

2023-07-14 Thread via GitHub


steveloughran commented on PR #5832:
URL: https://github.com/apache/hadoop/pull/5832#issuecomment-1636111884

   timeout in lru tests
   ```
   [ERROR] Tests run: 4, Failures: 0, Errors: 1, Skipped: 0, Time elapsed: 
843.577 s <<< FAILURE! - in 
org.apache.hadoop.fs.s3a.ITestS3APrefetchingLruEviction
   [ERROR] 
testSeeksWithLruEviction[max-blocks-1](org.apache.hadoop.fs.s3a.ITestS3APrefetchingLruEviction)
  Time elapsed: 600.017 s  <<< ERROR!
   org.junit.runners.model.TestTimedOutException: test timed out after 60 
milliseconds
   at sun.misc.Unsafe.park(Native Method)
   at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
   at 
java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:837)
   at 
java.util.concurrent.locks.AbstractQueuedSynchronizer.doAcquireSharedInterruptibly(AbstractQueuedSynchronizer.java:999)
   at 
java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireSharedInterruptibly(AbstractQueuedSynchronizer.java:1308)
   at java.util.concurrent.CountDownLatch.await(CountDownLatch.java:231)
   at 
org.apache.hadoop.fs.s3a.ITestS3APrefetchingLruEviction.testSeeksWithLruEviction(ITestS3APrefetchingLruEviction.java:176)
   at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
   at 
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
   at 
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
   at java.lang.reflect.Method.invoke(Method.java:498)
   at 
org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:59)
   at 
org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
   at 
org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:56)
   at 
org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
   at 
org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:26)
   at 
org.junit.internal.runners.statements.RunAfters.evaluate(RunAfters.java:27)
   at org.junit.rules.TestWatcher$1.evaluate(TestWatcher.java:61)
   at 
org.junit.internal.runners.statements.FailOnTimeout$CallableStatement.call(FailOnTimeout.java:299)
   at 
org.junit.internal.runners.statements.FailOnTimeout$CallableStatement.call(FailOnTimeout.java:293)
   at java.util.concurrent.FutureTask.run(FutureTask.java:266)
   at java.lang.Thread.run(Thread.java:750)
   
   ```
   issue here is having all the different bulk reads in the same test case; if 
it takes too long (> 10 minutes!) then it fails. the solution here shouldn't be 
"add a bigger timeout" it should be "make these tests faster by working with 
smaller files and smaller blocks"
   


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[GitHub] [hadoop] hadoop-yetus commented on pull request #5816: YARN-11525. [Federation] Router CLI Supports Save the SubClusterPolicyConfiguration Of Queues.

2023-07-14 Thread via GitHub


hadoop-yetus commented on PR #5816:
URL: https://github.com/apache/hadoop/pull/5816#issuecomment-1636101720

   :confetti_ball: **+1 overall**
   
   
   
   
   
   
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|
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|
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when building and testing our client artifacts.  |
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Binary files and potentially other changes not applied. Please rebase and 
squash commits if necessary.  |
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[/results-checkstyle-hadoop-yarn-project_hadoop-yarn.txt](https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5816/17/artifact/out/results-checkstyle-hadoop-yarn-project_hadoop-yarn.txt)
 |  hadoop-yarn-project/hadoop-yarn: The patch generated 6 new + 65 unchanged - 
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[jira] [Commented] (HADOOP-18184) s3a prefetching stream to support unbuffer()

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18184?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743212#comment-17743212
 ] 

ASF GitHub Bot commented on HADOOP-18184:
-

steveloughran commented on PR #5832:
URL: https://github.com/apache/hadoop/pull/5832#issuecomment-1636074815

   Yes, this is a lot more than just unbuffer, but its the first time i've 
really had the code in the IDE with me writing tests to use IOStats, context 
iostats, waiting for tests to finish etc.
   
   I have more to do which I will followup on different jiras. key: actually 
support small block memory caching so you can use the stream without any disk 
use. needed to switch to this everywhere.




> s3a prefetching stream to support unbuffer()
> 
>
> Key: HADOOP-18184
> URL: https://issues.apache.org/jira/browse/HADOOP-18184
> Project: Hadoop Common
>  Issue Type: Sub-task
>  Components: fs/s3
>Affects Versions: 3.4.0
>Reporter: Steve Loughran
>Assignee: Steve Loughran
>Priority: Minor
>  Labels: pull-request-available
>
> Apache Impala uses unbuffer() to free up all client side resources held by a 
> stream, so allowing it to have a map of available (path -> stream) objects, 
> retained across queries.
> This saves on having to reopen the files, with the cost of HEAD checks etc. 
> S3AInputStream just closes its http connection. here there is a lot more 
> state to discard, but all memory and file storage must be freed.
> until this done, ITestS3AContractUnbuffer must skip when the prefetch stream 
> is used.
> its notable that the other tests don't fail, even though the stream doesn't 
> implement the interface; the graceful degradation handles that. it should 
> fail if the test xml resource says the stream does it, but that the stream 
> capabilities say it doesn't.



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[GitHub] [hadoop] steveloughran commented on pull request #5832: HADOOP-18184. S3A Prefetching unbuffer.

2023-07-14 Thread via GitHub


steveloughran commented on PR #5832:
URL: https://github.com/apache/hadoop/pull/5832#issuecomment-1636074815

   Yes, this is a lot more than just unbuffer, but its the first time i've 
really had the code in the IDE with me writing tests to use IOStats, context 
iostats, waiting for tests to finish etc.
   
   I have more to do which I will followup on different jiras. key: actually 
support small block memory caching so you can use the stream without any disk 
use. needed to switch to this everywhere.


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[jira] [Commented] (HADOOP-18184) s3a prefetching stream to support unbuffer()

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18184?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743209#comment-17743209
 ] 

ASF GitHub Bot commented on HADOOP-18184:
-

steveloughran commented on PR #5832:
URL: https://github.com/apache/hadoop/pull/5832#issuecomment-1636071189

   HADOOP-18184. S3A prefetch unbuffer
   
   * Lots of statistic collection with use in tests.
   * s3a prefetch tests all moved to prefetch. package
   * and split into caching stream and large files tests
   * large files and LRU are scale
   * and testRandomReadLargeFile uses small block size to reduce read overhead
   * new hadoop common org.apache.hadoop.test.Sizes sizes class with predefined
 sizes (from azure; not moved existing code to it yet)
   
   Overall, the prefetch reads of the large files are slow; while it's critical
   to test multi-block files, we don't need to work on the landsat csv file.
   
   better: one of the huge tests uses it, with a small block size of 1 MB to
   force lots of work.




> s3a prefetching stream to support unbuffer()
> 
>
> Key: HADOOP-18184
> URL: https://issues.apache.org/jira/browse/HADOOP-18184
> Project: Hadoop Common
>  Issue Type: Sub-task
>  Components: fs/s3
>Affects Versions: 3.4.0
>Reporter: Steve Loughran
>Assignee: Steve Loughran
>Priority: Minor
>  Labels: pull-request-available
>
> Apache Impala uses unbuffer() to free up all client side resources held by a 
> stream, so allowing it to have a map of available (path -> stream) objects, 
> retained across queries.
> This saves on having to reopen the files, with the cost of HEAD checks etc. 
> S3AInputStream just closes its http connection. here there is a lot more 
> state to discard, but all memory and file storage must be freed.
> until this done, ITestS3AContractUnbuffer must skip when the prefetch stream 
> is used.
> its notable that the other tests don't fail, even though the stream doesn't 
> implement the interface; the graceful degradation handles that. it should 
> fail if the test xml resource says the stream does it, but that the stream 
> capabilities say it doesn't.



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[GitHub] [hadoop] steveloughran commented on pull request #5832: HADOOP-18184. S3A Prefetching unbuffer.

2023-07-14 Thread via GitHub


steveloughran commented on PR #5832:
URL: https://github.com/apache/hadoop/pull/5832#issuecomment-1636071189

   HADOOP-18184. S3A prefetch unbuffer
   
   * Lots of statistic collection with use in tests.
   * s3a prefetch tests all moved to prefetch. package
   * and split into caching stream and large files tests
   * large files and LRU are scale
   * and testRandomReadLargeFile uses small block size to reduce read overhead
   * new hadoop common org.apache.hadoop.test.Sizes sizes class with predefined
 sizes (from azure; not moved existing code to it yet)
   
   Overall, the prefetch reads of the large files are slow; while it's critical
   to test multi-block files, we don't need to work on the landsat csv file.
   
   better: one of the huge tests uses it, with a small block size of 1 MB to
   force lots of work.


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[jira] [Commented] (HADOOP-18291) S3A prefetch - Implement LRU cache for SingleFilePerBlockCache

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18291?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743208#comment-17743208
 ] 

ASF GitHub Bot commented on HADOOP-18291:
-

steveloughran commented on PR #5754:
URL: https://github.com/apache/hadoop/pull/5754#issuecomment-1636070773

   merged, though now i'm using it that new test is way too slow. in my rebased 
unbuffered pr I have moved it to -Dscale, but really we can just set the block 
size down to something minimal and then work with a small file




> S3A prefetch - Implement LRU cache for SingleFilePerBlockCache
> --
>
> Key: HADOOP-18291
> URL: https://issues.apache.org/jira/browse/HADOOP-18291
> Project: Hadoop Common
>  Issue Type: Sub-task
>Affects Versions: 3.4.0
>Reporter: Ahmar Suhail
>Assignee: Viraj Jasani
>Priority: Major
>  Labels: pull-request-available
>
> Currently there is no limit on the size of disk cache. This means we could 
> have a large number of files on files, especially for access patterns that 
> are very random and do not always read the block fully. 
>  
> eg:
> in.seek(5);
> in.read(); 
> in.seek(blockSize + 10) // block 0 gets saved to disk as it's not fully read
> in.read();
> in.seek(2 * blockSize + 10) // block 1 gets saved to disk
> .. and so on
>  
> The in memory cache is bounded, and by default has a limit of 72MB (9 
> blocks). When a block is fully read, and a seek is issued it's released 
> [here|https://github.com/apache/hadoop/blob/feature-HADOOP-18028-s3a-prefetch/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/read/S3CachingInputStream.java#L109].
>  We can also delete the on disk file for the block here if it exists. 
>  
> Also maybe add an upper limit on disk space, and delete the file which stores 
> data of the block furthest from the current block (similar to the in memory 
> cache) when this limit is reached. 



