[jira] [Commented] (HADOOP-18840) Add enQueue time to RpcMetrics

2023-08-08 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18840?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17752283#comment-17752283
 ] 

ASF GitHub Bot commented on HADOOP-18840:
-

xinglin commented on PR #5926:
URL: https://github.com/apache/hadoop/pull/5926#issuecomment-1670753258

   > > @2005hithlj Please check the failed unit test and checkstyle.
   > 
   > @Hexiaoqiao sir. The failed UT 'TestRPCCallBenchmark is not related to my 
modification, and it will success in my modification branch in my local env.
   > 
   > And Checkstyle Warn: RpcMetrics.java:122: @Metric("EQueue time") 
MutableRate rpcEnQueueTime;:38: Variable 'rpcEnQueueTime' must be private and 
have accessor methods. [VisibilityModifier] RpcMetrics.java:123: 
MutableQuantiles[] rpcEnQueueTimeQuantiles;:22: Variable 
'rpcEnQueueTimeQuantiles' must be private and have accessor methods. 
[VisibilityModifier]
   > 
   > If I follow the above prompts to modify, it will break the style of the 
RpcMetrics class.
   
   I don't know the unit test but yeah, for the checkstyle, we can ignore these 
warnings: for metrics, we don't add visibility modifier. None of the existing 
metrics has the visibility modifier.




> Add enQueue time to RpcMetrics
> --
>
> Key: HADOOP-18840
> URL: https://issues.apache.org/jira/browse/HADOOP-18840
> Project: Hadoop Common
>  Issue Type: Improvement
>  Components: rpc-server
>Reporter: Liangjun He
>Assignee: Liangjun He
>Priority: Minor
>  Labels: pull-request-available
>
> Sometimes, the request time observed by the client is much longer than the 
> queue + process time on the RPC server. Perhaps the RPC request 'waiting 
> enQueue' took too long on the RPC server, so we should add enQueue time to 
> RpcMetrics.



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[GitHub] [hadoop] xinglin commented on pull request #5926: HADOOP-18840. Add enQueue time to RpcMetrics

2023-08-08 Thread via GitHub


xinglin commented on PR #5926:
URL: https://github.com/apache/hadoop/pull/5926#issuecomment-1670753258

   > > @2005hithlj Please check the failed unit test and checkstyle.
   > 
   > @Hexiaoqiao sir. The failed UT 'TestRPCCallBenchmark is not related to my 
modification, and it will success in my modification branch in my local env.
   > 
   > And Checkstyle Warn: RpcMetrics.java:122: @Metric("EQueue time") 
MutableRate rpcEnQueueTime;:38: Variable 'rpcEnQueueTime' must be private and 
have accessor methods. [VisibilityModifier] RpcMetrics.java:123: 
MutableQuantiles[] rpcEnQueueTimeQuantiles;:22: Variable 
'rpcEnQueueTimeQuantiles' must be private and have accessor methods. 
[VisibilityModifier]
   > 
   > If I follow the above prompts to modify, it will break the style of the 
RpcMetrics class.
   
   I don't know the unit test but yeah, for the checkstyle, we can ignore these 
warnings: for metrics, we don't add visibility modifier. None of the existing 
metrics has the visibility modifier.


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[GitHub] [hadoop] xinglin commented on pull request #5878: HDFS-17030 Limit wait time for getHAServiceState in ObserverReadProxyProvider

2023-08-08 Thread via GitHub


xinglin commented on PR #5878:
URL: https://github.com/apache/hadoop/pull/5878#issuecomment-1670751349

   > > Hi @goiri,
   > > could you take a look at this backport PR for branch-3.3 as well? thanks,
   > 
   > You'd have to put a separate PR together I'd say.
   
   I am confused: this is a separate PR, right?


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[GitHub] [hadoop] xinglin commented on a diff in pull request #5878: HDFS-17030 Limit wait time for getHAServiceState in ObserverReadProxyProvider

2023-08-08 Thread via GitHub


xinglin commented on code in PR #5878:
URL: https://github.com/apache/hadoop/pull/5878#discussion_r1288010220


##
hadoop-hdfs-project/hadoop-hdfs-client/src/main/java/org/apache/hadoop/hdfs/server/namenode/ha/ObserverReadProxyProvider.java:
##
@@ -285,13 +323,67 @@ private synchronized NNProxyInfo 
changeProxy(NNProxyInfo initial) {
 }
 currentIndex = (currentIndex + 1) % nameNodeProxies.size();
 currentProxy = createProxyIfNeeded(nameNodeProxies.get(currentIndex));
-currentProxy.setCachedState(getHAServiceState(currentProxy));
+currentProxy.setCachedState(getHAServiceStateWithTimeout(currentProxy));
 LOG.debug("Changed current proxy from {} to {}",
 initial == null ? "none" : initial.proxyInfo,
 currentProxy.proxyInfo);
 return currentProxy;
   }
 
+  /**
+   * Execute getHAServiceState() call with a timeout, to avoid a long wait when
+   * an NN becomes irresponsive to rpc requests
+   * (when a thread/heap dump is being taken, e.g.).
+   *
+   * For each getHAServiceState() call, a task is created and submitted to a
+   * threadpool for execution. We will wait for a response up to
+   * namenodeHAStateProbeTimeoutSec and cancel these requests if they time out.
+   *
+   * The implementation is split into two functions so that we can unit test
+   * the second function.
+   */
+  HAServiceState getHAServiceStateWithTimeout(final NNProxyInfo proxyInfo) {
+Callable getHAServiceStateTask = () -> 
getHAServiceState(proxyInfo);
+
+try {
+  Future task =
+  nnProbingThreadPool.submit(getHAServiceStateTask);

Review Comment:
   fixed. fits in one line with 100 characters. So, did not bother splitting 
into two lines.



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[GitHub] [hadoop] xinglin commented on a diff in pull request #5878: HDFS-17030 Limit wait time for getHAServiceState in ObserverReadProxyProvider

2023-08-08 Thread via GitHub


xinglin commented on code in PR #5878:
URL: https://github.com/apache/hadoop/pull/5878#discussion_r1288009483


##
hadoop-hdfs-project/hadoop-hdfs-client/src/main/java/org/apache/hadoop/hdfs/server/namenode/ha/ObserverReadProxyProvider.java:
##
@@ -285,13 +323,67 @@ private synchronized NNProxyInfo 
changeProxy(NNProxyInfo initial) {
 }
 currentIndex = (currentIndex + 1) % nameNodeProxies.size();
 currentProxy = createProxyIfNeeded(nameNodeProxies.get(currentIndex));
-currentProxy.setCachedState(getHAServiceState(currentProxy));
+currentProxy.setCachedState(getHAServiceStateWithTimeout(currentProxy));
 LOG.debug("Changed current proxy from {} to {}",
 initial == null ? "none" : initial.proxyInfo,
 currentProxy.proxyInfo);
 return currentProxy;
   }
 
+  /**
+   * Execute getHAServiceState() call with a timeout, to avoid a long wait when
+   * an NN becomes irresponsive to rpc requests
+   * (when a thread/heap dump is being taken, e.g.).
+   *
+   * For each getHAServiceState() call, a task is created and submitted to a
+   * threadpool for execution. We will wait for a response up to
+   * namenodeHAStateProbeTimeoutSec and cancel these requests if they time out.
+   *
+   * The implementation is split into two functions so that we can unit test
+   * the second function.
+   */
+  HAServiceState getHAServiceStateWithTimeout(final NNProxyInfo proxyInfo) {
+Callable getHAServiceStateTask = () -> 
getHAServiceState(proxyInfo);
+
+try {
+  Future task =
+  nnProbingThreadPool.submit(getHAServiceStateTask);
+  return getHAServiceStateWithTimeout(proxyInfo, task);
+} catch (RejectedExecutionException e) {
+  LOG.warn("Run out of threads to submit the request to query HA state. "
+  + "Ok to return null and we will fallback to use active NN to serve "
+  + "this request.");
+  return null;
+}
+  }
+
+  HAServiceState getHAServiceStateWithTimeout(final NNProxyInfo proxyInfo,
+  Future task) {
+HAServiceState state = null;
+try {
+  if (namenodeHAStateProbeTimeoutMs > 0) {
+state = task.get(namenodeHAStateProbeTimeoutMs, TimeUnit.MILLISECONDS);
+  } else {
+// Disable timeout by waiting indefinitely when 
namenodeHAStateProbeTimeoutSec is set to 0
+// or a negative value.
+state = task.get();
+  }
+  LOG.debug("HA State for {} is {}", proxyInfo.proxyInfo, state);
+} catch (TimeoutException e) {
+  // Cancel the task on timeout
+  String msg = String.format("Cancel NN probe task due to timeout for %s", 
proxyInfo.proxyInfo);
+  LOG.warn(msg, e);
+  if (task != null) {

Review Comment:
   removed.



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[GitHub] [hadoop] anujmodi2021 commented on pull request #5909: Hadoop 18826: [ABFS] Fix for Empty Relative Path Issue Leading to GetFileStatus("/") failure.

2023-08-08 Thread via GitHub


anujmodi2021 commented on PR #5909:
URL: https://github.com/apache/hadoop/pull/5909#issuecomment-1670620744

   > merged, doing a backport
   
   Thanks a lot Steve...


