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  1. HBase
  2. HBASE-20429 Support for mixed or write-heavy workloads on non-HDFS filesystems
  3. HBASE-20431

Store commit transaction for filesystems that do not support an atomic rename

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    • Sub-task
    • Status: Closed
    • Major
    • Resolution: Duplicate
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    Description

      HBase expects the Hadoop filesystem implementation to support an atomic rename() operation. HDFS does. The S3 backed filesystems do not. The fundamental issue is the non-atomic and eventually consistent nature of the S3 service. A S3 bucket is not a filesystem. S3 is not always immediately read-your-writes. Object metadata can be temporarily inconsistent just after new objects are stored. There can be a settling period to ride over. Renaming/moving objects from one path to another are copy operations with O(file) complexity and O(data) time followed by a series of deletes with O(file) complexity. Failures at any point prior to completion will leave the operation in an inconsistent state. The missing atomic rename semantic opens opportunities for corruption and data loss, which may or may not be repairable with HBCK.

      Handling this at the HBase level could be done with a new multi-step filesystem transaction framework. Call it StoreCommitTransaction. SplitTransaction and MergeTransaction are well established cases where even on HDFS we have non-atomic filesystem changes and are our implementation template for the new work. In this new StoreCommitTransaction we'd be moving flush and compaction temporaries out of the temporary directory into the region store directory. On HDFS the implementation would be easy. We can rely on the filesystem's atomic rename semantics. On S3 it would be work: First we would build the list of objects to move, then copy each object into the destination, and then finally delete all objects at the original path. We must handle transient errors with retry strategies appropriate for the action at hand. We must handle serious or permanent errors where the RS doesn't need to be aborted with a rollback that cleans it all up. Finally, we must handle permanent errors where the RS must be aborted with a rollback during region open/recovery. Note that after all objects have been copied and we are deleting obsolete source objects we must roll forward, not back. To support recovery after an abort we must utilize the WAL to track transaction progress. Put markers in for StoreCommitTransaction start and completion state, with details of the store file(s) involved, so it can be rolled back during region recovery at open. This will be significant work in HFile, HStore, flusher, compactor, and HRegion. Wherever we use HDFS's rename now we would substitute the running of this new multi-step filesystem transaction.

      We need to determine this for certain, but I believe on S3 the PUT or multipart upload of an object must complete before the object is visible, so we don't have to worry about the case where an object is visible before fully uploaded as part of normal operations. So an individual object copy will either happen entirely and the target will then become visible, or it won't and the target won't exist.

      S3 has an optimization, PUT COPY (https://docs.aws.amazon.com/AmazonS3/latest/API/RESTObjectCOPY.html), which the AmazonClient embedded in S3A utilizes for moves. When designing the StoreCommitTransaction be sure to allow for filesystem implementations that leverage a server side copy operation. Doing a get-then-put should be optional. (Not sure Hadoop has an interface that advertises this capability yet; we can add one if not.)

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              Unassigned Unassigned
              apurtell Andrew Kyle Purtell
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