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[GitHub] [hadoop] steveloughran commented on pull request #5754: HADOOP-18291. S3A prefetch - Implement thread-safe LRU cache for SingleFilePerBlockCache

2023-07-14 Thread via GitHub


steveloughran commented on PR #5754:
URL: https://github.com/apache/hadoop/pull/5754#issuecomment-1636070773

   merged, though now i'm using it that new test is way too slow. in my rebased 
unbuffered pr I have moved it to -Dscale, but really we can just set the block 
size down to something minimal and then work with a small file


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[jira] [Commented] (HADOOP-18801) Delete path directly when it can not be parsed in trash

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18801?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743205#comment-17743205
 ] 

ASF GitHub Bot commented on HADOOP-18801:
-

ayushtkn commented on code in PR #5744:
URL: https://github.com/apache/hadoop/pull/5744#discussion_r1263885805


##
hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/TrashPolicyDefault.java:
##
@@ -374,8 +382,14 @@ private void deleteCheckpoint(Path trashRoot, boolean 
deleteImmediately)
   try {
 time = getTimeFromCheckpoint(name);
   } catch (ParseException e) {
-LOG.warn("Unexpected item in trash: "+dir+". Ignoring.");
-continue;
+if (cleanNonCheckpointUnderTrashRoot) {
+  fs.delete(path, true);
+  LOG.warn("Unexpected item in trash: " + dir + ". Force to delete 
it.");

Review Comment:
   can we change to
   ```
LOG.warn("Unexpected item in trash: " + dir + ". Deleting.");
   ```



##
hadoop-common-project/hadoop-common/src/main/resources/core-default.xml:
##
@@ -974,6 +974,14 @@
   
 
 
+
+  fs.trash.clean.trashroot.enable
+  false
+  Whether clean some directories or files
+at home of Trash which are not under checkpoint directory or not.
+  

Review Comment:
   some error in language, can we change it something like
   ```
   Whether to delete directories and files in Trash home which are not under 
checkpoint directory
   ```



##
hadoop-common-project/hadoop-common/src/test/java/org/apache/hadoop/fs/TestTrash.java:
##
@@ -786,6 +787,55 @@ public void testTrashEmptier() throws Exception {
 emptierThread.join();
   }
 
+  /**
+   * Test trash emptier can whether delete non-checkpoint dir or not.

Review Comment:
   typo: can & whether don't go together
   ```
   Test trash emptier can delete non-checkpoint dir or not.
   ```





> Delete path directly when it can not be parsed in trash
> ---
>
> Key: HADOOP-18801
> URL: https://issues.apache.org/jira/browse/HADOOP-18801
> Project: Hadoop Common
>  Issue Type: Improvement
>Reporter: farmmamba
>Assignee: farmmamba
>Priority: Major
>  Labels: pull-request-available
>
> If we move path to trash dir directly rather than use delete API or rm 
> command, when 
> invoke deleteCheckpoint method, it will catch ParseException and ignore 
> deleting the path. It will never be deleted, so we should do something to 
> prevent or monitor it.
> Some logs are listed below.
>  
> {code:java}
> WARN org.apache.hadoop.fs.TrashPolicyDefault: Unexpected item in trash: 
> /user/de_eight/.Trash/college_geek_job_recall_als_modelres_5_2_6.del. 
> Ignoring.
> WARN org.apache.hadoop.fs.TrashPolicyDefault: Unexpected item in trash: 
> /user/de_eight/.Trash/college_geek_addf_vector. Ignoring.
>  {code}
>  
>  



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[GitHub] [hadoop] ayushtkn commented on a diff in pull request #5744: HADOOP-18801. Delete path directly when it can not be parsed in trash.

2023-07-14 Thread via GitHub


ayushtkn commented on code in PR #5744:
URL: https://github.com/apache/hadoop/pull/5744#discussion_r1263885805


##
hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/TrashPolicyDefault.java:
##
@@ -374,8 +382,14 @@ private void deleteCheckpoint(Path trashRoot, boolean 
deleteImmediately)
   try {
 time = getTimeFromCheckpoint(name);
   } catch (ParseException e) {
-LOG.warn("Unexpected item in trash: "+dir+". Ignoring.");
-continue;
+if (cleanNonCheckpointUnderTrashRoot) {
+  fs.delete(path, true);
+  LOG.warn("Unexpected item in trash: " + dir + ". Force to delete 
it.");

Review Comment:
   can we change to
   ```
LOG.warn("Unexpected item in trash: " + dir + ". Deleting.");
   ```



##
hadoop-common-project/hadoop-common/src/main/resources/core-default.xml:
##
@@ -974,6 +974,14 @@
   
 
 
+
+  fs.trash.clean.trashroot.enable
+  false
+  Whether clean some directories or files
+at home of Trash which are not under checkpoint directory or not.
+  

Review Comment:
   some error in language, can we change it something like
   ```
   Whether to delete directories and files in Trash home which are not under 
checkpoint directory
   ```



##
hadoop-common-project/hadoop-common/src/test/java/org/apache/hadoop/fs/TestTrash.java:
##
@@ -786,6 +787,55 @@ public void testTrashEmptier() throws Exception {
 emptierThread.join();
   }
 
+  /**
+   * Test trash emptier can whether delete non-checkpoint dir or not.

Review Comment:
   typo: can & whether don't go together
   ```
   Test trash emptier can delete non-checkpoint dir or not.
   ```



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[GitHub] [hadoop] ayushtkn merged pull request #5809: HDFS-17068. Datanode should record last directory scan time.

2023-07-14 Thread via GitHub


ayushtkn merged PR #5809:
URL: https://github.com/apache/hadoop/pull/5809


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[GitHub] [hadoop] zhtttylz commented on pull request #5836: HDFS-17083. Support getErasureCodeCodecs API in WebHDFS

2023-07-14 Thread via GitHub


zhtttylz commented on PR #5836:
URL: https://github.com/apache/hadoop/pull/5836#issuecomment-1636019383

   @ayushtkn @slfan1989 Thank you for your assistance in reviewing the code!


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[jira] [Created] (HADOOP-18804) Out of Memory when mistakenly set io.file.buffer.size to a large number

2023-07-14 Thread ConfX (Jira)
ConfX created HADOOP-18804:
--

 Summary: Out of Memory when mistakenly set io.file.buffer.size to 
a large number
 Key: HADOOP-18804
 URL: https://issues.apache.org/jira/browse/HADOOP-18804
 Project: Hadoop Common
  Issue Type: Bug
  Components: common, fs
Reporter: ConfX


h2. What happened:

When setting io.file.buffer.size to a large number, 
BufferedIOStatisticsOutputStream in Hcommon throws an out-of-memory exception 
due to inappropriate checking and handling.
The config is used to initialize a file system by passing it as one of the 
parameters bufferSize.
h2. Buggy code:

In RawLocalFileSystem.java
{code:java}
private FSDataOutputStream create(Path f, boolean overwrite,
      boolean createParent, int bufferSize, short replication, long blockSize,
      Progressable progress, FsPermission permission) throws IOException {
  ...
  return new FSDataOutputStream(new BufferedIOStatisticsOutputStream(
    createOutputStreamWithMode(f, false, permission), bufferSize, true), <<--- 
creates a BufferedIOStatisticsOutputStream with bufferSize, often set to config 
io.file.buffer.size
    statistics);
} {code}
In BufferedIOStatisticsOutputStream.java:
{code:java}
public class BufferedIOStatisticsOutputStream extends BufferedOutputStream
  implements IOStatisticsSource, Syncable, StreamCapabilities {
  ...
  public BufferedIOStatisticsOutputStream(
      final OutputStream out,
      final int size,
      final boolean downgradeSyncable) {
    super(out, size); <<--- init the BufferedOutputStream with a huge buffer 
size
    ...
  }{code}
h2. StackTrace:
{code:java}
java.lang.OutOfMemoryError: Java heap space
        at 
java.base/java.io.BufferedOutputStream.(BufferedOutputStream.java:75)
        at 
org.apache.hadoop.fs.statistics.BufferedIOStatisticsOutputStream.(BufferedIOStatisticsOutputSt
ream.java:78)
        at 
org.apache.hadoop.fs.RawLocalFileSystem.create(RawLocalFileSystem.java:428)
        at 
org.apache.hadoop.fs.RawLocalFileSystem.create(RawLocalFileSystem.java:413)
        at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1175)
        at 
org.apache.hadoop.fs.contract.ContractTestUtils.writeDataset(ContractTestUtils.java:183)
        at 
org.apache.hadoop.fs.contract.ContractTestUtils.writeDataset(ContractTestUtils.java:152)
        at 
org.apache.hadoop.fs.contract.AbstractContractRenameTest.expectRenameUnderFileFails(AbstractContract
RenameTest.java:335)
...{code}
h2. Reproduce:

(1) Set io.file.buffer.size to a large value, e.g., 2112001717
(2) Run a simple test that exercises this parameter, e.g. 
org.apache.hadoop.fs.contract.rawlocal.TestRawlocalContractRename#testRenameFileUnderFile



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[jira] [Updated] (HADOOP-18802) Collision of config key name fs.viewfs.mounttable.default.name.key to other keys that specify the entry point to mount tables

2023-07-14 Thread ConfX (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18802?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

ConfX updated HADOOP-18802:
---
Description: 
h2. What happened:

When manually set fs.viewfs.mounttable.default.name.key to default (the same as 
default value) in HCommon, test 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches
 would fail.
But the test can pass if this parameter is not manually set in the 
configuration file.
h2. Where's the bug:

In the constructor of InodeTree, the tree attempts to get all the mount table 
entry points set by user in the configuration and process them one by one:
{code:java}
for (Entry si : config) {       
final String key = si.getKey();       
if (!key.startsWith(mountTablePrefix)) {         
continue;       
}  
    
gotMountTableEntry = true;       
LinkType linkType;       
String src = key.substring(mountTablePrefix.length());       
...
{code}
Here mountTablePrefix="fs.viewfs.mounttable.default.". However, it just so 
happens that the name of the configuration users use to specify the default 
mount table is fs.viewfs.mounttable.default.name.key. Thus, if a user specifies 
the default mount table and uses InodeTree the name.key would be falsely parsed 
as the entry point to one of the mount tables, which would cause InodeTree to 
throw an exception since name.key is not a valid entry.
h2. Stack trace:
{code:java}
java.lang.RuntimeException: java.io.IOException: ViewFs: Cannot initialize: 
Invalid entry in Mount table in config: name.key
        at org.apache.hadoop.fs.FileContext.getFileContext(FileContext.java:470)
at 
org.apache.hadoop.fs.viewfs.ViewFsTestSetup.setupForViewFsLocalFs(ViewFsTestSetup.java:88)
at 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs.setUp(TestFcMainOperationsLocalFs.java:38){code}
h2. How to reproduce:

(1) Set fs.viewfs.mounttable.default.name.key to default
(2) Run test 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches

You can use the reproduce.sh in the attachment to easily reproduce the bug.

We are happy to provide a patch if this issue is confirmed. 

  was:
h2. What happened:

When manually set fs.viewfs.mounttable.default.name.key to default (the same as 
default value) in HCommon, test 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches
 would fail.
But the test can pass if this parameter is not manually set in the 
configuration file.
h2. Where's the bug:

In the constructor of InodeTree, the tree attempts to get all the mount table 
entry points set by user in the configuration and process them one by one:
{code:java}
for (Entry si : config) {       
final String key = si.getKey();       
if (!key.startsWith(mountTablePrefix)) {         
continue;       
}  
    
gotMountTableEntry = true;       
LinkType linkType;       
String src = key.substring(mountTablePrefix.length());       
...
{code}
Here mountTablePrefix="fs.viewfs.mounttable.default.". However, it just so 
happens that the name of the configuration users use to specify the default 
mount table is fs.viewfs.mounttable.default.name.key. Thus, if a user specifies 
the default mount table and uses InodeTree the name.key would be falsely parsed 
as the entry point to one of the mount tables, which would cause InodeTree to 
throw an exception since name.key is not a valid entry.
h2. Stack trace:
{code:java}
java.lang.RuntimeException: java.io.IOException: ViewFs: Cannot initialize: 
Invalid entry in Mount table in config: name.key
        at org.apache.hadoop.fs.FileContext.getFileContext(FileContext.java:470)
at 
org.apache.hadoop.fs.viewfs.ViewFsTestSetup.setupForViewFsLocalFs(ViewFsTestSetup.java:88)
at 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs.setUp(TestFcMainOperationsLocalFs.java:38){code}
h2. How to reproduce:

(1) Set fs.viewfs.mounttable.default.name.key to default
(2) Run test 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches

You can use the reproduce.sh in the attachment to easily reproduce the bug:

We are happy to provide a patch if this issue is confirmed. 


> Collision of config key name fs.viewfs.mounttable.default.name.key to other 
> keys that specify the entry point to mount tables
> -
>
> Key: HADOOP-18802
> URL: https://issues.apache.org/jira/browse/HADOOP-18802
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: common, conf, fs
>Reporter: ConfX
>Priority: Critical
> Attachments: reproduce.sh
>
>
> h2. What happened:
> When manually set 

[jira] [Updated] (HADOOP-18803) ClassCastException in test TestRPC#testWrappedStopProxy

2023-07-14 Thread ConfX (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18803?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

ConfX updated HADOOP-18803:
---
Description: 
h2. What happened:

In HCommon, test TestRPC#testWrappedStopProxy tries to cast 
org.apache.hadoop.ipc.WritableRpcEngine$Invoker to 
org.apache.hadoop.ipc.TestRPC$StoppedInvocationHandler and causes 
ClassCastException.
h2. Buggy code:

In TestRPC.java:
{code:java}
@Test
public void testWrappedStopProxy() throws IOException {
  StoppedProtocol wrappedProxy = RPC.getProxy(StoppedProtocol.class,
      StoppedProtocol.versionID, null, conf);
  StoppedInvocationHandler invocationHandler = (StoppedInvocationHandler)    // 
<--- Here causes ClassCastException
      Proxy.getInvocationHandler(wrappedProxy);
  ...
} {code}
h2. How to reproduce:

(1) Just directly run test TestRPC#testWrappedStopProxy.

You can use the reproduce.sh in the attachment to easily reproduce the bug.

We are happy to provide a patch if this issue is confirmed. 

  was:
h2. What happened:

In HCommon, test TestRPC#testWrappedStopProxy tries to cast 
org.apache.hadoop.ipc.WritableRpcEngine$Invoker to 
org.apache.hadoop.ipc.TestRPC$StoppedInvocationHandler and causes 
ClassCastException.
h2. Buggy code:

In TestRPC.java:

 
{code:java}
@Test
public void testWrappedStopProxy() throws IOException {
  StoppedProtocol wrappedProxy = RPC.getProxy(StoppedProtocol.class,
      StoppedProtocol.versionID, null, conf);
  StoppedInvocationHandler invocationHandler = (StoppedInvocationHandler)    // 
<--- Here causes ClassCastException
      Proxy.getInvocationHandler(wrappedProxy);
  ...
} {code}
 
h2. How to reproduce:

(1) Just directly run test TestRPC#testWrappedStopProxy.

You can use the reproduce.sh in the attachment to easily reproduce the bug:

We are happy to provide a patch if this issue is confirmed. 


> ClassCastException in test TestRPC#testWrappedStopProxy
> ---
>
> Key: HADOOP-18803
> URL: https://issues.apache.org/jira/browse/HADOOP-18803
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: common, ipc
>Reporter: ConfX
>Priority: Critical
> Attachments: reproduce.sh
>
>
> h2. What happened:
> In HCommon, test TestRPC#testWrappedStopProxy tries to cast 
> org.apache.hadoop.ipc.WritableRpcEngine$Invoker to 
> org.apache.hadoop.ipc.TestRPC$StoppedInvocationHandler and causes 
> ClassCastException.
> h2. Buggy code:
> In TestRPC.java:
> {code:java}
> @Test
> public void testWrappedStopProxy() throws IOException {
>   StoppedProtocol wrappedProxy = RPC.getProxy(StoppedProtocol.class,
>       StoppedProtocol.versionID, null, conf);
>   StoppedInvocationHandler invocationHandler = (StoppedInvocationHandler)    
> // <--- Here causes ClassCastException
>       Proxy.getInvocationHandler(wrappedProxy);
>   ...
> } {code}
> h2. How to reproduce:
> (1) Just directly run test TestRPC#testWrappedStopProxy.
> You can use the reproduce.sh in the attachment to easily reproduce the bug.
> We are happy to provide a patch if this issue is confirmed. 



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[jira] [Created] (HADOOP-18803) ClassCastException in test TestRPC#testWrappedStopProxy

2023-07-14 Thread ConfX (Jira)
ConfX created HADOOP-18803:
--

 Summary: ClassCastException in test TestRPC#testWrappedStopProxy
 Key: HADOOP-18803
 URL: https://issues.apache.org/jira/browse/HADOOP-18803
 Project: Hadoop Common
  Issue Type: Bug
  Components: common, ipc
Reporter: ConfX
 Attachments: reproduce.sh

h2. What happened:

In HCommon, test TestRPC#testWrappedStopProxy tries to cast 
org.apache.hadoop.ipc.WritableRpcEngine$Invoker to 
org.apache.hadoop.ipc.TestRPC$StoppedInvocationHandler and causes 
ClassCastException.
h2. Buggy code:

In TestRPC.java:

 
{code:java}
@Test
public void testWrappedStopProxy() throws IOException {
  StoppedProtocol wrappedProxy = RPC.getProxy(StoppedProtocol.class,
      StoppedProtocol.versionID, null, conf);
  StoppedInvocationHandler invocationHandler = (StoppedInvocationHandler)    // 
<--- Here causes ClassCastException
      Proxy.getInvocationHandler(wrappedProxy);
  ...
} {code}
 
h2. How to reproduce:

(1) Just directly run test TestRPC#testWrappedStopProxy.

You can use the reproduce.sh in the attachment to easily reproduce the bug:

We are happy to provide a patch if this issue is confirmed. 