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[jira] [Commented] (HADOOP-18840) Add enQueue time to RpcMetrics

2023-08-08 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18840?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17752231#comment-17752231
 ] 

ASF GitHub Bot commented on HADOOP-18840:
-

2005hithlj commented on PR #5926:
URL: https://github.com/apache/hadoop/pull/5926#issuecomment-1670549206

   > @2005hithlj Please check the failed unit test and checkstyle.
   
   @Hexiaoqiao sir.
   The failed UT 'TestRPCCallBenchmark is not related to my modification, and 
it will success in my modification branch in my local env.
   
   And Checkstyle Warn:
   RpcMetrics.java:122:  @Metric("EQueue time") MutableRate rpcEnQueueTime;:38: 
Variable 'rpcEnQueueTime' must be private and have accessor methods. 
[VisibilityModifier]
   RpcMetrics.java:123:  MutableQuantiles[] rpcEnQueueTimeQuantiles;:22: 
Variable 'rpcEnQueueTimeQuantiles' must be private and have accessor methods. 
[VisibilityModifier]
   
   If I follow the above prompts to modify, it will break the style of the 
RpcMetrics class.
   
   
   




> Add enQueue time to RpcMetrics
> --
>
> Key: HADOOP-18840
> URL: https://issues.apache.org/jira/browse/HADOOP-18840
> Project: Hadoop Common
>  Issue Type: Improvement
>  Components: rpc-server
>Reporter: Liangjun He
>Assignee: Liangjun He
>Priority: Minor
>  Labels: pull-request-available
>
> Sometimes, the request time observed by the client is much longer than the 
> queue + process time on the RPC server. Perhaps the RPC request 'waiting 
> enQueue' took too long on the RPC server, so we should add enQueue time to 
> RpcMetrics.



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[GitHub] [hadoop] 2005hithlj commented on pull request #5926: HADOOP-18840. Add enQueue time to RpcMetrics

2023-08-08 Thread via GitHub


2005hithlj commented on PR #5926:
URL: https://github.com/apache/hadoop/pull/5926#issuecomment-1670549206

   > @2005hithlj Please check the failed unit test and checkstyle.
   
   @Hexiaoqiao sir.
   The failed UT 'TestRPCCallBenchmark is not related to my modification, and 
it will success in my modification branch in my local env.
   
   And Checkstyle Warn:
   RpcMetrics.java:122:  @Metric("EQueue time") MutableRate rpcEnQueueTime;:38: 
Variable 'rpcEnQueueTime' must be private and have accessor methods. 
[VisibilityModifier]
   RpcMetrics.java:123:  MutableQuantiles[] rpcEnQueueTimeQuantiles;:22: 
Variable 'rpcEnQueueTimeQuantiles' must be private and have accessor methods. 
[VisibilityModifier]
   
   If I follow the above prompts to modify, it will break the style of the 
RpcMetrics class.
   
   
   


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[jira] [Resolved] (HADOOP-18826) abfs getFileStatus(/) fails with "Value for one of the query parameters specified in the request URI is invalid.", 400

2023-08-08 Thread Steve Loughran (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18826?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Steve Loughran resolved HADOOP-18826.
-
Fix Version/s: 3.4.0
   3.3.9
   Resolution: Fixed

> abfs getFileStatus(/) fails with "Value for one of the query parameters 
> specified in the request URI is invalid.", 400
> --
>
> Key: HADOOP-18826
> URL: https://issues.apache.org/jira/browse/HADOOP-18826
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: fs/azure
>Affects Versions: 3.3.1, 3.3.2, 3.3.5, 3.3.3, 3.3.4, 3.3.6
>Reporter: Sergey Shabalov
>Assignee: Anuj Modi
>Priority: Major
> Fix For: 3.4.0, 3.3.9
>
> Attachments: test_hadoop-azure-3_3_1-FileSystem_getFileStatus - 
> Copy.zip
>
>
> I am using hadoop-azure-3.3.0.jar and have written code:
> {code:java}
> static final String ROOT_DIR = 
> "abfs://ssh-test...@sshadlsgen2.dfs.core.windows.net",
> Configuration config = new Configuration();        
> config.set("fs.defaultFS",ROOT_DIR);        
> config.set("fs.adl.oauth2.access.token.provider.type","ClientCredential");    
>     config.set("fs.adl.oauth2.client.id","");        
> config.set("fs.adl.oauth2.credential","");        
> config.set("fs.adl.oauth2.refresh.url","");        
> config.set("fs.azure.account.key.sshadlsgen2.dfs.core.windows.net",ACCESS_TOKEN);
>         
> config.set("fs.azure.skipUserGroupMetadataDuringInitialization","true");
>   FileSystem fs = FileSystem.get(config);
>   System.out.println( "\nfs:'"+fs.toString()+"'");
>   FileStatus status = fs.getFileStatus(new Path(ROOT_DIR)); // !!! 
> Exception in 3.3.1-*
>   System.out.println( "\nstatus:'"+status.toString()+"'");
>  {code}
> It did work properly till 3.3.1. 
> But in 3.3.1 it fails with exception:
> {code:java}
> Caused by: Operation failed: "Value for one of the query parameters specified 
> in the request URI is invalid.", 400, HEAD, 
> https://sshadlsgen2.dfs.core.windows.net/ssh-test-fs?upn=false&action=getAccessControl&timeout=90
>   at 
> org.apache.hadoop.fs.azurebfs.services.AbfsRestOperation.completeExecute(AbfsRestOperation.java:218)
>  at 
> org.apache.hadoop.fs.azurebfs.services.AbfsRestOperation.lambda$execute$0(AbfsRestOperation.java:181)
>  at 
> org.apache.hadoop.fs.statistics.impl.IOStatisticsBinding.measureDurationOfInvocation(IOStatisticsBinding.java:494)
>  at 
> org.apache.hadoop.fs.statistics.impl.IOStatisticsBinding.trackDurationOfInvocation(IOStatisticsBinding.java:465)
>  at 
> org.apache.hadoop.fs.azurebfs.services.AbfsRestOperation.execute(AbfsRestOperation.java:179)
>  at 
> org.apache.hadoop.fs.azurebfs.services.AbfsClient.getAclStatus(AbfsClient.java:942)
>  at 
> org.apache.hadoop.fs.azurebfs.services.AbfsClient.getAclStatus(AbfsClient.java:924)
>  at 
> org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore.getFileStatus(AzureBlobFileSystemStore.java:846)
>  at 
> org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem.getFileStatus(AzureBlobFileSystem.java:507)
>  {code}
> I performed some research and found:
> In hadoop-azure-3.3.0.jar we see:
> {code:java}
> org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore{
>   ...
>   public FileStatus getFileStatus(final Path path) throws IOException {
>   ...
> Line 604: op = 
> client.getAclStatus(AbfsHttpConstants.FORWARD_SLASH + 
> AbfsHttpConstants.ROOT_PATH);
>   ...
>   }
>   ...
> } {code}
> and this code produces REST request:
> {code:java}
> https://sshadlsgen2.dfs.core.windows.net/ssh-test-fs//?upn=false&action=getAccessControl&timeout=90
>   {code}
> There is finalizes slash in path part 
> "...ssh-test-fs{*}{color:#de350b}//{color}{*}?upn=false..." This request does 
> work properly.
> But since hadoop-azure-3.3.1.jar till latest hadoop-azure-3.3.6.jar we see:
> {code:java}
> org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore {
>   ...
>   public FileStatus getFileStatus(final Path path) throws IOException {
>   ...
>   perfInfo.registerCallee("getAclStatus");
> Line 846:   op = client.getAclStatus(getRelativePath(path));
>   ...
>   }
>   ...
> }
> Line 1492:
> private String getRelativePath(final Path path) {
>   ...
>   return path.toUri().getPath();
> } {code}
> and this code prduces REST request:
> {code:java}
> https://sshadlsgen2.dfs.core.windows.net/ssh-test-fs?upn=false&action=getAccessControl&timeout=90
>  {code}
> There is not finalizes slash in path part "...ssh-test-fs?upn=false..." It 
> happens because the new code "path.toUri().getPath();" produces empty string.
> This request fails with message:
> {code:java}
> Caused by: Operation failed: "Value for one of the 

[GitHub] [hadoop] steveloughran commented on pull request #5909: Hadoop 18826: [ABFS] Fix for Empty Relative Path Issue Leading to GetFileStatus("/") failure.

2023-08-08 Thread via GitHub


steveloughran commented on PR #5909:
URL: https://github.com/apache/hadoop/pull/5909#issuecomment-167001

   merged, doing a backport


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[GitHub] [hadoop] steveloughran merged pull request #5909: Hadoop 18826: [ABFS] Fix for Empty Relative Path Issue Leading to GetFileStatus("/") failure.

2023-08-08 Thread via GitHub


steveloughran merged PR #5909:
URL: https://github.com/apache/hadoop/pull/5909


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[jira] [Commented] (HADOOP-18757) S3A Committer only finalizes the commits in a single thread

2023-08-08 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18757?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17752147#comment-17752147
 ] 

ASF GitHub Bot commented on HADOOP-18757:
-

steveloughran commented on code in PR #5706:
URL: https://github.com/apache/hadoop/pull/5706#discussion_r1287471261


##
hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/commit/impl/CommitContext.java:
##
@@ -236,7 +236,7 @@ private ExecutorService buildThreadPool(
 .setDaemon(true)
 .setNameFormat(THREAD_PREFIX + jobId + "-%d")
 .build();
-return new HadoopThreadPoolExecutor(0, numThreads,
+return new HadoopThreadPoolExecutor(numThreads, numThreads,

Review Comment:
   you are going to have to go with it for now; i think we should be thinking 
about a 3.3.7 before long as we have some other abfs and s3a issues causing 
pain...





