[SPARK-56335][SQL] Implement SupportsMetadataColumns in FileTable#55320
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LuciferYang wants to merge 12 commits intoapache:masterfrom
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[SPARK-56335][SQL] Implement SupportsMetadataColumns in FileTable#55320LuciferYang wants to merge 12 commits intoapache:masterfrom
LuciferYang wants to merge 12 commits intoapache:masterfrom
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…Frame API writes and delete FallBackFileSourceV2 Key changes: - FileWrite: added partitionSchema, customPartitionLocations, dynamicPartitionOverwrite, isTruncate; path creation and truncate logic; dynamic partition overwrite via FileCommitProtocol - FileTable: createFileWriteBuilder with SupportsDynamicOverwrite and SupportsTruncate; capabilities now include TRUNCATE and OVERWRITE_DYNAMIC; fileIndex skips file existence checks when userSpecifiedSchema is provided (write path) - All file format writes (Parquet, ORC, CSV, JSON, Text, Avro) use createFileWriteBuilder with partition/truncate/overwrite support - DataFrameWriter.lookupV2Provider: enabled FileDataSourceV2 for non-partitioned Append and Overwrite via df.write.save(path) - DataFrameWriter.insertInto: V1 fallback for file sources (TODO: SPARK-56175) - DataFrameWriter.saveAsTable: V1 fallback for file sources (TODO: SPARK-56230, needs StagingTableCatalog) - DataSourceV2Utils.getTableProvider: V1 fallback for file sources (TODO: SPARK-56175) - Removed FallBackFileSourceV2 rule - V2SessionCatalog.createTable: V1 FileFormat data type validation
…catalog table loading, and gate removal Key changes: - FileTable extends SupportsPartitionManagement with createPartition, dropPartition, listPartitionIdentifiers, partitionSchema - Partition operations sync to catalog metastore (best-effort) - V2SessionCatalog.loadTable returns FileTable instead of V1Table, sets catalogTable and useCatalogFileIndex on FileTable - V2SessionCatalog.getDataSourceOptions includes storage.properties for proper option propagation (header, ORC bloom filter, etc.) - V2SessionCatalog.createTable validates data types via FileTable - FileTable.columns() restores NOT NULL constraints from catalogTable - FileTable.partitioning() falls back to userSpecifiedPartitioning or catalog partition columns - FileTable.fileIndex uses CatalogFileIndex when catalog has registered partitions (custom partition locations) - FileTable.schema checks column name duplication for non-catalog tables only - DataSourceV2Utils.getTableProvider: removed FileDataSourceV2 gate - DataFrameWriter.insertInto: enabled V2 for file sources - DataFrameWriter.saveAsTable: V1 fallback (TODO: SPARK-56230) - ResolveSessionCatalog: V1 fallback for FileTable-backed commands (AnalyzeTable, AnalyzeColumn, TruncateTable, TruncatePartition, ShowPartitions, RecoverPartitions, AddPartitions, RenamePartitions, DropPartitions, SetTableLocation, CREATE TABLE validation, REPLACE TABLE blocking) - FindDataSourceTable: streaming V1 fallback for FileTable (TODO: SPARK-56233) - DataSource.planForWritingFileFormat: graceful V2 handling
Enable bucketed writes for V2 file tables via catalog BucketSpec. Key changes: - FileWrite: add bucketSpec field, use V1WritesUtils.getWriterBucketSpec() instead of hardcoded None - FileTable: createFileWriteBuilder passes catalogTable.bucketSpec to the write pipeline - FileDataSourceV2: getTable uses collect to skip BucketTransform (handled via catalogTable.bucketSpec instead) - FileWriterFactory: use DynamicPartitionDataConcurrentWriter for bucketed writes since V2's RequiresDistributionAndOrdering cannot express hash-based ordering - All 6 format Write/Table classes updated with BucketSpec parameter Note: bucket pruning and bucket join (read-path optimization) are not included in this patch (tracked under SPARK-56231).