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[jira] [Commented] (HADOOP-18776) Add OptimizedS3AMagicCommitter For Zero Rename Commits to S3 Endpoints

2023-07-14 Thread Syed Shameerur Rahman (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18776?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743161#comment-17743161
 ] 

Syed Shameerur Rahman commented on HADOOP-18776:


[~ste...@apache.org] - If i understood your comment, You are proposing 
something like even if this committer(which does complete mpu in commitTask) is 
enabled when task attempt retry is 1 then we are okay, If not there should be 
some mechanism to fail the job when we use this committer and  task attempt 
retry > 1 and the task which failed had called commitTask operation

Am i correct?

> Add OptimizedS3AMagicCommitter For Zero Rename Commits to S3 Endpoints
> --
>
> Key: HADOOP-18776
> URL: https://issues.apache.org/jira/browse/HADOOP-18776
> Project: Hadoop Common
>  Issue Type: New Feature
>  Components: fs/s3
>Reporter: Syed Shameerur Rahman
>Priority: Major
>  Labels: pull-request-available
>
> The goal is to add a new S3A committer named *OptimizedS3AMagicCommitter* 
> which is an another type of S3 Magic committer but with a better performance 
> by taking in few tradeoffs.
> The following are the differences in MagicCommitter vs OptimizedMagicCommitter
>  
> ||Operation||Magic Committer||*OptimizedS3AMagicCommitter*||
> |commitTask|1. Lists all {{.pending}} files in its attempt directory.
>  
> 2. The contents are loaded into a list of single pending uploads.
>  
> 3. Saved to a {{.pendingset}} file in the job attempt directory.|1. Lists all 
> {{.pending}} files in its attempt directory
>  
> 2. The contents are loaded into a list of single pending uploads.
>  
> 3. For each pending upload, commit operation is called (complete 
> multiPartUpload)|
> |commitJob|1. Loads all {{.pendingset}} files in its job attempt directory
>  
> 2. Then every pending commit in the job will be committed.
>  
> 3. "SUCCESS" marker is created (if config is enabled)
>  
> 4. "__magic" directory is cleaned up.|1. "SUCCESS" marker is created (if 
> config is enabled)
>  
> 2.  "__magic" directory is cleaned up.|
>  
> *Performance Benefits :-*
>  # The primary performance boost due to distributed complete multiPartUpload 
> call being made in the taskAttempts(Task containers/Executors) rather than a 
> single job driver. In case of MagicCommitter it is O(files/threads).
>  # It also saves a couple of S3 calls needed to PUT the "{{{}.pendingset{}}}" 
> files and READ call to read them in the Job Driver.
>  
> *TradeOffs :-*
> The tradeoffs are similar to the one in FileOutputCommitter V2 version. Users 
> migrating from FileOutputCommitter V2 to OptimizedS3AMagicCommitter will no 
> see behavioral change as such
>  # During execution, intermediate data becomes visible after commitTask 
> operation
>  # On a failure, all output must be deleted and the job needs to be restarted.
>  
> *Performance Benchmark :-*
> Cluster : c4.8x large (ec2-instance)
> Instance : 1 (primary) + 5 (core)
> Data Size : 3TB Partitioned(TPC-DS store_sales data)
> Engine : Apache Spark 3.3.1 / Hadoop 3.3.3
> Query: The following query inserts around 3000+ files into the table 
> directory (ran for 3 iterations)
> {code:java}
> insert into  select ss_quantity from store_sales; {code}
> ||Committer||Iteration 1||Iteration 2||Iteration 3||
> |Magic|126|127|122|
> |OptimizedMagic|50|51|58|
> So on an average, OptimizedMagicCommitter was *~2.3x* faster as compared to 
> MagicCommitter.
>  
> _*Note: Unlike MagicCommitter , OptimizedMagicCommitter is not suitable for 
> all the cases where in user requires the guarantees of file not being visible 
> in failure scenarios. Given the performance benefit, user can may choose to 
> use this if they don't require any guarantees or have some mechanism to clean 
> up the data before retrying.*_
>  



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[jira] [Updated] (HADOOP-18802) Collision of config key name fs.viewfs.mounttable.default.name.key to other keys that specify the entry point to mount tables

2023-07-14 Thread ConfX (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18802?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

ConfX updated HADOOP-18802:
---
Description: 
h2. What happened:

When manually set fs.viewfs.mounttable.default.name.key to default (the same as 
default value) in HCommon, test 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches
 would fail.
But the test can pass if this parameter is not manually set in the 
configuration file.
h2. Where's the bug:

In the constructor of InodeTree, the tree attempts to get all the mount table 
entry points set by user in the configuration and process them one by one:
{code:java}
for (Entry si : config) {       
final String key = si.getKey();       
if (!key.startsWith(mountTablePrefix)) {         
continue;       
}  
    
gotMountTableEntry = true;       
LinkType linkType;       
String src = key.substring(mountTablePrefix.length());       
...
{code}
Here mountTablePrefix="fs.viewfs.mounttable.default.". However, it just so 
happens that the name of the configuration users use to specify the default 
mount table is fs.viewfs.mounttable.default.name.key. Thus, if a user specifies 
the default mount table and uses InodeTree the name.key would be falsely parsed 
as the entry point to one of the mount tables, which would cause InodeTree to 
throw an exception since name.key is not a valid entry.
h2. Stack trace:
{code:java}
java.lang.RuntimeException: java.io.IOException: ViewFs: Cannot initialize: 
Invalid entry in Mount table in config: name.key
        at org.apache.hadoop.fs.FileContext.getFileContext(FileContext.java:470)
at 
org.apache.hadoop.fs.viewfs.ViewFsTestSetup.setupForViewFsLocalFs(ViewFsTestSetup.java:88)
at 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs.setUp(TestFcMainOperationsLocalFs.java:38){code}
h2. How to reproduce:

(1) Set fs.viewfs.mounttable.default.name.key to default
(2) Run test 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches

You can use the reproduce.sh in the attachment to easily reproduce the bug:

We are happy to provide a patch if this issue is confirmed. 

  was:
h2. What happened:

When manually set fs.viewfs.mounttable.default.name.key to default (the same as 
default value) in HCommon, test 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches
 would fail.
But the test can pass if this parameter is not manually set in the 
configuration file.
h2. Where's the bug:

In the constructor of InodeTree, the tree attempts to get all the mount table 
entry points set by user in the configuration and process them one by one:
{code:java}
for (Entry si : config) {       
final String key = si.getKey();       
if (!key.startsWith(mountTablePrefix)) {         
continue;       
}  
    
gotMountTableEntry = true;       
LinkType linkType;       
String src = key.substring(mountTablePrefix.length());       
...
{code}
Here {{{}mountTablePrefix="fs.viewfs.mounttable.default."{}}}. However, it just 
so happens that the name of the configuration users use to specify the default 
mount table is {{{}fs.viewfs.mounttable.default.name.key{}}}. Thus, if a user 
specifies the default mount table and uses InodeTree the {{name.key}} would be 
falsely parsed as the entry point to one of the mount tables, which would cause 
{{InodeTree}} to throw an exception since {{name.key}} is not a valid entry.
h2. Stack trace:
{code:java}
java.lang.RuntimeException: java.io.IOException: ViewFs: Cannot initialize: 
Invalid entry in Mount table in config: name.key
        at org.apache.hadoop.fs.FileContext.getFileContext(FileContext.java:470)
at 
org.apache.hadoop.fs.viewfs.ViewFsTestSetup.setupForViewFsLocalFs(ViewFsTestSetup.java:88)
at 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs.setUp(TestFcMainOperationsLocalFs.java:38){code}
h2. How to reproduce:

(1) Set {{fs.viewfs.mounttable.default.name.key}} to {{default}}
(2) Run test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}

You can use the reproduce.sh in the attachment to easily reproduce the bug:

We are happy to provide a patch if this issue is confirmed. 


> Collision of config key name fs.viewfs.mounttable.default.name.key to other 
> keys that specify the entry point to mount tables
> -
>
> Key: HADOOP-18802
> URL: https://issues.apache.org/jira/browse/HADOOP-18802
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: common, conf, fs
>Reporter: ConfX
>Priority: Critical
> Attachments: reproduce.sh
>
>
> h2. 

[jira] [Updated] (HADOOP-18802) Collision of config key name fs.viewfs.mounttable.default.name.key to other keys that specify the entry point to mount tables

2023-07-14 Thread ConfX (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18802?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

ConfX updated HADOOP-18802:
---
Description: 
h2. What happened:

When manually set fs.viewfs.mounttable.default.name.key to default (the same as 
default value) in HCommon, test 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches
 would fail.
But the test can pass if this parameter is not manually set in the 
configuration file.
h2. Where's the bug:

In the constructor of InodeTree, the tree attempts to get all the mount table 
entry points set by user in the configuration and process them one by one:
{code:java}
for (Entry si : config) {       
final String key = si.getKey();       
if (!key.startsWith(mountTablePrefix)) {         
continue;       
}  
    
gotMountTableEntry = true;       
LinkType linkType;       
String src = key.substring(mountTablePrefix.length());       
...
{code}
Here {{{}mountTablePrefix="fs.viewfs.mounttable.default."{}}}. However, it just 
so happens that the name of the configuration users use to specify the default 
mount table is {{{}fs.viewfs.mounttable.default.name.key{}}}. Thus, if a user 
specifies the default mount table and uses InodeTree the {{name.key}} would be 
falsely parsed as the entry point to one of the mount tables, which would cause 
{{InodeTree}} to throw an exception since {{name.key}} is not a valid entry.
h2. Stack trace:
{code:java}
java.lang.RuntimeException: java.io.IOException: ViewFs: Cannot initialize: 
Invalid entry in Mount table in config: name.key
        at org.apache.hadoop.fs.FileContext.getFileContext(FileContext.java:470)
at 
org.apache.hadoop.fs.viewfs.ViewFsTestSetup.setupForViewFsLocalFs(ViewFsTestSetup.java:88)
at 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs.setUp(TestFcMainOperationsLocalFs.java:38){code}
h2. How to reproduce:

(1) Set {{fs.viewfs.mounttable.default.name.key}} to {{default}}
(2) Run test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}

You can use the reproduce.sh in the attachment to easily reproduce the bug:

We are happy to provide a patch if this issue is confirmed. 

  was:
h2. What happened:

When manually set fs.viewfs.mounttable.default.name.key to default (the same as 
default value) in HCommon, test 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches
 would fail.
But the test can pass if this parameter is not manually set in the 
configuration file.
h2. Where's the bug:

In the constructor of {{{}InodeTree{}}}, the tree attempts to get all the mount 
table entry points set by user in the configuration and process them one by one:
{code:java}
for (Entry si : config) {       
final String key = si.getKey();       
if (!key.startsWith(mountTablePrefix)) {         
continue;       
}  
    
gotMountTableEntry = true;       
LinkType linkType;       
String src = key.substring(mountTablePrefix.length());       
...
{code}
Here {{{}mountTablePrefix="fs.viewfs.mounttable.default."{}}}. However, it just 
so happens that the name of the configuration users use to specify the default 
mount table is {{{}fs.viewfs.mounttable.default.name.key{}}}. Thus, if a user 
specifies the default mount table and uses InodeTree the {{name.key}} would be 
falsely parsed as the entry point to one of the mount tables, which would cause 
{{InodeTree}} to throw an exception since {{name.key}} is not a valid entry.
h2. Stack trace:
{code:java}
java.lang.RuntimeException: java.io.IOException: ViewFs: Cannot initialize: 
Invalid entry in Mount table in config: name.key
        at org.apache.hadoop.fs.FileContext.getFileContext(FileContext.java:470)
at 
org.apache.hadoop.fs.viewfs.ViewFsTestSetup.setupForViewFsLocalFs(ViewFsTestSetup.java:88)
at 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs.setUp(TestFcMainOperationsLocalFs.java:38){code}
h2. How to reproduce:

(1) Set {{fs.viewfs.mounttable.default.name.key}} to {{default}}
(2) Run test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}

You can use the reproduce.sh in the attachment to easily reproduce the bug:

We are happy to provide a patch if this issue is confirmed. 


> Collision of config key name fs.viewfs.mounttable.default.name.key to other 
> keys that specify the entry point to mount tables
> -
>
> Key: HADOOP-18802
> URL: https://issues.apache.org/jira/browse/HADOOP-18802
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: common, conf, fs
>Reporter: ConfX
>Priority: Critical
> 

[jira] [Updated] (HADOOP-18802) Collision of config key name fs.viewfs.mounttable.default.name.key to other keys that specify the entry point to mount tables

2023-07-14 Thread ConfX (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18802?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

ConfX updated HADOOP-18802:
---
Description: 
h2. What happened:

When manually set fs.viewfs.mounttable.default.name.key to default (the same as 
default value) in HCommon, test 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches
 would fail.
But the test can pass if this parameter is not manually set in the 
configuration file.
h2. Where's the bug:

In the constructor of {{{}InodeTree{}}}, the tree attempts to get all the mount 
table entry points set by user in the configuration and process them one by one:
{code:java}
for (Entry si : config) {       
final String key = si.getKey();       
if (!key.startsWith(mountTablePrefix)) {         
continue;       
}  
    
gotMountTableEntry = true;       
LinkType linkType;       
String src = key.substring(mountTablePrefix.length());       
...
{code}
Here {{{}mountTablePrefix="fs.viewfs.mounttable.default."{}}}. However, it just 
so happens that the name of the configuration users use to specify the default 
mount table is {{{}fs.viewfs.mounttable.default.name.key{}}}. Thus, if a user 
specifies the default mount table and uses InodeTree the {{name.key}} would be 
falsely parsed as the entry point to one of the mount tables, which would cause 
{{InodeTree}} to throw an exception since {{name.key}} is not a valid entry.
h2. Stack trace:
{code:java}
java.lang.RuntimeException: java.io.IOException: ViewFs: Cannot initialize: 
Invalid entry in Mount table in config: name.key
        at org.apache.hadoop.fs.FileContext.getFileContext(FileContext.java:470)
at 
org.apache.hadoop.fs.viewfs.ViewFsTestSetup.setupForViewFsLocalFs(ViewFsTestSetup.java:88)
at 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs.setUp(TestFcMainOperationsLocalFs.java:38){code}
h2. How to reproduce:

(1) Set {{fs.viewfs.mounttable.default.name.key}} to {{default}}
(2) Run test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}

You can use the reproduce.sh in the attachment to easily reproduce the bug:

We are happy to provide a patch if this issue is confirmed. 

  was:
h2. What happened:

When manually set {{fs.viewfs.mounttable.default.name.key}} to {{default}} (the 
same as default value) in HCommon, test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}
 would fail.
But the test can pass if this parameter is not manually set in the 
configuration file.
h2. Where's the bug:

In the constructor of {{{}InodeTree{}}}, the tree attempts to get all the mount 
table entry points set by user in the configuration and process them one by one:
{code:java}
for (Entry si : config) {       
final String key = si.getKey();       
if (!key.startsWith(mountTablePrefix)) {         
continue;       
}  
    
gotMountTableEntry = true;       
LinkType linkType;       
String src = key.substring(mountTablePrefix.length());       
...
{code}
Here {{{}mountTablePrefix="fs.viewfs.mounttable.default."{}}}. However, it just 
so happens that the name of the configuration users use to specify the default 
mount table is {{{}fs.viewfs.mounttable.default.name.key{}}}. Thus, if a user 
specifies the default mount table and uses InodeTree the {{name.key}} would be 
falsely parsed as the entry point to one of the mount tables, which would cause 
{{InodeTree}} to throw an exception since {{name.key}} is not a valid entry.
h2. Stack trace:
{code:java}
java.lang.RuntimeException: java.io.IOException: ViewFs: Cannot initialize: 
Invalid entry in Mount table in config: name.key
        at org.apache.hadoop.fs.FileContext.getFileContext(FileContext.java:470)
at 
org.apache.hadoop.fs.viewfs.ViewFsTestSetup.setupForViewFsLocalFs(ViewFsTestSetup.java:88)
at 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs.setUp(TestFcMainOperationsLocalFs.java:38){code}
h2. How to reproduce:

(1) Set {{fs.viewfs.mounttable.default.name.key}} to {{default}}
(2) Run test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}

You can use the reproduce.sh in the attachment to easily reproduce the bug:

We are happy to provide a patch if this issue is confirmed. 

{{}}


> Collision of config key name fs.viewfs.mounttable.default.name.key to other 
> keys that specify the entry point to mount tables
> -
>
> Key: HADOOP-18802
> URL: https://issues.apache.org/jira/browse/HADOOP-18802
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: common, conf, fs
>Reporter: ConfX
>   

[jira] [Updated] (HADOOP-18802) Collision of config key name fs.viewfs.mounttable.default.name.key to other keys that specify the entry point to mount tables

2023-07-14 Thread ConfX (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18802?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

ConfX updated HADOOP-18802:
---
Description: 
h2. What happened:

When manually set {{fs.viewfs.mounttable.default.name.key}} to {{default}} (the 
same as default value) in HCommon, test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}
 would fail.
But the test can pass if this parameter is not manually set in the 
configuration file.
h2. Where's the bug:

In the constructor of {{{}InodeTree{}}}, the tree attempts to get all the mount 
table entry points set by user in the configuration and process them one by one:
{code:java}
for (Entry si : config) {       
final String key = si.getKey();       
if (!key.startsWith(mountTablePrefix)) {         
continue;       
}  
    
gotMountTableEntry = true;       
LinkType linkType;       
String src = key.substring(mountTablePrefix.length());       
...
{code}
Here {{{}mountTablePrefix="fs.viewfs.mounttable.default."{}}}. However, it just 
so happens that the name of the configuration users use to specify the default 
mount table is {{{}fs.viewfs.mounttable.default.name.key{}}}. Thus, if a user 
specifies the default mount table and uses InodeTree the {{name.key}} would be 
falsely parsed as the entry point to one of the mount tables, which would cause 
{{InodeTree}} to throw an exception since {{name.key}} is not a valid entry.
h2. Stack trace:
{code:java}
java.lang.RuntimeException: java.io.IOException: ViewFs: Cannot initialize: 
Invalid entry in Mount table in config: name.key
        at org.apache.hadoop.fs.FileContext.getFileContext(FileContext.java:470)
at 
org.apache.hadoop.fs.viewfs.ViewFsTestSetup.setupForViewFsLocalFs(ViewFsTestSetup.java:88)
at 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs.setUp(TestFcMainOperationsLocalFs.java:38){code}
h2. How to reproduce:

(1) Set {{fs.viewfs.mounttable.default.name.key}} to {{default}}
(2) Run test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}

You can use the reproduce.sh in the attachment to easily reproduce the bug:

We are happy to provide a patch if this issue is confirmed. 