> S3A Committer only finalizes the commits in a single thread
> ---
>
> Key: HADOOP-18757
> URL: https://issues.apache.org/jira/browse/HADOOP-18757
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: fs/s3
>Affects Versions: 3.3.5
>Reporter: Moditha Hewasinghage
>Assignee: Moditha Hewasinghage
>Priority: Major
>  Labels: pull-request-available
> Fix For: 3.4.0, 3.3.9
>
>
> S3A Committer is being bottle-necked on the driver when finalizing the 
> commits. It seems like only a single thread is being used to finalize the 
> commit. In the experiment we are saving 36,000 files ending committing for 
> almost 2 hours each file taking 0.1 - 0.5 seconds while all the executors 
> stay idle while the driver commits. I have attached the driver log snippets 
> to support this theory in comparison to spark 3.4.0.
> The most likely reason is the usage of 
> [ThreadPoolExecutor]([https://docs.oracle.com/javase/8/docs/api/java/util/concurrent/ThreadPoolExecutor.html])
>  in 
> [https://github.com/apache/hadoop/blob/706d88266abcee09ed78fbaa0ad5f74d818ab0e9/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/commit/impl/CommitContext.java#L239-L244]
> where an LinkedBlockingQueue is used with a corePoolSize of 0 which ends up 
> with a single thread and no new threads created.
> From the documentation
> {code:java}
> Unbounded queues. Using an unbounded queue (for example a LinkedBlockingQueue 
> without a predefined capacity) will cause new tasks to wait in the queue when 
> all corePoolSize threads are busy. Thus, no more than corePoolSize threads 
> will ever be created. (And the value of the maximumPoolSize therefore doesn't 
> have any effect.) This may be appropriate when each task is completely 
> independent of others, so tasks cannot affect each others execution; for 
> example, in a web page server. While this style of queuing can be useful in 
> smoothing out transient bursts of requests, it admits the possibility of 
> unbounded work queue growth when commands continue to arrive on average 
> faster than they can be processed.{code}
> Magic Committer spark 3.5.0-SNAPSHOT
> {code:java}
> 2023-05-26 15:35:04,852 DEBUG impl.CommitContext: creating thread pool of 
> size 32
> 2023-05-26 15:35:04,922 INFO yarn.YarnAllocator: Driver requested a total 
> number of 0 executor(s) for resource profile id: 0.
> 2023-05-26 15:35:07,910 INFO commit.AbstractS3ACommitter: Starting: 
> committing the output of 36000 task(s)
> 2023-05-26 15:35:07,914 INFO commit.AbstractS3ACommitter: Starting: Loading 
> and committing files in pendingset 
> s3:date=20230520/__magic/job-b9167b1a-35a5-448
> e-8022-31e0f7457354/00/task_202305261454174742717183892533843_0031_m_00.pendingset
> 2023-05-26 15:35:07,941 DEBUG files.PersistentCommitData: Reading commit data 
> from file 
> s3:date=20230520/__magic/job-b9167b1a-35a5-448e-8022-31e0f7457354/00/
> task_202305261454174742717183892533843_0031_m_00.pendingset
> 2023-05-26 15:35:08,036 DEBUG impl.CommitContext: creating thread pool of 
> size 32
> 2023-05-26 15:35:08,037 DEBUG impl.CommitOperations: Committing single commit 
> SinglePendingCommit
> {version=2, 
> uri='s3:date=20230520/__magic/job-b9167b1a-35a5- 
> 448e-8022-31e0f7457354/00/tasks/attempt_202305261454174742717183892533843_0031_m_00_1920855/__base/rawRequestType=imp_dsp/part-0-b196e04e-c87b-43e1-97e0-7ad34ef0bedf.c000.zstd.parquet',
>  
> destination='/date=20230520/rawRequestType=imp_dsp/part-0-b196e04e-c87b-43e1-97e0-7ad34ef0bedf.c000.zstd.parquet',
>  
> uploadId='SCp78J9aYOmnPwrtfd5a.Q6B9Zu6olQw3eZcpyt.W.BCu6.M6fz54nlTe2ZYUDicSskFgPocsjlVXAbfiPn3Xu
>  26MzXNdWcg5j_kBGg9iWpeoWh4K21gt7bbKetML95MXAck15yP.VGFeOleoAspUg--', 
> created=1685113555232, saved=1685113555232, size=110636173, date='Fri May 26 
> 15:05:55 UTC 2023', jobId='b9167b1a-35a5-448e-8022-3

[GitHub] [hadoop] steveloughran commented on a diff in pull request #5706: HADOOP-18757: Bump corePoolSize of HadoopThreadPoolExecutor in s3a committer

2023-08-08 Thread via GitHub


steveloughran commented on code in PR #5706:
URL: https://github.com/apache/hadoop/pull/5706#discussion_r1287471261


##
hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/commit/impl/CommitContext.java:
##
@@ -236,7 +236,7 @@ private ExecutorService buildThreadPool(
 .setDaemon(true)
 .setNameFormat(THREAD_PREFIX + jobId + "-%d")
 .build();
-return new HadoopThreadPoolExecutor(0, numThreads,
+return new HadoopThreadPoolExecutor(numThreads, numThreads,

Review Comment:
   you are going to have to go with it for now; i think we should be thinking 
about a 3.3.7 before long as we have some other abfs and s3a issues causing 
pain...



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[GitHub] [hadoop-thirdparty] fredbalves86 commented on pull request #23: HADOOP-18843. Guava version 32.0.1 bump to fix CVE-2023-2976

2023-08-08 Thread via GitHub


fredbalves86 commented on PR #23:
URL: https://github.com/apache/hadoop-thirdparty/pull/23#issuecomment-1670048204

   @jojochuang Done.


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[jira] [Updated] (HADOOP-18838) Some fs.s3a.* config values are different in sources and documentation

2023-08-08 Thread Steve Loughran (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18838?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Steve Loughran updated HADOOP-18838:

Priority: Minor  (was: Major)

> Some fs.s3a.* config values are different in sources and documentation
> --
>
> Key: HADOOP-18838
> URL: https://issues.apache.org/jira/browse/HADOOP-18838
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: documentation, fs/s3
>Affects Versions: 3.3.6
>Reporter: Maxim Martynov
>Priority: Minor
>
> For config option {{fs.s3a.retry.throttle.interval}} default value in source 
> code is {{500ms}}:
> {code:java}
> public static final String RETRY_THROTTLE_INTERVAL_DEFAULT = "500ms";
> {code}
> https://github.com/apache/hadoop/blob/rel/release-3.3.6/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/Constants.java#L921
> In {{core-default.xml}} it has value {{100ms}}, but in the description 
> {{500ms}}:
> {code:xml}
> 
>   fs.s3a.retry.throttle.interval
>   100ms
>   
> Initial between retry attempts on throttled requests, +/- 50%. chosen at 
> random.
> i.e. for an intial value of 3000ms, the initial delay would be in the 
> range 1500ms to 4500ms.
> Backoffs are exponential; again randomness is used to avoid the 
> thundering heard problem.
> 500ms is the default value used by the AWS S3 Retry policy.
>   
> 
> {code}
> https://github.com/apache/hadoop/blob/rel/release-3.3.6/hadoop-common-project/hadoop-common/src/main/resources/core-default.xml#L1750
> This change introduced in HADOOP-16823.
> In Hadoop-AWS module documentation it has value {{1000ms}}:
> {code:xml}
> 
>   fs.s3a.retry.throttle.interval
>   1000ms
>   
> Interval between retry attempts on throttled requests.
>   
> 
> {code}
> https://github.com/apache/hadoop/blob/rel/release-3.3.6/hadoop-tools/hadoop-aws/src/site/markdown/tools/hadoop-aws/index.md?plain=1#L1223
> File was created in HADOOP-13786, and value is left unchanged since when.
> In performance tuning page it has up-to-date value {{500ms}}:
> {code:xml}
> 
>   fs.s3a.retry.throttle.interval
>   500ms
>   
> Interval between retry attempts on throttled requests.
>   
> 
> {code}
> https://github.com/apache/hadoop/blob/rel/release-3.3.6/hadoop-tools/hadoop-aws/src/site/markdown/tools/hadoop-aws/performance.md?plain=1#L435
> This change introduced in HADOOP-15076.
> The same issue with:
> * {{fs.s3a.retry.throttle.limit}} - in source code it has value {{20}}, but 
> in some documents still old value ${fs.s3a.attempts.maximum}
> * {{fs.s3a.connection.establish.timeout}} - in source code it has value 
> {{50_000}}, in config file & documentation {{5_000}}
> * {{fs.s3a.attempts.maximum}} - in source code it has value {{10}}, in config 
> file & documentation {{20}}
> * {{fs.s3a.threads.max}} - in source & documentation code it has value 
> {{10}}, in config file {{64}}
> * {{fs.s3a.max.total.tasks}} - in source code & config it has value {{32}}, 
> in documentation {{5}}
> * {{fs.s3a.connection.maximum}} - in source code & config it has value 
> {{96}}, in documentation {{15}} or {{30}}
> Please sync these values, outdated documentation is very painful to work with.
> As an idea, is it possible to use {{core-default.xml}} directly in 
> documentation, or generate this documentation from docstrings in Java code?



