[SPARK-57591][SQL] Read and infer ORC schema from archives

[akshatshenoi-db]

What changes were proposed in this pull request?

This extends the archive-reader feature to the ORC data source, so a .tar/.tar.gz/.tgz/.zip/.7z archive of ORC files is read as if it were a directory of the entries it contains, gated by spark.sql.files.archive.reader.enabled (default false). It follows the series that added archive support to CSV (SPARK-57135, SPARK-57321), JSON (SPARK-57419), text (SPARK-57478), XML (SPARK-57479), Avro (SPARK-57481), the zip container (SPARK-57705), the SupportsArchiveFormat trait extraction (SPARK-58110), and Parquet (SPARK-57590).

ORC is a random-access format like Parquet: a footer read needs the whole file on disk, so it cannot be streamed entry-by-entry. It consumes the random-access surface already on the SupportsArchiveFormat trait (added by the Parquet port):

• OrcFileFormat mixes in SupportsArchiveFormat, returns archiveEntryFilter = true (ORC part-files are often extensionless, so every entry is read), reports isSplitable = false for an archive path, and in buildReaderWithPartitionValues dispatches an archive input to readLocalizedEntries, which unpacks each entry to a temp file and runs the normal single-file reader over it.
• OrcUtils routes schema inference through the archive: the non-merge path samples the first entry (readArchiveSchemas(stopAtFirst = true), matching ORC's existing sample-one behavior, SPARK-11500), and the mergeSchema parallel path folds every entry (whole-archive-atomic on a corrupt entry). A corrupt archive surfaces the same cannotReadFooterForFileError a corrupt loose file does.

The shared test base is refactored so the localize-path tests (vectorized-reader read parity, abandoned-read/corrupt-archive temp-dir cleanup, extensionless entries, mergeSchema field union) live in ArchiveReadSuiteBase behind localizesEntries, keyed on new archiveTempDirPrefix / vectorizedReaderConfKey hooks, instead of being duplicated per random-access format. ParquetArchiveReadBase is slimmed to set those hooks; OrcArchiveReadBase reuses them.

Why are the changes needed?

ORC was the remaining columnar format without archive-read support; this brings it to parity with Parquet and the streaming formats, so users can read archived ORC datasets without unpacking them first. Folding the shared random-access tests into the base avoids duplicating them for every columnar format.

Does this PR introduce any user-facing change?

Yes. When spark.sql.files.archive.reader.enabled is true (default false), the ORC data source reads supported archives as directories of their entries, for both scan and schema inference. With the flag off (the default) there is no behavior change.

How was this patch tested?

New OrcTarArchiveReadSuite, OrcZipArchiveReadSuite, and OrcSevenZArchiveReadSuite run the shared ArchiveReadSuiteBase matrix over ORC (read parity with a directory, schema inference, vectorized on/off, corrupt/missing handling, mergeSchema union, temp-dir cleanup). The refactored localize-path tests continue to run for Parquet via ParquetArchiveReadBase.

Was this patch authored or co-authored using generative AI tooling?

Generated-by: Claude Code