{{}}

  was:
h2. What happened:

When manually set {{fs.viewfs.mounttable.default.name.key}} to {{default}} (the 
same as default value) in HCommon, test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}
 would fail.
But the test can pass if this parameter is not manually set in the 
configuration file.
h2. Where's the bug:

In the constructor of {{{}InodeTree{}}}, the tree attempts to get all the mount 
table entry points set by user in the configuration and process them one by one:
{code:java}
for (Entry si : config) {       
final String key = si.getKey();       if 
(!key.startsWith(mountTablePrefix)) {         continue;       }      
gotMountTableEntry = true;       LinkType linkType;       String src = 
key.substring(mountTablePrefix.length());       ...
{code}
Here {{{}mountTablePrefix="fs.viewfs.mounttable.default."{}}}. However, it just 
so happens that the name of the configuration users use to specify the default 
mount table is {{{}fs.viewfs.mounttable.default.name.key{}}}. Thus, if a user 
specifies the default mount table and uses InodeTree the {{name.key}} would be 
falsely parsed as the entry point to one of the mount tables, which would cause 
{{InodeTree}} to throw an exception since {{name.key}} is not a valid entry.
h2. Stack trace:

java.lang.RuntimeException: java.io.IOException: ViewFs: Cannot initialize: 
Invalid entry in Mount table in config: name.keyat 
org.apache.hadoop.fs.FileContext.getFileContext(FileContext.java:470) at 
org.apache.hadoop.fs.viewfs.ViewFsTestSetup.setupForViewFsLocalFs(ViewFsTestSetup.java:88)
 at 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs.setUp(TestFcMainOperationsLocalFs.java:38)
h2. How to reproduce:

(1) Set {{fs.viewfs.mounttable.default.name.key}} to {{default}}
(2) Run test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}

You can use the reproduce.sh in the attachment to easily reproduce the bug:

We are happy to provide a patch if this issue is confirmed. 

{{}}


> Collision of config key name fs.viewfs.mounttable.default.name.key to other 
> keys that specify the entry point to mount tables
> -
>
> Key: HADOOP-18802
> URL: https://issues.apache.org/jira/browse/HADOOP-18802
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: common, conf, fs
>Reporter: ConfX
>Priority: Critical
> Attachments: reproduce.sh
>

[GitHub] [hadoop] hadoop-yetus commented on pull request #5841: YARN-11531. [Federation] Code cleanup for NodeManager#amrmproxy.

2023-07-14 Thread via GitHub


hadoop-yetus commented on PR #5841:
URL: https://github.com/apache/hadoop/pull/5841#issuecomment-1635845485

   :confetti_ball: **+1 overall**
   
   
   
   
   
   
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 |  
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[jira] [Updated] (HADOOP-18802) Collision of config key name fs.viewfs.mounttable.default.name.key to other keys that specify the entry point to mount tables

2023-07-14 Thread ConfX (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18802?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

ConfX updated HADOOP-18802:
---
Description: 
h2. What happened:

When manually set {{fs.viewfs.mounttable.default.name.key}} to {{default}} (the 
same as default value) in HCommon, test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}
 would fail.
But the test can pass if this parameter is not manually set in the 
configuration file.
h2. Where's the bug:

In the constructor of {{{}InodeTree{}}}, the tree attempts to get all the mount 
table entry points set by user in the configuration and process them one by one:
{code:java}
for (Entry si : config) {       
final String key = si.getKey();       if 
(!key.startsWith(mountTablePrefix)) {         continue;       }      
gotMountTableEntry = true;       LinkType linkType;       String src = 
key.substring(mountTablePrefix.length());       ...
{code}
Here {{{}mountTablePrefix="fs.viewfs.mounttable.default."{}}}. However, it just 
so happens that the name of the configuration users use to specify the default 
mount table is {{{}fs.viewfs.mounttable.default.name.key{}}}. Thus, if a user 
specifies the default mount table and uses InodeTree the {{name.key}} would be 
falsely parsed as the entry point to one of the mount tables, which would cause 
{{InodeTree}} to throw an exception since {{name.key}} is not a valid entry.
h2. Stack trace:

java.lang.RuntimeException: java.io.IOException: ViewFs: Cannot initialize: 
Invalid entry in Mount table in config: name.keyat 
org.apache.hadoop.fs.FileContext.getFileContext(FileContext.java:470) at 
org.apache.hadoop.fs.viewfs.ViewFsTestSetup.setupForViewFsLocalFs(ViewFsTestSetup.java:88)
 at 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs.setUp(TestFcMainOperationsLocalFs.java:38)
h2. How to reproduce:

(1) Set {{fs.viewfs.mounttable.default.name.key}} to {{default}}
(2) Run test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}

You can use the reproduce.sh in the attachment to easily reproduce the bug:

We are happy to provide a patch if this issue is confirmed. 

{{}}

  was:
h2. What happened:

When manually set {{fs.viewfs.mounttable.default.name.key}} to {{default}} (the 
same as default value) in HCommon, test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}
 would fail.
But the test can pass if this parameter is not manually set in the 
configuration file.
h2. Where's the bug:

In the constructor of {{{}InodeTree{}}}, the tree attempts to get all the mount 
table entry points set by user in the configuration and process them one by one:
for (Entry si : config) {  final String key = 
si.getKey();  if (!key.startsWith(mountTablePrefix)) {continue;
  }  gotMountTableEntry = true;  LinkType linkType;  String src 
= key.substring(mountTablePrefix.length());
  ...
Here {{{}mountTablePrefix="fs.viewfs.mounttable.default."{}}}. However, it just 
so happens that the name of the configuration users use to specify the default 
mount table is {{{}fs.viewfs.mounttable.default.name.key{}}}. Thus, if a user 
specifies the default mount table and uses InodeTree the {{name.key}} would be 
falsely parsed as the entry point to one of the mount tables, which would cause 
{{InodeTree}} to throw an exception since {{name.key}} is not a valid entry.
h2. Stack trace:
java.lang.RuntimeException: java.io.IOException: ViewFs: Cannot initialize: 
Invalid entry in Mount table in config: name.keyat 
org.apache.hadoop.fs.FileContext.getFileContext(FileContext.java:470)at 
org.apache.hadoop.fs.viewfs.ViewFsTestSetup.setupForViewFsLocalFs(ViewFsTestSetup.java:88)
at 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs.setUp(TestFcMainOperationsLocalFs.java:38)
h2. How to reproduce:

(1) Set {{fs.viewfs.mounttable.default.name.key}} to {{default}}
(2) Run test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}

You can use the reproduce.sh in the attachment to easily reproduce the bug:

We are happy to provide a patch if this issue is confirmed. 

{{}}


> Collision of config key name fs.viewfs.mounttable.default.name.key to other 
> keys that specify the entry point to mount tables
> -
>
> Key: HADOOP-18802
> URL: https://issues.apache.org/jira/browse/HADOOP-18802
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: common, conf, fs
>Reporter: ConfX
>Priority: Critical
> Attachments: reproduce.sh
>
>
> h2. What happened:
> When manually set {{fs.viewfs.mounttable.default.name.key}} to 

[jira] [Created] (HADOOP-18802) Collision of config key name fs.viewfs.mounttable.default.name.key to other keys that specify the entry point to mount tables

2023-07-14 Thread ConfX (Jira)
ConfX created HADOOP-18802:
--

 Summary: Collision of config key name 
fs.viewfs.mounttable.default.name.key to other keys that specify the entry 
point to mount tables
 Key: HADOOP-18802
 URL: https://issues.apache.org/jira/browse/HADOOP-18802
 Project: Hadoop Common
  Issue Type: Bug
  Components: common, conf, fs
Reporter: ConfX
 Attachments: reproduce.sh

h2. What happened:

When manually set {{fs.viewfs.mounttable.default.name.key}} to {{default}} (the 
same as default value) in HCommon, test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}
 would fail.
But the test can pass if this parameter is not manually set in the 
configuration file.
h2. Where's the bug:

In the constructor of {{{}InodeTree{}}}, the tree attempts to get all the mount 
table entry points set by user in the configuration and process them one by one:
for (Entry si : config) {  final String key = 
si.getKey();  if (!key.startsWith(mountTablePrefix)) {continue;
  }  gotMountTableEntry = true;  LinkType linkType;  String src 
= key.substring(mountTablePrefix.length());
  ...
Here {{{}mountTablePrefix="fs.viewfs.mounttable.default."{}}}. However, it just 
so happens that the name of the configuration users use to specify the default 
mount table is {{{}fs.viewfs.mounttable.default.name.key{}}}. Thus, if a user 
specifies the default mount table and uses InodeTree the {{name.key}} would be 
falsely parsed as the entry point to one of the mount tables, which would cause 
{{InodeTree}} to throw an exception since {{name.key}} is not a valid entry.
h2. Stack trace:
java.lang.RuntimeException: java.io.IOException: ViewFs: Cannot initialize: 
Invalid entry in Mount table in config: name.keyat 
org.apache.hadoop.fs.FileContext.getFileContext(FileContext.java:470)at 
org.apache.hadoop.fs.viewfs.ViewFsTestSetup.setupForViewFsLocalFs(ViewFsTestSetup.java:88)
at 
org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs.setUp(TestFcMainOperationsLocalFs.java:38)
h2. How to reproduce:

(1) Set {{fs.viewfs.mounttable.default.name.key}} to {{default}}
(2) Run test 
{{org.apache.hadoop.fs.viewfs.TestFcMainOperationsLocalFs#testGlobStatusWithMultipleWildCardMatches}}

You can use the reproduce.sh in the attachment to easily reproduce the bug:

We are happy to provide a patch if this issue is confirmed. 

{{}}



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[GitHub] [hadoop] hadoop-yetus commented on pull request #5840: HDFS-16911. Distcp with snapshot diff to support Ozone filesystem.