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[jira] [Commented] (HADOOP-18838) Some fs.s3a.* config values are different in sources and documentation

2023-08-08 Thread Steve Loughran (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18838?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17752145#comment-17752145
 ] 

Steve Loughran commented on HADOOP-18838:
-

you can actually get a dump of the live cluster settings from the hadoop hdfs 
namenode; this ensures that you get the *real* values, rather than just the 
default.

things are different in cloud-based deployment, which, given your minio 
configuration issues, seems to be what you are doing. For them, can i point you 
at cloudstore.jar, whose diagnostics handles things like s3a per bucket 
settings, gradually ramps up io, including giving incremental diagnostics. you 
may find it useful: https://github.com/steveloughran/cloudstore/tree/main

> Some fs.s3a.* config values are different in sources and documentation
> --
>
> Key: HADOOP-18838
> URL: https://issues.apache.org/jira/browse/HADOOP-18838
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: fs/s3
>Affects Versions: 3.3.6
>Reporter: Maxim Martynov
>Priority: Major
>
> For config option {{fs.s3a.retry.throttle.interval}} default value in source 
> code is {{500ms}}:
> {code:java}
> public static final String RETRY_THROTTLE_INTERVAL_DEFAULT = "500ms";
> {code}
> https://github.com/apache/hadoop/blob/rel/release-3.3.6/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/Constants.java#L921
> In {{core-default.xml}} it has value {{100ms}}, but in the description 
> {{500ms}}:
> {code:xml}
> 
>   fs.s3a.retry.throttle.interval
>   100ms
>   
> Initial between retry attempts on throttled requests, +/- 50%. chosen at 
> random.
> i.e. for an intial value of 3000ms, the initial delay would be in the 
> range 1500ms to 4500ms.
> Backoffs are exponential; again randomness is used to avoid the 
> thundering heard problem.
> 500ms is the default value used by the AWS S3 Retry policy.
>   
> 
> {code}
> https://github.com/apache/hadoop/blob/rel/release-3.3.6/hadoop-common-project/hadoop-common/src/main/resources/core-default.xml#L1750
> This change introduced in HADOOP-16823.
> In Hadoop-AWS module documentation it has value {{1000ms}}:
> {code:xml}
> 
>   fs.s3a.retry.throttle.interval
>   1000ms
>   
> Interval between retry attempts on throttled requests.
>   
> 
> {code}
> https://github.com/apache/hadoop/blob/rel/release-3.3.6/hadoop-tools/hadoop-aws/src/site/markdown/tools/hadoop-aws/index.md?plain=1#L1223
> File was created in HADOOP-13786, and value is left unchanged since when.
> In performance tuning page it has up-to-date value {{500ms}}:
> {code:xml}
> 
>   fs.s3a.retry.throttle.interval
>   500ms
>   
> Interval between retry attempts on throttled requests.
>   
> 
> {code}
> https://github.com/apache/hadoop/blob/rel/release-3.3.6/hadoop-tools/hadoop-aws/src/site/markdown/tools/hadoop-aws/performance.md?plain=1#L435
> This change introduced in HADOOP-15076.
> The same issue with:
> * {{fs.s3a.retry.throttle.limit}} - in source code it has value {{20}}, but 
> in some documents still old value ${fs.s3a.attempts.maximum}
> * {{fs.s3a.connection.establish.timeout}} - in source code it has value 
> {{50_000}}, in config file & documentation {{5_000}}
> * {{fs.s3a.attempts.maximum}} - in source code it has value {{10}}, in config 
> file & documentation {{20}}
> * {{fs.s3a.threads.max}} - in source & documentation code it has value 
> {{10}}, in config file {{64}}
> * {{fs.s3a.max.total.tasks}} - in source code & config it has value {{32}}, 
> in documentation {{5}}
> * {{fs.s3a.connection.maximum}} - in source code & config it has value 
> {{96}}, in documentation {{15}} or {{30}}
> Please sync these values, outdated documentation is very painful to work with.
> As an idea, is it possible to use {{core-default.xml}} directly in 
> documentation, or generate this documentation from docstrings in Java code?



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[jira] [Updated] (HADOOP-18838) Some fs.s3a.* config values are different in sources and documentation

2023-08-08 Thread Steve Loughran (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18838?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Steve Loughran updated HADOOP-18838:

Component/s: documentation

> Some fs.s3a.* config values are different in sources and documentation
> --
>
> Key: HADOOP-18838
> URL: https://issues.apache.org/jira/browse/HADOOP-18838
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: documentation, fs/s3
>Affects Versions: 3.3.6
>Reporter: Maxim Martynov
>Priority: Major
>
> For config option {{fs.s3a.retry.throttle.interval}} default value in source 
> code is {{500ms}}:
> {code:java}
> public static final String RETRY_THROTTLE_INTERVAL_DEFAULT = "500ms";
> {code}
> https://github.com/apache/hadoop/blob/rel/release-3.3.6/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/Constants.java#L921
> In {{core-default.xml}} it has value {{100ms}}, but in the description 
> {{500ms}}:
> {code:xml}
> 
>   fs.s3a.retry.throttle.interval
>   100ms
>   
> Initial between retry attempts on throttled requests, +/- 50%. chosen at 
> random.
> i.e. for an intial value of 3000ms, the initial delay would be in the 
> range 1500ms to 4500ms.
> Backoffs are exponential; again randomness is used to avoid the 
> thundering heard problem.
> 500ms is the default value used by the AWS S3 Retry policy.
>   
> 
> {code}
> https://github.com/apache/hadoop/blob/rel/release-3.3.6/hadoop-common-project/hadoop-common/src/main/resources/core-default.xml#L1750
> This change introduced in HADOOP-16823.
> In Hadoop-AWS module documentation it has value {{1000ms}}:
> {code:xml}
> 
>   fs.s3a.retry.throttle.interval
>   1000ms
>   
> Interval between retry attempts on throttled requests.
>   
> 
> {code}
> https://github.com/apache/hadoop/blob/rel/release-3.3.6/hadoop-tools/hadoop-aws/src/site/markdown/tools/hadoop-aws/index.md?plain=1#L1223
> File was created in HADOOP-13786, and value is left unchanged since when.
> In performance tuning page it has up-to-date value {{500ms}}:
> {code:xml}
> 
>   fs.s3a.retry.throttle.interval
>   500ms
>   
> Interval between retry attempts on throttled requests.
>   
> 
> {code}
> https://github.com/apache/hadoop/blob/rel/release-3.3.6/hadoop-tools/hadoop-aws/src/site/markdown/tools/hadoop-aws/performance.md?plain=1#L435
> This change introduced in HADOOP-15076.
> The same issue with:
> * {{fs.s3a.retry.throttle.limit}} - in source code it has value {{20}}, but 
> in some documents still old value ${fs.s3a.attempts.maximum}
> * {{fs.s3a.connection.establish.timeout}} - in source code it has value 
> {{50_000}}, in config file & documentation {{5_000}}
> * {{fs.s3a.attempts.maximum}} - in source code it has value {{10}}, in config 
> file & documentation {{20}}
> * {{fs.s3a.threads.max}} - in source & documentation code it has value 
> {{10}}, in config file {{64}}
> * {{fs.s3a.max.total.tasks}} - in source code & config it has value {{32}}, 
> in documentation {{5}}
> * {{fs.s3a.connection.maximum}} - in source code & config it has value 
> {{96}}, in documentation {{15}} or {{30}}
> Please sync these values, outdated documentation is very painful to work with.
> As an idea, is it possible to use {{core-default.xml}} directly in 
> documentation, or generate this documentation from docstrings in Java code?



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[jira] [Updated] (HADOOP-18839) s3a client SSLException is raised after very long timeout "Unsupported or unrecognized SSL message"

2023-08-08 Thread Steve Loughran (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18839?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Steve Loughran updated HADOOP-18839:

Summary: s3a client SSLException is raised after very long timeout 
"Unsupported or unrecognized SSL message"  (was: SSLException is raised after 
very long timeout "Unsupported or unrecognized SSL message")