Add RepairTableExec to sync filesystem partition directories with catalog metastore for V2 file tables. Key changes: - New RepairTableExec: scans filesystem partitions via FileTable.listPartitionIdentifiers(), compares with catalog, registers missing partitions and drops orphaned entries - DataSourceV2Strategy: route RepairTable and RecoverPartitions for FileTable to new V2 exec node
Implement SupportsOverwriteV2 for V2 file tables to support static partition overwrite (INSERT OVERWRITE TABLE t PARTITION(p=1) SELECT ...). Key changes: - FileTable: replace SupportsTruncate with SupportsOverwriteV2 on WriteBuilder, implement overwrite(predicates) - FileWrite: extend toBatch() to delete only the matching partition directory, ordered by partitionSchema - FileTable.CAPABILITIES: add OVERWRITE_BY_FILTER - All 6 format Write/Table classes: plumb overwritePredicates parameter This is a prerequisite for SPARK-56304 (ifPartitionNotExists).
…EAD) ### What changes were proposed in this pull request? Implements `MicroBatchStream` support for V2 file tables, enabling structured streaming reads through the V2 path instead of falling back to V1 `FileStreamSource`. Key changes: - New `FileMicroBatchStream` class implementing `MicroBatchStream`, `SupportsAdmissionControl`, and `SupportsTriggerAvailableNow` — handles file discovery, offset management, rate limiting, and partition planning - Override `FileScan.toMicroBatchStream()` to return `FileMicroBatchStream` - Add `withFileIndex` method to `FileScan` and all 6 concrete scans for creating batch-specific scans - Add `MICRO_BATCH_READ` to `FileTable.CAPABILITIES` - Update `ResolveDataSource` to allow `FileDataSourceV2` into the V2 streaming path (respects `USE_V1_SOURCE_LIST` for backward compatibility) - Remove the `FileTable` streaming fallback in `FindDataSourceTable` - Reuses V1 infrastructure (`FileStreamSourceLog`, `FileStreamSourceOffset`, `SeenFilesMap`) for checkpoint compatibility ### Why are the changes needed? V2 file tables cannot be fully adopted until streaming reads are supported. Without this, the V1 `FileStreamSource` fallback prevents deprecation of V1 file source code. ### Does this PR introduce _any_ user-facing change? No. By default, `USE_V1_SOURCE_LIST` includes all file formats, so streaming reads still use V1. Users can opt into V2 by clearing the list. Existing checkpoints are compatible. ### How was this patch tested? New `FileStreamV2ReadSuite` with 6 E2E tests. Existing `FileStreamSourceSuite` (76 tests) passes with V1 forced via `USE_V1_SOURCE_LIST`.
…ITE) ### What changes were proposed in this pull request? Implements `StreamingWrite` support for V2 file tables, enabling structured streaming writes through the V2 path instead of falling back to V1 `FileStreamSink`. Key changes: - New `FileStreamingWrite` class implementing `StreamingWrite` — uses `ManifestFileCommitProtocol` for file commit and `FileStreamSinkLog` for metadata tracking - New `FileStreamingWriterFactory` bridging `DataWriterFactory` to `StreamingDataWriterFactory` - Override `FileWrite.toStreaming()` to return `FileStreamingWrite` - Add `STREAMING_WRITE` to `FileTable.CAPABILITIES` - Idempotent `commit(epochId, messages)` — skips already-committed batches - Supports `retention` option for metadata log cleanup (V1 parity) - Checkpoint compatible with V1 `FileStreamSink` (same `_spark_metadata` format) ### Why are the changes needed? V2 file tables cannot be fully adopted until streaming writes are supported. Without this, the V1 `FileStreamSink` fallback prevents deprecation of V1 file source code. Together with SPARK-56232 (streaming read), this completes the streaming support needed for V1 deprecation. ### Does this PR introduce _any_ user-facing change? No. By default, `USE_V1_SOURCE_LIST` includes all file formats, so streaming writes still use V1. Users can opt into V2 by clearing the list. Existing checkpoints are compatible. ### How was this patch tested? New `FileStreamV2WriteSuite` with 4 E2E tests. Existing `FileStreamSinkV1Suite` passes. All 108 streaming file tests pass.