2023-07-14 Thread via GitHub


hadoop-yetus commented on PR #5840:
URL: https://github.com/apache/hadoop/pull/5840#issuecomment-1635821574

   :confetti_ball: **+1 overall**
   
   
   
   
   
   
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 |  hadoop-tools/hadoop-distcp: The patch generated 3 new + 26 unchanged - 0 
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[GitHub] [hadoop] hadoop-yetus commented on pull request #5839: HDFS-13916. Distcp SnapshotDiff to support WebHDFS.

2023-07-14 Thread via GitHub


hadoop-yetus commented on PR #5839:
URL: https://github.com/apache/hadoop/pull/5839#issuecomment-1635812415

   :confetti_ball: **+1 overall**
   
   
   
   
   
   
   | Vote | Subsystem | Runtime |  Logfile | Comment |
   |::|--:|:|::|:---:|
   | +0 :ok: |  reexec  |  11m  8s |  |  Docker mode activated.  |
    _ Prechecks _ |
   | +1 :green_heart: |  dupname  |   0m  0s |  |  No case conflicting files 
found.  |
   | +0 :ok: |  codespell  |   0m  0s |  |  codespell was not available.  |
   | +0 :ok: |  detsecrets  |   0m  0s |  |  detect-secrets was not available.  
|
   | +1 :green_heart: |  @author  |   0m  0s |  |  The patch does not contain 
any @author tags.  |
   | +1 :green_heart: |  test4tests  |   0m  0s |  |  The patch appears to 
include 1 new or modified test files.  |
    _ branch-3.3 Compile Tests _ |
   | +1 :green_heart: |  mvninstall  |  53m 32s |  |  branch-3.3 passed  |
   | +1 :green_heart: |  compile  |   0m 28s |  |  branch-3.3 passed  |
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when building and testing our client artifacts.  |
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   | +1 :green_heart: |  mvninstall  |   0m 31s |  |  the patch passed  |
   | +1 :green_heart: |  compile  |   0m 22s |  |  the patch passed  |
   | +1 :green_heart: |  javac  |   0m 22s |  |  the patch passed  |
   | +1 :green_heart: |  blanks  |   0m  0s |  |  The patch has no blanks 
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   | +1 :green_heart: |  unit  |  16m 24s |  |  hadoop-distcp in the patch 
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[GitHub] [hadoop] haiyang1987 opened a new pull request, #5842: HDFS-17086. Fix the parameter settings in TestDiskspaceQuotaUpdate#updateCountForQuota

2023-07-14 Thread via GitHub


haiyang1987 opened a new pull request, #5842:
URL: https://github.com/apache/hadoop/pull/5842

   ### Description of PR
   https://issues.apache.org/jira/browse/HDFS-17086
   
   Fix the parameter settings in TestDiskspaceQuotaUpdate#updateCountForQuota


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[GitHub] [hadoop] harris233 commented on pull request #5807: HDFS-17080. fix ec connection leak

2023-07-14 Thread via GitHub


harris233 commented on PR #5807:
URL: https://github.com/apache/hadoop/pull/5807#issuecomment-1635716182

   > Approved. Please following the guide of email from ASF. Thanks.
   
   Thanks, I have successfully applied


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[GitHub] [hadoop] haiyang1987 commented on a diff in pull request #5823: HDFS-17075. Reconfig disk balancer parameters for datanode

2023-07-14 Thread via GitHub


haiyang1987 commented on code in PR #5823:
URL: https://github.com/apache/hadoop/pull/5823#discussion_r1263602582


##
hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/DataNode.java:
##
@@ -951,6 +960,45 @@ private String reconfDfsUsageParameters(String property, 
String newVal)
 }
   }
 
+  private String reconfDiskBalancerParameters(String property, String newVal)
+  throws ReconfigurationException {
+String result = null;
+try {
+  LOG.info("Reconfiguring {} to {}", property, newVal);
+  if (property.equals(DFS_DISK_BALANCER_ENABLED)) {
+if (newVal != null && !newVal.equalsIgnoreCase("true")
+&& !newVal.equalsIgnoreCase("false")) {
+  throw new IllegalArgumentException("Not a valid Boolean value for " 
+ property +
+  " in reconfDiskBalancerParameters");
+}
+boolean enable = (newVal == null ? DFS_DISK_BALANCER_ENABLED_DEFAULT :
+Boolean.parseBoolean(newVal));

Review Comment:
   Hi Sir, the addition of this check is intended to consider the case where 
newVal is null.



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[GitHub] [hadoop] haiyang1987 commented on pull request #5834: HDFS-17082. Add documentation for provisionSnapshotTrash command to HDFSCommands.md and HdfsSnapshots.md"

2023-07-14 Thread via GitHub


haiyang1987 commented on PR #5834:
URL: https://github.com/apache/hadoop/pull/5834#issuecomment-1635648022

   
   Thanks @ayushtkn @slfan1989  help review and merge it.
   
   


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[GitHub] [hadoop] haiyang1987 commented on pull request #5833: HDFS-17081. Append ec file check if a block is replicated to at least the minimum replication need consider striped block

2023-07-14 Thread via GitHub


haiyang1987 commented on PR #5833:
URL: https://github.com/apache/hadoop/pull/5833#issuecomment-1635646287

   Thanks @ayushtkn help review and merge it.


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[GitHub] [hadoop] haiyang1987 commented on pull request #5823: HDFS-17075. Reconfig disk balancer parameters for datanode

2023-07-14 Thread via GitHub


haiyang1987 commented on PR #5823:
URL: https://github.com/apache/hadoop/pull/5823#issuecomment-1635644518

   Thanks @ayushtkn help me review, i will update it later.


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[GitHub] [hadoop] slfan1989 opened a new pull request, #5841: YARN-11531. [Federation] Code cleanup for NodeManager#amrmproxy.

2023-07-14 Thread via GitHub


slfan1989 opened a new pull request, #5841:
URL: https://github.com/apache/hadoop/pull/5841

   
   
   ### Description of PR
   JIRA: YARN-11531. [Federation] Code cleanup for NodeManager#amrmproxy.
   
   ### How was this patch tested?
   
   
   ### For code changes:
   
   - [ ] Does the title or this PR starts with the corresponding JIRA issue id 
(e.g. 'HADOOP-17799. Your PR title ...')?
   - [ ] Object storage: have the integration tests been executed and the 
endpoint declared according to the connector-specific documentation?
   - [ ] If adding new dependencies to the code, are these dependencies 
licensed in a way that is compatible for inclusion under [ASF 
2.0](http://www.apache.org/legal/resolved.html#category-a)?
   - [ ] If applicable, have you updated the `LICENSE`, `LICENSE-binary`, 
`NOTICE-binary` files?
   
   


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[GitHub] [hadoop] sadanand48 opened a new pull request, #5840: HDFS-16911. Distcp with snapshot diff to support Ozone filesystem.

2023-07-14 Thread via GitHub


sadanand48 opened a new pull request, #5840:
URL: https://github.com/apache/hadoop/pull/5840

   ### Description of PR
   Backport of HDFS-16911 into branch-3.3
   
   ### How was this patch tested?
   Unit tests


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[GitHub] [hadoop] sadanand48 opened a new pull request, #5839: HDFS-13916. Distcp SnapshotDiff to support WebHDFS.

2023-07-14 Thread via GitHub


sadanand48 opened a new pull request, #5839:
URL: https://github.com/apache/hadoop/pull/5839

   ### Description of PR
   Backport of change HDFS-13916  into branch-3.3
   
   ### How was this patch tested?
   Unit tests.


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[jira] [Commented] (HADOOP-18291) S3A prefetch - Implement LRU cache for SingleFilePerBlockCache

2023-07-14 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18291?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17743069#comment-17743069
 ] 

ASF GitHub Bot commented on HADOOP-18291:
-

steveloughran merged PR #5754:
URL: https://github.com/apache/hadoop/pull/5754




> S3A prefetch - Implement LRU cache for SingleFilePerBlockCache
> --
>
> Key: HADOOP-18291
> URL: https://issues.apache.org/jira/browse/HADOOP-18291
> Project: Hadoop Common
>  Issue Type: Sub-task
>Affects Versions: 3.4.0
>Reporter: Ahmar Suhail
>Assignee: Viraj Jasani
>Priority: Major
>  Labels: pull-request-available
>
> Currently there is no limit on the size of disk cache. This means we could 
> have a large number of files on files, especially for access patterns that 
> are very random and do not always read the block fully. 
>  
> eg:
> in.seek(5);
> in.read(); 
> in.seek(blockSize + 10) // block 0 gets saved to disk as it's not fully read
> in.read();
> in.seek(2 * blockSize + 10) // block 1 gets saved to disk
> .. and so on
>  
> The in memory cache is bounded, and by default has a limit of 72MB (9 
> blocks). When a block is fully read, and a seek is issued it's released 
> [here|https://github.com/apache/hadoop/blob/feature-HADOOP-18028-s3a-prefetch/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/read/S3CachingInputStream.java#L109].
>  We can also delete the on disk file for the block here if it exists. 
>  
> Also maybe add an upper limit on disk space, and delete the file which stores 
> data of the block furthest from the current block (similar to the in memory 
> cache) when this limit is reached. 