> s3a client SSLException is raised after very long timeout "Unsupported or 
> unrecognized SSL message"
> ---
>
> Key: HADOOP-18839
> URL: https://issues.apache.org/jira/browse/HADOOP-18839
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: fs/s3
>Affects Versions: 3.3.4
>Reporter: Maxim Martynov
>Priority: Minor
> Attachments: host.log, ssl.log
>
>
> I've tried to connect from PySpark to Minio running in docker.
> Installing PySpark and starting Minio:
> {code:bash}
> pip install pyspark==3.4.1
> docker run --rm -d --hostname minio --name minio -p 9000:9000 -p 9001:9001 -e 
> MINIO_ACCESS_KEY=access -e MINIO_SECRET_KEY=Eevoh2wo0ui6ech0wu8oy
> 3feiR3eicha -e MINIO_ROOT_USER=admin -e 
> MINIO_ROOT_PASSWORD=iepaegaigi3ofa9TaephieSo1iecaesh bitnami/minio:latest
> docker exec minio mc mb test-bucket
> {code}
> Then create Spark session:
> {code:python}
> from pyspark.sql import SparkSession
> spark = SparkSession.builder\
>   .config("spark.jars.packages", 
> "org.apache.hadoop:hadoop-aws:3.3.4")\
>   .config("spark.hadoop.fs.s3a.endpoint", "localhost:9000")\
>   .config("spark.hadoop.fs.s3a.access.key", "access")\
>   .config("spark.hadoop.fs.s3a.secret.key", 
> "Eevoh2wo0ui6ech0wu8oy3feiR3eicha")\
>   .config("spark.hadoop.fs.s3a.aws.credentials.provider", 
> "org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider")\
>   .getOrCreate()
> spark.sparkContext.setLogLevel("debug")
> {code}
> And try to access some object in a bucket:
> {code:python}
> import time
> begin = time.perf_counter()
> spark.read.format("csv").load("s3a://test-bucket/fake")
> end = time.perf_counter()
> py4j.protocol.Py4JJavaError: An error occurred while calling o40.load.
> : org.apache.hadoop.fs.s3a.AWSClientIOException: getFileStatus on 
> s3a://test-bucket/fake: com.amazonaws.SdkClientException: Unable to execute 
> HTTP request: Unsupported or unrecognized SSL message: Unable to execute HTTP 
> request: Unsupported or unrecognized SSL message
> ...
> {code}
> [^ssl.log]
> {code:python}
> >>> print((end-begin)/60)
> 14.72387898775002
> {code}
> I was waiting almost *15 minutes* to get the exception from Spark. The reason 
> was I tried to connect to endpoint with 
> {{{}fs.s3a.connection.ssl.enabled=true{}}}, but Minio is configured to listen 
> for HTTP protocol only.
> Is there any way to immediately raise exception if SSL connection cannot be 
> established?
> If I try to pass wrong endpoint, like {{{}localhos:9000{}}}, I'll get 
> exception like this in just 5 seconds:
> {code:java}
> : org.apache.hadoop.fs.s3a.AWSClientIOException: getFileStatus on 
> s3a://test-bucket/fake: com.amazonaws.SdkClientException: Unable to execute 
> HTTP request: test-bucket.localhos: Unable to execute HTTP request: 
> test-bucket.localhos
> ...
> {code}
> [^host.log]
> {code:python}
> >>> print((end-begin)/60)
> 0.09500707178334172
> >>> end-begin
> 5.700424307000503
> {code}
> I know about options like {{fs.s3a.attempts.maximum}} and 
> {{{}fs.s3a.retry.limit{}}}, setting them to 1 will cause raising exception 
> just immediately. But this does not look right.



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[jira] [Commented] (HADOOP-18839) SSLException is raised after very long timeout

2023-08-08 Thread Steve Loughran (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18839?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17752144#comment-17752144
 ] 

Steve Loughran commented on HADOOP-18839:
-

bq. The point of this issue is to provide better developer experience without 
overriding default values. Is that possible?
yes, but that is going to need someone to write new code and tests. I am trying 
to also suggest any short term workarounds.

> SSLException is raised after very long timeout
> --
>
> Key: HADOOP-18839
> URL: https://issues.apache.org/jira/browse/HADOOP-18839
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: fs/s3
>Affects Versions: 3.3.4
>Reporter: Maxim Martynov
>Priority: Minor
> Attachments: host.log, ssl.log
>
>
> I've tried to connect from PySpark to Minio running in docker.
> Installing PySpark and starting Minio:
> {code:bash}
> pip install pyspark==3.4.1
> docker run --rm -d --hostname minio --name minio -p 9000:9000 -p 9001:9001 -e 
> MINIO_ACCESS_KEY=access -e MINIO_SECRET_KEY=Eevoh2wo0ui6ech0wu8oy
> 3feiR3eicha -e MINIO_ROOT_USER=admin -e 
> MINIO_ROOT_PASSWORD=iepaegaigi3ofa9TaephieSo1iecaesh bitnami/minio:latest
> docker exec minio mc mb test-bucket
> {code}
> Then create Spark session:
> {code:python}
> from pyspark.sql import SparkSession
> spark = SparkSession.builder\
>   .config("spark.jars.packages", 
> "org.apache.hadoop:hadoop-aws:3.3.4")\
>   .config("spark.hadoop.fs.s3a.endpoint", "localhost:9000")\
>   .config("spark.hadoop.fs.s3a.access.key", "access")\
>   .config("spark.hadoop.fs.s3a.secret.key", 
> "Eevoh2wo0ui6ech0wu8oy3feiR3eicha")\
>   .config("spark.hadoop.fs.s3a.aws.credentials.provider", 
> "org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider")\
>   .getOrCreate()
> spark.sparkContext.setLogLevel("debug")
> {code}
> And try to access some object in a bucket:
> {code:python}
> import time
> begin = time.perf_counter()
> spark.read.format("csv").load("s3a://test-bucket/fake")
> end = time.perf_counter()
> py4j.protocol.Py4JJavaError: An error occurred while calling o40.load.
> : org.apache.hadoop.fs.s3a.AWSClientIOException: getFileStatus on 
> s3a://test-bucket/fake: com.amazonaws.SdkClientException: Unable to execute 
> HTTP request: Unsupported or unrecognized SSL message: Unable to execute HTTP 
> request: Unsupported or unrecognized SSL message
> ...
> {code}
> [^ssl.log]
> {code:python}
> >>> print((end-begin)/60)
> 14.72387898775002
> {code}
> I was waiting almost *15 minutes* to get the exception from Spark. The reason 
> was I tried to connect to endpoint with 
> {{{}fs.s3a.connection.ssl.enabled=true{}}}, but Minio is configured to listen 
> for HTTP protocol only.
> Is there any way to immediately raise exception if SSL connection cannot be 
> established?
> If I try to pass wrong endpoint, like {{{}localhos:9000{}}}, I'll get 
> exception like this in just 5 seconds:
> {code:java}
> : org.apache.hadoop.fs.s3a.AWSClientIOException: getFileStatus on 
> s3a://test-bucket/fake: com.amazonaws.SdkClientException: Unable to execute 
> HTTP request: test-bucket.localhos: Unable to execute HTTP request: 
> test-bucket.localhos
> ...
> {code}
> [^host.log]
> {code:python}
> >>> print((end-begin)/60)
> 0.09500707178334172
> >>> end-begin
> 5.700424307000503
> {code}
> I know about options like {{fs.s3a.attempts.maximum}} and 
> {{{}fs.s3a.retry.limit{}}}, setting them to 1 will cause raising exception 
> just immediately. But this does not look right.



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[jira] [Updated] (HADOOP-18839) SSLException is raised after very long timeout "Unsupported or unrecognized SSL message"

2023-08-08 Thread Steve Loughran (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18839?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Steve Loughran updated HADOOP-18839:

Summary: SSLException is raised after very long timeout "Unsupported or 
unrecognized SSL message"  (was: SSLException is raised after very long timeout)

> SSLException is raised after very long timeout "Unsupported or unrecognized 
> SSL message"
> 
>
> Key: HADOOP-18839
> URL: https://issues.apache.org/jira/browse/HADOOP-18839
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: fs/s3
>Affects Versions: 3.3.4
>Reporter: Maxim Martynov
>Priority: Minor
> Attachments: host.log, ssl.log
>
>
> I've tried to connect from PySpark to Minio running in docker.
> Installing PySpark and starting Minio:
> {code:bash}
> pip install pyspark==3.4.1
> docker run --rm -d --hostname minio --name minio -p 9000:9000 -p 9001:9001 -e 
> MINIO_ACCESS_KEY=access -e MINIO_SECRET_KEY=Eevoh2wo0ui6ech0wu8oy
> 3feiR3eicha -e MINIO_ROOT_USER=admin -e 
> MINIO_ROOT_PASSWORD=iepaegaigi3ofa9TaephieSo1iecaesh bitnami/minio:latest
> docker exec minio mc mb test-bucket
> {code}
> Then create Spark session:
> {code:python}
> from pyspark.sql import SparkSession
> spark = SparkSession.builder\
>   .config("spark.jars.packages", 
> "org.apache.hadoop:hadoop-aws:3.3.4")\
>   .config("spark.hadoop.fs.s3a.endpoint", "localhost:9000")\
>   .config("spark.hadoop.fs.s3a.access.key", "access")\
>   .config("spark.hadoop.fs.s3a.secret.key", 
> "Eevoh2wo0ui6ech0wu8oy3feiR3eicha")\
>   .config("spark.hadoop.fs.s3a.aws.credentials.provider", 
> "org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider")\
>   .getOrCreate()
> spark.sparkContext.setLogLevel("debug")
> {code}
> And try to access some object in a bucket:
> {code:python}
> import time
> begin = time.perf_counter()
> spark.read.format("csv").load("s3a://test-bucket/fake")
> end = time.perf_counter()
> py4j.protocol.Py4JJavaError: An error occurred while calling o40.load.
> : org.apache.hadoop.fs.s3a.AWSClientIOException: getFileStatus on 
> s3a://test-bucket/fake: com.amazonaws.SdkClientException: Unable to execute 
> HTTP request: Unsupported or unrecognized SSL message: Unable to execute HTTP 
> request: Unsupported or unrecognized SSL message
> ...
> {code}
> [^ssl.log]
> {code:python}
> >>> print((end-begin)/60)
> 14.72387898775002
> {code}
> I was waiting almost *15 minutes* to get the exception from Spark. The reason 
> was I tried to connect to endpoint with 
> {{{}fs.s3a.connection.ssl.enabled=true{}}}, but Minio is configured to listen 
> for HTTP protocol only.
> Is there any way to immediately raise exception if SSL connection cannot be 
> established?
> If I try to pass wrong endpoint, like {{{}localhos:9000{}}}, I'll get 
> exception like this in just 5 seconds:
> {code:java}
> : org.apache.hadoop.fs.s3a.AWSClientIOException: getFileStatus on 
> s3a://test-bucket/fake: com.amazonaws.SdkClientException: Unable to execute 
> HTTP request: test-bucket.localhos: Unable to execute HTTP request: 
> test-bucket.localhos
> ...
> {code}
> [^host.log]
> {code:python}
> >>> print((end-begin)/60)
> 0.09500707178334172
> >>> end-begin
> 5.700424307000503
> {code}
> I know about options like {{fs.s3a.attempts.maximum}} and 
> {{{}fs.s3a.retry.limit{}}}, setting them to 1 will cause raising exception 
> just immediately. But this does not look right.



