HIVE-29437: Iceberg: Fix concurrency issues between compaction and co…#6292
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difin wants to merge 2 commits intoapache:masterfrom
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HIVE-29437: Iceberg: Fix concurrency issues between compaction and co…#6292difin wants to merge 2 commits intoapache:masterfrom
difin wants to merge 2 commits intoapache:masterfrom
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…ncurrent write operations.
deniskuzZ
reviewed
Feb 3, 2026
| IcebergCompactionUtil.getDataFiles(table, snapshotId, partitionPath, fileSizeThreshold); | ||
| List<DeleteFile> existingDeleteFiles = fileSizeThreshold == -1 ? | ||
| IcebergCompactionUtil.getDeleteFiles(table, partitionPath) : Collections.emptyList(); | ||
| IcebergCompactionUtil.getDeleteFiles(table, snapshotId, partitionPath) : Collections.emptyList(); |
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please add test.
as an example you could use TestConflictingDataFiles#testConflictingUpdateAndDelete
deniskuzZ
reviewed
Feb 3, 2026
| Table deletesTable = | ||
| MetadataTableUtils.createMetadataTableInstance(table, MetadataTableType.POSITION_DELETES); | ||
| CloseableIterable<ScanTask> deletesScanTasks = deletesTable.newBatchScan().planFiles(); | ||
| CloseableIterable<ScanTask> deletesScanTasks = deletesTable.newBatchScan().useSnapshot(snapshotId).planFiles(); |
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why do you use here newBatchScan() and in getDataFiles newScan()? should we use BatchScan in both places?
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It was in the existing code, changed to newScan().
Changed to use BatchScan in both places.
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…ncurrent write operations.
What changes were proposed in this pull request?
Fixing concurrency issues between compaction and concurrent write operations.
Why are the changes needed?
It was found in downstream testing that when Hive Iceberg compaction is running in parallel to Spark write operations on the same table, compaction sometimes produces wrong results. Before committing, when Hive already has the compacted data files that need to replace existing, uncompacted data and delete files in a table or partition, it collects those uncompacted data and delete files to replace them with the compacted files. The issue is that Hive collects those uncompacted data and delete files from the latest Iceberg snapshot instead of using the original snapshot. The latest snapshot may contain different data because of concurrent write operations, which can lead to data corruption.
Does this PR introduce any user-facing change?
No
How was this patch tested?
The fix was validated downstream with concurrent Spark write operations and Hive Iceberg compaction.