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https://issues.apache.org/jira/browse/HADOOP-17377?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18032105#comment-18032105
]
ASF GitHub Bot commented on HADOOP-17377:
-----------------------------------------
steveloughran commented on PR #5273:
URL: https://github.com/apache/hadoop/pull/5273#issuecomment-3432466591
@anujmodi2021 can you revisit this so I can get it in?
we do appear to have been using it internally since december 2023, so I'm
happy it works.
> ABFS: MsiTokenProvider doesn't retry HTTP 429 from the Instance Metadata
> Service
> --------------------------------------------------------------------------------
>
> Key: HADOOP-17377
> URL: https://issues.apache.org/jira/browse/HADOOP-17377
> Project: Hadoop Common
> Issue Type: Bug
> Components: fs/azure
> Affects Versions: 3.2.1
> Reporter: Brandon
> Priority: Major
> Labels: pull-request-available
>
> *Summary*
> The instance metadata service has its own guidance for error handling and
> retry which are different from the Blob store.
> [https://docs.microsoft.com/en-us/azure/active-directory/managed-identities-azure-resources/how-to-use-vm-token#error-handling]
> In particular, it responds with HTTP 429 if request rate is too high. Whereas
> Blob store will respond with HTTP 503. The retry policy used only accounts
> for the latter as it will retry any status >=500. This can result in job
> instability when running multiple processes on the same host.
> *Environment*
> * Spark talking to an ABFS store
> * Hadoop 3.2.1
> * Running on an Azure VM with user-assigned identity, ABFS configured to use
> MsiTokenProvider
> * 6 executor processes on each VM
> *Example*
> Here's an example error message and stack trace. It's always the same stack
> trace. This appears in logs a few hundred to low thousands of times a day.
> It's luckily skating by since the download operation is wrapped in 3 retries.
> {noformat}
> AADToken: HTTP connection failed for getting token from AzureAD. Http
> response: 429 null
> Content-Type: application/json; charset=utf-8 Content-Length: 90 Request ID:
> Proxies: none
> First 1K of Body: {"error":"invalid_request","error_description":"Temporarily
> throttled, too many requests"}
> at
> org.apache.hadoop.fs.azurebfs.services.AbfsRestOperation.executeHttpOperation(AbfsRestOperation.java:190)
> at
> org.apache.hadoop.fs.azurebfs.services.AbfsRestOperation.execute(AbfsRestOperation.java:125)
> at
> org.apache.hadoop.fs.azurebfs.services.AbfsClient.getAclStatus(AbfsClient.java:506)
> at
> org.apache.hadoop.fs.azurebfs.services.AbfsClient.getAclStatus(AbfsClient.java:489)
> at
> org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore.getIsNamespaceEnabled(AzureBlobFileSystemStore.java:208)
> at
> org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore.getFileStatus(AzureBlobFileSystemStore.java:473)
> at
> org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem.getFileStatus(AzureBlobFileSystem.java:437)
> at org.apache.hadoop.fs.FileSystem.isFile(FileSystem.java:1717)
> at org.apache.spark.util.Utils$.fetchHcfsFile(Utils.scala:747)
> at org.apache.spark.util.Utils$.doFetchFile(Utils.scala:724)
> at org.apache.spark.util.Utils$.fetchFile(Utils.scala:496)
> at
> org.apache.spark.executor.Executor.$anonfun$updateDependencies$7(Executor.scala:812)
> at
> org.apache.spark.executor.Executor.$anonfun$updateDependencies$7$adapted(Executor.scala:803)
> at
> scala.collection.TraversableLike$WithFilter.$anonfun$foreach$1(TraversableLike.scala:792)
> at
> scala.collection.mutable.HashMap.$anonfun$foreach$1(HashMap.scala:149)
> at scala.collection.mutable.HashTable.foreachEntry(HashTable.scala:237)
> at scala.collection.mutable.HashTable.foreachEntry$(HashTable.scala:230)
> at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:44)
> at scala.collection.mutable.HashMap.foreach(HashMap.scala:149)
> at
> scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:791)
> at
> org.apache.spark.executor.Executor.org$apache$spark$executor$Executor$$updateDependencies(Executor.scala:803)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:375)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748){noformat}
> CC [~mackrorysd], [[email protected]]
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