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[jira] [Created] (HADOOP-18844) Add a way to get the IOStatistics of active filesystems in long-lived processes

2023-08-08 Thread Steve Loughran (Jira)
Steve Loughran created HADOOP-18844:
---

 Summary: Add a way to get the IOStatistics of active filesystems 
in long-lived processes
 Key: HADOOP-18844
 URL: https://issues.apache.org/jira/browse/HADOOP-18844
 Project: Hadoop Common
  Issue Type: Sub-task
  Components: fs/azure, fs/s3
Affects Versions: 3.3.9
Reporter: Steve Loughran


we can configure abfs and s3a to print out the filesystem IOStats in close(), 
but this doesn't let us see the state of long-lived processes, including 
latencies, error rates, and other important information.

Proposed: we add a means by which all cached filesystems which provide 
IOStatistics can log them to a file/console *while the process continues to run*


* a configurable scheduled thread which enumerates all open filesystem 
instances, gets their iostats and if non empty dumps to a log...log 
configuration can set that to the console or elsewhere. Good: can run without 
intervention; bad: one more thread to manage.
* option to add a signal handler which will do this whenever a SIGUSR2 is 
raised. JVM signal handling is a bit of a brittle feature, so it should be off 
by default.
{{org.apache.hadoop.service.launcher.IrqHandler}} supports signal wire-up. 
good: gives us an equivalent of kill -quit to get a view of iostats. bad: you 
need to be on the machine



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[jira] [Updated] (HADOOP-18843) Guava version 32.0.1 bump to fix CVE-2023-2976 (hadoop-thirdparty PR#23)

2023-08-08 Thread Wei-Chiu Chuang (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18843?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Wei-Chiu Chuang updated HADOOP-18843:
-
Target Version/s: 3.4.0, 3.3.7

> Guava version 32.0.1 bump to fix CVE-2023-2976 (hadoop-thirdparty PR#23)
> 
>
> Key: HADOOP-18843
> URL: https://issues.apache.org/jira/browse/HADOOP-18843
> Project: Hadoop Common
>  Issue Type: Task
>Reporter: Wei-Chiu Chuang
>Priority: Major
>  Labels: pull-request-available
>  Time Spent: 10m
>  Remaining Estimate: 0h
>
> Create the corresponding jira for hadoop-thirdparty PR#23.



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[jira] [Updated] (HADOOP-18843) Guava version 32.0.1 bump to fix CVE-2023-2976 (hadoop-thirdparty PR#23)

2023-08-08 Thread ASF GitHub Bot (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18843?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

ASF GitHub Bot updated HADOOP-18843:

Labels: pull-request-available  (was: )

> Guava version 32.0.1 bump to fix CVE-2023-2976 (hadoop-thirdparty PR#23)
> 
>
> Key: HADOOP-18843
> URL: https://issues.apache.org/jira/browse/HADOOP-18843
> Project: Hadoop Common
>  Issue Type: Task
>Reporter: Wei-Chiu Chuang
>Priority: Major
>  Labels: pull-request-available
>  Time Spent: 10m
>  Remaining Estimate: 0h
>
> Create the corresponding jira for hadoop-thirdparty PR#23.



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[GitHub] [hadoop-thirdparty] jojochuang commented on pull request #23: HADOOP-18843. Guava version 32.0.1 bump to fix CVE-2023-2976

2023-08-08 Thread via GitHub


jojochuang commented on PR #23:
URL: https://github.com/apache/hadoop-thirdparty/pull/23#issuecomment-1669990265

   We'd also need to release a new hadoop-thirdparty version so the main hadoop 
repo can use.


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[jira] [Created] (HADOOP-18843) Guava version 32.0.1 bump to fix CVE-2023-2976 (hadoop-thirdparty PR#23)

2023-08-08 Thread Wei-Chiu Chuang (Jira)
Wei-Chiu Chuang created HADOOP-18843:


 Summary: Guava version 32.0.1 bump to fix CVE-2023-2976 
(hadoop-thirdparty PR#23)
 Key: HADOOP-18843
 URL: https://issues.apache.org/jira/browse/HADOOP-18843
 Project: Hadoop Common
  Issue Type: Task
Reporter: Wei-Chiu Chuang


Create the corresponding jira for hadoop-thirdparty PR#23.



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[GitHub] [hadoop] hadoop-yetus commented on pull request #5862: YARN-11536. [Federation] Router CLI Supports Batch Save the SubClusterPolicyConfiguration Of Queues.

2023-08-08 Thread via GitHub


hadoop-yetus commented on PR #5862:
URL: https://github.com/apache/hadoop/pull/5862#issuecomment-1669986915

   :confetti_ball: **+1 overall**
   
   
   
   
   
   
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[GitHub] [hadoop] hadoop-yetus commented on pull request #5547: HDFS-16977. Forbid assigned characters in pathname.

2023-08-08 Thread via GitHub


hadoop-yetus commented on PR #5547:
URL: https://github.com/apache/hadoop/pull/5547#issuecomment-1669950199

   :broken_heart: **-1 overall**
   
   
   
   
   
   
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[GitHub] [hadoop] hadoop-yetus commented on pull request #5855: HDFS-17093. In the case of all datanodes sending FBR when the namenode restarts (large clusters), there is an issue with incomplete bloc

2023-08-08 Thread via GitHub


hadoop-yetus commented on PR #5855:
URL: https://github.com/apache/hadoop/pull/5855#issuecomment-1669741496

   :broken_heart: **-1 overall**
   
   
   
   
   
   
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[jira] [Updated] (HADOOP-18842) Support Overwrite Directory On Commit For S3A Committers

2023-08-08 Thread Steve Loughran (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18842?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Steve Loughran updated HADOOP-18842:

Affects Version/s: 3.4.0

> Support Overwrite Directory On Commit For S3A Committers
> 
>
> Key: HADOOP-18842
> URL: https://issues.apache.org/jira/browse/HADOOP-18842
> Project: Hadoop Common
>  Issue Type: New Feature
>  Components: fs/s3
>Affects Versions: 3.4.0
>Reporter: Syed Shameerur Rahman
>Priority: Major
>  Labels: pull-request-available
>
> The goal is to add a new kind of commit mechanism in which the destination 
> directory is cleared off before committing the file.
> *Use Case*
> In case of dynamicPartition insert overwrite queries, The destination 
> directory which needs to be overwritten are not known before the execution 
> and hence it becomes a challenge to clear off the destination directory.
>  
> One approach to handle this is, The underlying engines/client will clear off 
> all the destination directories before calling the commitJob operation but 
> the issue with this approach is that, In case of failures while committing 
> the files, We might end up with the whole of previous data being deleted 
> making the recovery process difficult or time consuming.
>  
> *Solution*
> Based on mode of commit operation either *INSERT* or *OVERWRITE* , During 
> commitJob operations, The committer will map each destination directory with 
> the commits which needs to be added in the directory and if the mode is 
> *OVERWRITE* , The committer will delete the directory recursively and then 
> commit each of the files in the directory. So in case of failures (worst 
> case) The number of destination directory which will be deleted will be equal 
> to the number of threads if we do it in multi-threaded way as compared to the 
> whole data if it was done in the engine side.



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[jira] [Updated] (HADOOP-18842) Support Overwrite Directory On Commit For S3A Committers

2023-08-08 Thread Steve Loughran (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18842?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Steve Loughran updated HADOOP-18842:

Component/s: fs/s3

> Support Overwrite Directory On Commit For S3A Committers
> 
>
> Key: HADOOP-18842
> URL: https://issues.apache.org/jira/browse/HADOOP-18842
> 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 kind of commit mechanism in which the destination 
> directory is cleared off before committing the file.
> *Use Case*
> In case of dynamicPartition insert overwrite queries, The destination 
> directory which needs to be overwritten are not known before the execution 
> and hence it becomes a challenge to clear off the destination directory.
>  
> One approach to handle this is, The underlying engines/client will clear off 
> all the destination directories before calling the commitJob operation but 
> the issue with this approach is that, In case of failures while committing 
> the files, We might end up with the whole of previous data being deleted 
> making the recovery process difficult or time consuming.
>  
> *Solution*
> Based on mode of commit operation either *INSERT* or *OVERWRITE* , During 
> commitJob operations, The committer will map each destination directory with 
> the commits which needs to be added in the directory and if the mode is 
> *OVERWRITE* , The committer will delete the directory recursively and then 
> commit each of the files in the directory. So in case of failures (worst 
> case) The number of destination directory which will be deleted will be equal 
> to the number of threads if we do it in multi-threaded way as compared to the 
> whole data if it was done in the engine side.



