sahnib opened a new pull request, #47875:
URL: https://github.com/apache/spark/pull/47875
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### What changes were proposed in this pull request?
Currently, we have a scenario where if a version X is loaded (and there is
an existing snapshot with version X), Spark will reuse the SST files from the
existing Snapshot resulting in a VersionID Mismatch error. This PR fixes this
issue, and simplifies RocksDB state management. The change eliminates the
majority of shared state between Task thread and Maintenance thread,
simplifying the implementation.
With this change, the task thread is now solely responsible for keeping
track of the local files to DFS file mapping, the maintenance thread will not
access this mapping. The DFS file names are generated at `commit()` - the
generated snapshot, and the mapping containing the new SST files (with their
generated DFS names) is handed over to the maintenance thread. The latest
generated snapshot will be appended to a ConcurrentLinkedQueue (named
snapshotsToUploadQueue).
The maintenance thread polls from the snapshotsToUploadQueue repeatedly
until its empty. For the last snapshot polled out of the queue, the maintenance
thread will upload the new SST files. The maintenance thread will also clear
all removed snapshot objects from the disk.
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### Why are the changes needed?
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These changes fix an issue where Spark Streaming fails with RocksDB
VersionIdMismatch error if there is a existing snapshot (not yet uploaded) for
RocksDB version being loaded. In this scenario, SST files from existing
snapshot are reused resulting in a versionId Mismatch error. In short, these
changes:
1. Remove shared fileMapping between RocksDB Maintenance thread and task
thread, simplifying the file mapping logic. The file Mapping is only modified
from task thread after this change.
2. Fixes the issue where RocksDB SST files from current snapshot (with same
version) are reused, resulting in RocksDB VersionId Mismatch.
3. Swap acquireLock with a Reentrant logic for easier management of acquire
Lock.
### Does this PR introduce _any_ user-facing change?
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No
### How was this patch tested?
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1. All existing testcases pass.
2. Added new testcases suggested in
https://github.com/apache/spark/pull/47850/files, and ensure they pass with
these changes.
### Was this patch authored or co-authored using generative AI tooling?
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No
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