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[GitHub] [hadoop] steveloughran merged pull request #5754: HADOOP-18291. S3A prefetch - Implement thread-safe LRU cache for SingleFilePerBlockCache

2023-07-14 Thread via GitHub


steveloughran merged PR #5754:
URL: https://github.com/apache/hadoop/pull/5754


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[GitHub] [hadoop] ayushtkn commented on a diff in pull request #5823: HDFS-17075. Reconfig disk balancer parameters for datanode

2023-07-14 Thread via GitHub


ayushtkn commented on code in PR #5823:
URL: https://github.com/apache/hadoop/pull/5823#discussion_r1263492781


##
hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/DataNode.java:
##
@@ -951,6 +960,45 @@ private String reconfDfsUsageParameters(String property, 
String newVal)
 }
   }
 
+  private String reconfDiskBalancerParameters(String property, String newVal)
+  throws ReconfigurationException {
+String result = null;
+try {
+  LOG.info("Reconfiguring {} to {}", property, newVal);
+  if (property.equals(DFS_DISK_BALANCER_ENABLED)) {
+if (newVal != null && !newVal.equalsIgnoreCase("true")
+&& !newVal.equalsIgnoreCase("false")) {
+  throw new IllegalArgumentException("Not a valid Boolean value for " 
+ property +
+  " in reconfDiskBalancerParameters");

Review Comment:
   this isn't required
   ```
   " in reconfDiskBalancerParameters"
   ```



##
hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/DataNode.java:
##
@@ -4201,7 +4249,7 @@ public List getVolumeReport() throws 
IOException {
 return volumeInfoList;
   }
 
-  private DiskBalancer getDiskBalancer() throws IOException {
+  public DiskBalancer getDiskBalancer() throws IOException {

Review Comment:
   Add   ```@VisibleForTesting```



##
hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/DataNode.java:
##
@@ -951,6 +960,45 @@ private String reconfDfsUsageParameters(String property, 
String newVal)
 }
   }
 
+  private String reconfDiskBalancerParameters(String property, String newVal)
+  throws ReconfigurationException {
+String result = null;
+try {
+  LOG.info("Reconfiguring {} to {}", property, newVal);
+  if (property.equals(DFS_DISK_BALANCER_ENABLED)) {
+if (newVal != null && !newVal.equalsIgnoreCase("true")
+&& !newVal.equalsIgnoreCase("false")) {
+  throw new IllegalArgumentException("Not a valid Boolean value for " 
+ property +
+  " in reconfDiskBalancerParameters");
+}
+boolean enable = (newVal == null ? DFS_DISK_BALANCER_ENABLED_DEFAULT :
+Boolean.parseBoolean(newVal));

Review Comment:
   this is a redundant check, earlier above we already did checks to figure out 
whether it is true/false, should have done check once and saved the value above 
only



##
hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/DiskBalancer.java:
##
@@ -341,6 +341,59 @@ private void checkDiskBalancerEnabled()
 }
   }
 
+  /**
+   * Sets Disk balancer is to enable or not to enable.
+   *
+   * @param diskBalancerEnabled
+   *  true, enable diskBalancer, otherwise false to disable it.
+   */
+  public void setDiskBalancerEnabled(boolean diskBalancerEnabled) {
+isDiskBalancerEnabled = diskBalancerEnabled;
+  }
+
+  /**
+   * Returns the value indicating if diskBalancer is enabled.
+   *
+   * @return boolean.
+   */
+  @VisibleForTesting
+  public boolean isDiskBalancerEnabled() {
+return isDiskBalancerEnabled;
+  }
+
+  /**
+   * Sets maximum amount of time disk balancer plan is valid.
+   *
+   * @param planValidityInterval

Review Comment:
   add description for the param



##
hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/DiskBalancer.java:
##
@@ -341,6 +341,59 @@ private void checkDiskBalancerEnabled()
 }
   }
 
+  /**
+   * Sets Disk balancer is to enable or not to enable.
+   *
+   * @param diskBalancerEnabled
+   *  true, enable diskBalancer, otherwise false to disable it.
+   */
+  public void setDiskBalancerEnabled(boolean diskBalancerEnabled) {
+isDiskBalancerEnabled = diskBalancerEnabled;
+  }
+
+  /**
+   * Returns the value indicating if diskBalancer is enabled.
+   *
+   * @return boolean.
+   */
+  @VisibleForTesting
+  public boolean isDiskBalancerEnabled() {
+return isDiskBalancerEnabled;
+  }
+
+  /**
+   * Sets maximum amount of time disk balancer plan is valid.
+   *
+   * @param planValidityInterval
+   */
+  public void setPlanValidityInterval(long planValidityInterval) {
+
this.config.setTimeDuration(DFSConfigKeys.DFS_DISK_BALANCER_PLAN_VALID_INTERVAL,
+planValidityInterval, TimeUnit.MILLISECONDS);
+this.planValidityInterval = planValidityInterval;
+  }
+
+  /**
+   * Gets maximum amount of time disk balancer plan is valid, then 
milliseconds is assumed.
+   *
+   * @return long

Review Comment:
   it returns ``plan validity interval``, rather than putting the return type 
add description



##
hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/DiskBalancer.java:
##
@@ -341,6 +341,59 @@ private void checkDiskBalancerEnabled()
 }
   }
 
+  /**
+   * Sets Disk balancer is to enable or not to enable.
+   *
+   * 

[GitHub] [hadoop] hadoop-yetus commented on pull request #5838: fix MAPREDUCE-7442. Fix exception message is not intusive when accessing the job configuration web UI

2023-07-14 Thread via GitHub


hadoop-yetus commented on PR #5838:
URL: https://github.com/apache/hadoop/pull/5838#issuecomment-1635539975

   :broken_heart: **-1 overall**
   
   
   
   
   
   
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[GitHub] [hadoop] symious commented on pull request #5835: HDFS-17084. Utilize StringTable for numerable XAttributes

2023-07-14 Thread via GitHub


symious commented on PR #5835:
URL: https://github.com/apache/hadoop/pull/5835#issuecomment-1635539770

   @jojochuang @ferhui Could you help to review this PR?


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[GitHub] [hadoop] hadoop-yetus commented on pull request #5835: HDFS-17084. Utilize StringTable for numerable XAttributes

2023-07-14 Thread via GitHub


hadoop-yetus commented on PR #5835:
URL: https://github.com/apache/hadoop/pull/5835#issuecomment-1635537811

   :confetti_ball: **+1 overall**
   
   
   
   
   
   
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[GitHub] [hadoop] hfutatzhanghb commented on pull request #5597: HDFS-16993. Datanode supports configure TopN DatanodeNetworkCounts

2023-07-14 Thread via GitHub


hfutatzhanghb commented on PR #5597:
URL: https://github.com/apache/hadoop/pull/5597#issuecomment-1635378755

   > @hfutatzhanghb try writing a minimal test, even if it fails due to same 
ip, I can try help fixing it from there
   
   @ayushtkn Thanx sir.  Will write an unit test soonly.


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[GitHub] [hadoop] ayushtkn commented on pull request #5597: HDFS-16993. Datanode supports configure TopN DatanodeNetworkCounts

2023-07-14 Thread via GitHub


ayushtkn commented on PR #5597:
URL: https://github.com/apache/hadoop/pull/5597#issuecomment-1635373215

   @hfutatzhanghb try writing a minimal test, even if it fails due to same ip, 
I can try help fixing it from there


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[GitHub] [hadoop] ayushtkn commented on pull request #5809: HDFS-17068. Datanode should record last directory scan time.

2023-07-14 Thread via GitHub


ayushtkn commented on PR #5809:
URL: https://github.com/apache/hadoop/pull/5809#issuecomment-1635349696

   @Hexiaoqiao any further comments, planning to hold for you a couple of days


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[GitHub] [hadoop] liangyu-1 opened a new pull request, #5838: fix MAPREDUCE-7442. Fix exception message is not intusive when accessing the job configuration web UI

2023-07-14 Thread via GitHub


liangyu-1 opened a new pull request, #5838:
URL: https://github.com/apache/hadoop/pull/5838

   
   
   ### Description of PR
   fix the bug is issue 
[MAPREDUCE-7442](https://issues.apache.org/jira/browse/MAPREDUCE-7442)
   this PR fix the bug that exception message is not intusive when accessing 
the job configuration web UI.
   
   ### How was this patch tested?
   I rebuild the project, and restart our own Hadoop cluster, then we can the 
exception message on the webpage of the job configuration, and here is the 
picture:
   
![image](https://github.com/apache/hadoop/assets/62563545/7fb5f9ab-b839-4535-9684-792ea7449760)
   
   
   ### For code changes:
   
   I changed the file

hadoop/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-app/src/main/java/org/apache/hadoop/mapreduce/v2/app/webapp/ConfBlock.java,
 line116.
   
   - [ ] Does the title or this PR starts with the corresponding JIRA issue id 
(e.g. 'HADOOP-17799. Your PR title ...')?
   - [ ] Object storage: have the integration tests been executed and the 
endpoint declared according to the connector-specific documentation?
   - [ ] If adding new dependencies to the code, are these dependencies 
licensed in a way that is compatible for inclusion under [ASF 
2.0](http://www.apache.org/legal/resolved.html#category-a)?
   - [ ] If applicable, have you updated the `LICENSE`, `LICENSE-binary`, 
`NOTICE-binary` files?
   
   


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[GitHub] [hadoop] ayushtkn merged pull request #5833: HDFS-17081. Append ec file check if a block is replicated to at least the minimum replication need consider striped block

2023-07-14 Thread via GitHub


ayushtkn merged PR #5833:
URL: https://github.com/apache/hadoop/pull/5833


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[GitHub] [hadoop] ayushtkn merged pull request #5836: HDFS-17083. Support getErasureCodeCodecs API in WebHDFS

2023-07-14 Thread via GitHub


ayushtkn merged PR #5836:
URL: https://github.com/apache/hadoop/pull/5836


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