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[jira] [Commented] (HADOOP-18842) Support Overwrite Directory On Commit For S3A Committers

2023-08-08 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18842?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17752038#comment-17752038
 ] 

ASF GitHub Bot commented on HADOOP-18842:
-

steveloughran commented on PR #5931:
URL: https://github.com/apache/hadoop/pull/5931#issuecomment-1669566586

   this is very like the staging committer's partitioned overwrite, and is 
needed for the magic committer to support insert overwrite in spark, so will be 
good.
   
   Now HADOOP-16570 covers the scale problems with the staging committer, I'd 
hoped the manifest committer would be safe as the per-file data is so much 
smaller, but MAPREDUCE-7435 shows that no, you can't even include manifest 
(source, dest) rename lists without overloading the memory of a spark driver.  
The fix there involved streaming the pending data to the local fs and reading 
back in...I think this may be needed here too. Using the local fs avoids all s3 
writeback/reading. 
   
   The hardest bit of that PR, 
org.apache.hadoop.mapreduce.lib.output.committer.manifest.impl.EntryFileIO, 
will be on the classpath; maybe a more abstract superclass can be extracted, 
SinglePendingCommit data made Writable and then the same queue-based 
serialization used in this job commit: a pool of threads to read all 
.pendingset files, all then streamed to a temp file while that list of dirs to 
clean up is enumerated.





> Support Overwrite Directory On Commit For S3A Committers
> 
>
> Key: HADOOP-18842
> URL: https://issues.apache.org/jira/browse/HADOOP-18842
> Project: Hadoop Common
>  Issue Type: New Feature
>Reporter: Syed Shameerur Rahman
>Priority: Major
>  Labels: pull-request-available
>
> The goal is to add a new kind of commit mechanism in which the destination 
> directory is cleared off before committing the file.
> *Use Case*
> In case of dynamicPartition insert overwrite queries, The destination 
> directory which needs to be overwritten are not known before the execution 
> and hence it becomes a challenge to clear off the destination directory.
>  
> One approach to handle this is, The underlying engines/client will clear off 
> all the destination directories before calling the commitJob operation but 
> the issue with this approach is that, In case of failures while committing 
> the files, We might end up with the whole of previous data being deleted 
> making the recovery process difficult or time consuming.
>  
> *Solution*
> Based on mode of commit operation either *INSERT* or *OVERWRITE* , During 
> commitJob operations, The committer will map each destination directory with 
> the commits which needs to be added in the directory and if the mode is 
> *OVERWRITE* , The committer will delete the directory recursively and then 
> commit each of the files in the directory. So in case of failures (worst 
> case) The number of destination directory which will be deleted will be equal 
> to the number of threads if we do it in multi-threaded way as compared to the 
> whole data if it was done in the engine side.



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[GitHub] [hadoop] steveloughran commented on pull request #5931: [WIP][DRAFT] HADOOP-18842: Support Overwrite Directory On Commit For S3A Committers

2023-08-08 Thread via GitHub


steveloughran commented on PR #5931:
URL: https://github.com/apache/hadoop/pull/5931#issuecomment-1669566586

   this is very like the staging committer's partitioned overwrite, and is 
needed for the magic committer to support insert overwrite in spark, so will be 
good.
   
   Now HADOOP-16570 covers the scale problems with the staging committer, I'd 
hoped the manifest committer would be safe as the per-file data is so much 
smaller, but MAPREDUCE-7435 shows that no, you can't even include manifest 
(source, dest) rename lists without overloading the memory of a spark driver.  
The fix there involved streaming the pending data to the local fs and reading 
back in...I think this may be needed here too. Using the local fs avoids all s3 
writeback/reading. 
   
   The hardest bit of that PR, 
org.apache.hadoop.mapreduce.lib.output.committer.manifest.impl.EntryFileIO, 
will be on the classpath; maybe a more abstract superclass can be extracted, 
SinglePendingCommit data made Writable and then the same queue-based 
serialization used in this job commit: a pool of threads to read all 
.pendingset files, all then streamed to a temp file while that list of dirs to 
clean up is enumerated.



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[GitHub] [hadoop] hadoop-yetus commented on pull request #4314: YARN-11153. Make proxy server support YARN federation.

2023-08-08 Thread via GitHub


hadoop-yetus commented on PR #4314:
URL: https://github.com/apache/hadoop/pull/4314#issuecomment-1669555702

   :confetti_ball: **+1 overall**
   
   
   
   
   
   
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[GitHub] [hadoop] hadoop-yetus commented on pull request #5934: YARN-7599. [BackPort][GPG] ApplicationCleaner in Global Policy Generator.

2023-08-08 Thread via GitHub


hadoop-yetus commented on PR #5934:
URL: https://github.com/apache/hadoop/pull/5934#issuecomment-1669554747

   :broken_heart: **-1 overall**
   
   
   
   
   
   
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[/results-javadoc-javadoc-hadoop-yarn-project_hadoop-yarn_hadoop-yarn-server_hadoop-yarn-server-globalpolicygenerator-jdkUbuntu-11.0.20+8-post-Ubuntu-1ubuntu120.04.txt](https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5934/1/artifact/out/results-javadoc-javadoc-hadoop-yarn-project_hadoop-yarn_hadoop-yarn-server_hadoop-yarn-server-globalpolicygenerator-jdkUbuntu-11.0.20+8-post-Ubuntu-1ubuntu120.04.txt)
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hadoop-

[GitHub] [hadoop] slfan1989 commented on pull request #4314: YARN-11153. Make proxy server support YARN federation.

2023-08-08 Thread via GitHub


slfan1989 commented on PR #4314:
URL: https://github.com/apache/hadoop/pull/4314#issuecomment-1669545487

   @zhengchenyu Thanks for the contribution! LGTM.


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[jira] [Commented] (HADOOP-18837) Upgrade Okio to 3.4.0 due to CVE-2023-3635

2023-08-08 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18837?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17752027#comment-17752027
 ] 

ASF GitHub Bot commented on HADOOP-18837:
-

steveloughran merged PR #5914:
URL: https://github.com/apache/hadoop/pull/5914




> Upgrade Okio to 3.4.0 due to CVE-2023-3635
> --
>
> Key: HADOOP-18837
> URL: https://issues.apache.org/jira/browse/HADOOP-18837
> Project: Hadoop Common
>  Issue Type: Task
>Reporter: Rohit Kumar
>Assignee: Rohit Kumar
>Priority: Major
>  Labels: pull-request-available
> Fix For: 3.4.0
>
>
> Upgrade Okio to 3.4.0 due to CVE-2023-3635
> GzipSource does not handle an exception that might be raised when parsing a 
> malformed gzip buffer. This may lead to denial of service of the Okio client 
> when handling a crafted GZIP archive, by using the GzipSource class.
> CVSSv3 Score:- 7.5(High)
> [https://nvd.nist.gov/vuln/detail/CVE-2023-3635] 



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[GitHub] [hadoop] steveloughran merged pull request #5914: HADOOP-18837. Upgrade okio to 3.4.0 due to CVE-2023-3635

2023-08-08 Thread via GitHub


steveloughran merged PR #5914:
URL: https://github.com/apache/hadoop/pull/5914


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[GitHub] [hadoop] haiyang1987 commented on pull request #5913: HDFS-17137. Standby/Observer NameNode skip to handle redundant replica block logic when set decrease replication.

2023-08-08 Thread via GitHub


haiyang1987 commented on PR #5913:
URL: https://github.com/apache/hadoop/pull/5913#issuecomment-1669411025

   Thanks sir @Hexiaoqiao @tomscut help me review and merge !!!


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[jira] [Updated] (HADOOP-18233) Initialization race condition with TemporaryAWSCredentialsProvider

2023-08-08 Thread Steve Loughran (Jira)


 [ 
https://issues.apache.org/jira/browse/HADOOP-18233?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Steve Loughran updated HADOOP-18233:

Summary: Initialization race condition with TemporaryAWSCredentialsProvider 
 (was: Possible race condition with TemporaryAWSCredentialsProvider)