Exposes the V1-compatible `_metadata` struct column (`file_path`, `file_name`, `file_size`, `file_block_start`, `file_block_length`, `file_modification_time`) on V2 file-based tables so that queries like `SELECT _metadata.file_path FROM parquet.`<path>`` work against the V2 scan path instead of forcing a V1 fallback. The wiring is: * `FileTable` implements `SupportsMetadataColumns.metadataColumns()` and returns a single `_metadata` struct column whose fields come from `FileFormat.BASE_METADATA_FIELDS`. Formats may extend `metadataSchemaFields` later to expose additional fields (e.g., Parquet's `row_index`, tracked in SPARK-56371). * `FileScanBuilder.pruneColumns` intercepts the `_metadata` field from the required schema, stores the pruned metadata struct on `requestedMetadataFields`, and keeps it out of `readDataSchema` so the format-specific reader stays unchanged. * `FileScan.readSchema` re-exposes `_metadata` as a trailing struct field when metadata is requested, so `V2ScanRelationPushDown` can rebind the downstream attribute reference back to the scan output. * A new `MetadataAppendingFilePartitionReaderFactory` wraps the format-specific reader factory and appends a single `_metadata` struct value (via `JoinedRow` + an inner `GenericInternalRow`) to each row. Columnar reads are disabled while metadata is requested since `ConstantColumnVector` is scalar and cannot represent a struct column; queries fall back to the row path. * All six concrete scans (Parquet/ORC/CSV/JSON/Text/Avro) take `requestedMetadataFields` as a trailing default-valued case-class parameter and call the new `wrapWithMetadataIfNeeded` helper when constructing their reader factory. Their `ScanBuilder.build()` implementations pass the field through from `FileScanBuilder`. Parquet's generated `row_index` metadata field is intentionally out of scope; follow-up work is tracked in SPARK-56371. Before this change, `_metadata` on a DSv2 file table was unresolvable and the query fell back to the V1 `FileSourceScanExec` path, which is one of the remaining blockers for deprecating the V1 file sources (SPARK-56170). Yes. `_metadata.*` queries now work against the V2 file sources with the same semantics as V1. New `FileMetadataColumnsV2Suite` exercises read and projection paths for Parquet/ORC/JSON/CSV/Text, forcing the V2 path via `useV1SourceList`, and asserts the metadata struct values against the underlying file's `java.io.File` stats. All 16 tests pass.
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This is the 12th PR for SPARK-56170 |
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What changes were proposed in this pull request?
Expose the V1-compatible
_metadatastruct column (file_path,file_name,file_size,file_block_start,file_block_length,file_modification_time)on V2 file-based tables so that queries like
SELECT _metadata.file_path FROM parquet.`` work against the V2 scanpath instead of forcing a V1 fallback.
Key changes:
FileTableimplementsSupportsMetadataColumns:metadataColumns()returns a single
_metadatastruct column whose fields come fromFileFormat.BASE_METADATA_FIELDS. Formats can extendmetadataSchemaFieldsto expose additional fields (e.g., Parquet's
row_index, tracked inSPARK-56371).
FileScanBuilder.pruneColumns: Intercepts the_metadatafield fromthe required schema, stores the pruned metadata struct on
requestedMetadataFields, and keeps it out ofreadDataSchemaso theformat-specific reader stays unchanged.
FileScan.readSchema: Re-exposes_metadataas a trailing struct fieldwhen metadata is requested, so
V2ScanRelationPushDowncan rebind thedownstream attribute reference back to the scan output.
MetadataAppendingFilePartitionReaderFactory(new): Wraps theformat-specific reader factory and appends a single
_metadatastruct value(via
JoinedRow+ an innerGenericInternalRow) to each row. Columnarreads are disabled while metadata is requested since
ConstantColumnVectoris scalar and cannot represent a struct column; queries fall back to the row
path.
All six concrete scans (Parquet/ORC/CSV/JSON/Text/Avro): Take
requestedMetadataFieldsas a trailing default-valued case-class parameterand call the new
wrapWithMetadataIfNeededhelper when constructing theirreader factory. Their
ScanBuilder.build()implementations pass the fieldthrough from
FileScanBuilder.Parquet's generated
row_indexmetadata field is intentionally out of scope;follow-up work is tracked in SPARK-56371.
Why are the changes needed?
Before this change,
_metadataon a DSv2 file table was unresolvable and thequery fell back to the V1
FileSourceScanExecpath. This is one of theremaining blockers for deprecating the V1 file sources (SPARK-56170).
Does this PR introduce any user-facing change?
Yes.
_metadata.*queries now work against V2 file sources with the samesemantics as V1.
How was this patch tested?
New
FileMetadataColumnsV2Suite(24 tests) exercises read and projection pathsfor Parquet/ORC/JSON/CSV/Text, forcing the V2 path via
spark.sql.sources.useV1SourceList = "", and asserts the metadata struct valuesagainst the underlying file's
java.io.Filestats.Was this patch authored or co-authored using generative AI tooling?
Generated-by: Claude Code