> Initialization race condition with TemporaryAWSCredentialsProvider
> --
>
> Key: HADOOP-18233
> URL: https://issues.apache.org/jira/browse/HADOOP-18233
> Project: Hadoop Common
>  Issue Type: Bug
>  Components: auth, fs/s3
>Affects Versions: 3.3.1
> Environment: spark v3.2.0
> hadoop-aws v3.3.1
> java version 1.8.0_265 via zulu-8
>Reporter: Jason Sleight
>Assignee: Jimmy Wong
>Priority: Major
>  Labels: pull-request-available
> Fix For: 3.4.0, 3.3.5
>
>
> I'm in the process of upgrading spark+hadoop versions for my workflows and 
> observing a weird behavior regression.  I'm setting
> {code:java}
> spark.hadoop.fs.s3a.aws.credentials.provider=org.apache.hadoop.fs.s3a.TemporaryAWSCredentialsProvider
> spark.hadoop.fs.s3.impl=org.apache.hadoop.fs.s3a.S3AFileSystem
> spark.sql.catalogImplementation=hive
> spark.hadoop.aws.region=us-west-2
> ...many other things, I think these might be the relevant ones though...{code}
> in Spark config and I'm observing some non-fatal warnings/exceptions (see 
> below for some examples).  The warnings/exceptions randomly appear for some 
> tasks, which causes them to fail, but then when Spark retries the task it 
> will succeed.  The initial tasks don't always fail either, just sometimes.
> I also found that if I switch to a SimpleAWSCredentials and use static keys, 
> then I don't see any issues.
> My old setup was spark v3.0.2 with hadoop-aws v3.2.1 which also does not have 
> these warnings/exceptions.
> From reading some other tickets I thought perhaps adding
> {code:java}
> spark.sql.hive.metastore.sharedPrefixes=com.amazonaws {code}
> would help, but it did not.
> Appreciate any suggestions for how to proceed or debug further :)
>  
> Example stack traces:
> First one for an s3 read
> {code:java}
>  WARN TaskSetManager: Lost task 27.0 in stage 4.0 (TID 29) ( executor 
> 13): java.nio.file.AccessDeniedException: 
> s3a://bucket/path/to/part.snappy.parquet: 
> org.apache.hadoop.fs.s3a.CredentialInitializationException: Provider 
> TemporaryAWSCredentialsProvider has no credentials
>     at org.apache.hadoop.fs.s3a.S3AUtils.translateException(S3AUtils.java:206)
>     at org.apache.hadoop.fs.s3a.S3AUtils.translateException(S3AUtils.java:170)
>     at 
> org.apache.hadoop.fs.s3a.S3AFileSystem.s3GetFileStatus(S3AFileSystem.java:3289)
>     at 
> org.apache.hadoop.fs.s3a.S3AFileSystem.innerGetFileStatus(S3AFileSystem.java:3185)
>     at 
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:3053)
>     at 
> org.apache.parquet.hadoop.util.HadoopInputFile.fromPath(HadoopInputFile.java:39)
>     at 
> org.apache.spark.sql.execution.datasources.parquet.ParquetFooterReader.readFooter(ParquetFooterReader.java:39)
>     at 
> org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat.footerFileMetaData$lzycompute$1(ParquetFileFormat.scala:268)
>     at 
> org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat.footerFileMetaData$1(ParquetFileFormat.scala:267)
>     at 
> org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat.$anonfun$buildReaderWithPartitionValues$2(ParquetFileFormat.scala:270)
>     at 
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:116)
>     at 
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:164)
>     at 
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:93)
>     at 
> org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:522)
>     at 
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage7.columnartorow_nextBatch_0$(Unknown
>  Source)
>     at 
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage7.processNext(Unknown
>  Source)
>     at 
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
>     at 
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759)
>     at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
>     at 
> org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:140)
>     at 
> org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
>     at 
> org.apache.spark.sch

[GitHub] [hadoop-thirdparty] fredbalves86 commented on pull request #23: Guava version 32.0.1 bump to fix CVE-2023-2976

2023-08-08 Thread via GitHub


fredbalves86 commented on PR #23:
URL: https://github.com/apache/hadoop-thirdparty/pull/23#issuecomment-1669393233

   @jojochuang Can this be done? 
   
   This is the only dependency of hadoop-common that still has guava 31.1-jre


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[GitHub] [hadoop] YuanbenWang closed pull request #5547: HDFS-16977. Forbid assigned characters in pathname.

2023-08-08 Thread via GitHub


YuanbenWang closed pull request #5547: HDFS-16977. Forbid assigned characters 
in pathname.
URL: https://github.com/apache/hadoop/pull/5547


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[GitHub] [hadoop] slfan1989 opened a new pull request, #5934: YARN-7599. [BackPort][GPG] ApplicationCleaner in Global Policy Generator.

2023-08-08 Thread via GitHub


slfan1989 opened a new pull request, #5934:
URL: https://github.com/apache/hadoop/pull/5934

   
   
   ### Description of PR
   JIRA: YARN-7599. [BackPort][GPG] ApplicationCleaner in Global Policy 
Generator. 
   
   ### 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] hadoop-yetus commented on pull request #4314: YARN-11153. Make proxy server support YARN federation.

2023-08-08 Thread via GitHub


hadoop-yetus commented on PR #4314:
URL: https://github.com/apache/hadoop/pull/4314#issuecomment-1669146353

   :broken_heart: **-1 overall**
   
   
   
   
   
   
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[/branch-spotbugs-hadoop-yarn-project_hadoop-yarn_hadoop-yarn-server_hadoop-yarn-server-web-proxy.txt](https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-4314/27/artifact/out/branch-spotbugs-hadoop-yarn-project_hadoop-yarn_hadoop-yarn-server_hadoop-yarn-server-web-proxy.txt)
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[GitHub] [hadoop] slfan1989 commented on a diff in pull request #5924: HDFS-17140. Optimize the BPOfferService.reportBadBlocks() method

2023-08-08 Thread via GitHub


slfan1989 commented on code in PR #5924:
URL: https://github.com/apache/hadoop/pull/5924#discussion_r1286759399


##
hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/BPOfferService.java:
##
@@ -291,9 +291,8 @@ public String toString() {
   void reportBadBlocks(ExtendedBlock block,
String storageUuid, StorageType storageType) {
 checkBlock(block);
+ReportBadBlockAction rbbAction = new ReportBadBlockAction(block, 
storageUuid, storageType);

Review Comment:
   Thank you very much for your explanation! Personally, I believe this 
modification seems a bit forced and unnecessary. 
   Let's wait for @2005hithlj  to give a detailed explanation.



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[GitHub] [hadoop] hadoop-yetus commented on pull request #5933: HDFS-17145. Fix description of property dfs.namenode.file.close.num-committed-allowed.

2023-08-08 Thread via GitHub


hadoop-yetus commented on PR #5933:
URL: https://github.com/apache/hadoop/pull/5933#issuecomment-1669119407

   :broken_heart: **-1 overall**
   
   
   
   
   
   
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[/patch-unit-hadoop-hdfs-project_hadoop-hdfs.txt](https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5933/1/artifact/out/patch-unit-hadoop-hdfs-project_hadoop-hdfs.txt)
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[GitHub] [hadoop] Hexiaoqiao commented on pull request #5913: HDFS-17137. Standby/Observer NameNode skip to handle redundant replica block logic when set decrease replication.

2023-08-08 Thread via GitHub


Hexiaoqiao commented on PR #5913:
URL: https://github.com/apache/hadoop/pull/5913#issuecomment-1669086283

   The failed unit test is not related to this changes. Committed to trunk.
   Thanks @haiyang1987 for your contribution and @tomscut reviews!


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[GitHub] [hadoop] Hexiaoqiao merged pull request #5913: HDFS-17137. Standby/Observer NameNode skip to handle redundant replica block logic when set decrease replication.

2023-08-08 Thread via GitHub


Hexiaoqiao merged PR #5913:
URL: https://github.com/apache/hadoop/pull/5913


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[GitHub] [hadoop] Hexiaoqiao commented on pull request #5926: HADOOP-18840. Add enQueue time to RpcMetrics

2023-08-08 Thread via GitHub


Hexiaoqiao commented on PR #5926:
URL: https://github.com/apache/hadoop/pull/5926#issuecomment-1669074483

   @2005hithlj Please check the failed unit test and checkstyle.


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[jira] [Commented] (HADOOP-18840) Add enQueue time to RpcMetrics

2023-08-08 Thread ASF GitHub Bot (Jira)


[ 
https://issues.apache.org/jira/browse/HADOOP-18840?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17751924#comment-17751924
 ] 

ASF GitHub Bot commented on HADOOP-18840:
-

Hexiaoqiao commented on PR #5926:
URL: https://github.com/apache/hadoop/pull/5926#issuecomment-1669074483

   @2005hithlj Please check the failed unit test and checkstyle.




> Add enQueue time to RpcMetrics
> --
>
> Key: HADOOP-18840
> URL: https://issues.apache.org/jira/browse/HADOOP-18840
> Project: Hadoop Common
>  Issue Type: Improvement
>  Components: rpc-server
>Reporter: Liangjun He
>Assignee: Liangjun He
>Priority: Minor
>  Labels: pull-request-available
>
> Sometimes, the request time observed by the client is much longer than the 
> queue + process time on the RPC server. Perhaps the RPC request 'waiting 
> enQueue' took too long on the RPC server, so we should add enQueue time to 
> RpcMetrics.



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[GitHub] [hadoop] Hexiaoqiao commented on a diff in pull request #5924: HDFS-17140. Optimize the BPOfferService.reportBadBlocks() method

2023-08-08 Thread via GitHub


Hexiaoqiao commented on code in PR #5924:
URL: https://github.com/apache/hadoop/pull/5924#discussion_r1286718143


##
hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/BPOfferService.java:
##
@@ -291,9 +291,8 @@ public String toString() {
   void reportBadBlocks(ExtendedBlock block,
String storageUuid, StorageType storageType) {
 checkBlock(block);
+ReportBadBlockAction rbbAction = new ReportBadBlockAction(block, 
storageUuid, storageType);

Review Comment:
   I am not worried about that, because `BPOfferService` is isolated for 
different namespaces. But I am wonder what improvement here, save the cost to 
create object and heap footprint?



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[GitHub] [hadoop] huangzhaobo99 commented on pull request #5930: HDFS-17143. Optimize the logic for reconfigure ReadStrategy enable for Namenode.

2023-08-08 Thread via GitHub


huangzhaobo99 commented on PR #5930:
URL: https://github.com/apache/hadoop/pull/5930#issuecomment-1669064696

   Hi @slfan1989, Could you help review this when you have time? Thanks.


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[GitHub] [hadoop] huangzhaobo99 commented on pull request #5930: HDFS-17143. Optimize the logic for reconfigure ReadStrategy enable for Namenode.

2023-08-08 Thread via GitHub


huangzhaobo99 commented on PR #5930:
URL: https://github.com/apache/hadoop/pull/5930#issuecomment-1669062915

   Those failed unit tests were unrelated to the change. And they work fine 
locally.


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