Spark 4.1: expose catalog labels via metadata table and DESCRIBE - #17411
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Reference client implementation for the IRC labels read-path spec change (apache#15750). Without it, RESTObjectMapper (which sets FAIL_ON_UNKNOWN_PROPERTIES = false) silently drops the labels field on deserialization, so labels returned by a catalog are invisible to the Java client. New rest.labels package (mirroring rest.credentials): Labels (object + fields sub-scopes, with a shared empty instance) and FieldLabels (per-field, keyed by field-id) value types as immutables interfaces, each with a JSON parser. FieldLabels validates field-id >= 1 and a non-empty labels map, matching Credential. Wire an optional labels field into LoadTableResponse / LoadViewResponse and their parsers. labels() never returns null (empty instance when absent), on LoadViewResponse via a @Value.Default default method so no interface API break is introduced. Labels are omitted from the wire when absent (or empty), so the change is additive and backward compatible.
Builds on the labels read-path serde: make the catalog-provided labels from the load response reachable by consumers. - New SupportsLabels mixin interface (mirroring SupportsDistributedScanPlanning) with a single labels() accessor. - BaseTable implements SupportsLabels via a new constructor that carries an optional Labels; existing constructors default to an empty instance. The field is transient and not copied into SerializableTable, so labels are ephemeral catalog enrichment and are not preserved across table serialization. - RESTSessionCatalog populates labels from the load response for both the plain BaseTable and the server-side scan-planning RESTTable paths, across loadTable, registerTable, and createTable.
Builds on the SupportsLabels table exposure to make catalog-provided labels
reachable from Spark.
- New LabelsTable metadata table (core): MetadataTableType.LABELS plus a
BaseMetadataTable that flattens a table's labels into rows
{scope, field_id, key, value}. object-level labels use scope "object" with a
null field_id; field-level labels use scope "field". Registered in
MetadataTableUtils, so it is queryable as `SELECT * FROM tbl.labels` (Spark
routes metadata tables generically, no Spark-side change needed).
- Spark BaseSparkTable.properties() surfaces labels under labels.object.* and
labels.field.<id>.* so they appear in DESCRIBE EXTENDED. Driver-side only;
labels are ephemeral catalog enrichment and are not distributed to executors.
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Makes the catalog-provided labels reachable from Spark.
Stacked on the catalog PR (which is stacked on #17337). Review the top commit — the lower layers belong to the parent PRs.
What changed
LabelsTablemetadata table (core):MetadataTableType.LABELSplus aBaseMetadataTablethat flattens a table's labels into rows{scope, field_id, key, value}. Object-level labels use scopeobjectwith a nullfield_id; field-level labels use scopefield. Registered inMetadataTableUtils, so it is queryable asSELECT * FROM tbl.labels(Spark routes metadata tables generically, no Spark-side change needed for query access).BaseSparkTable.properties()surfaces labels underlabels.object.*andlabels.field.<id>.*so they appear inDESCRIBE EXTENDED. Driver-side only; labels are ephemeral catalog enrichment and are not distributed to executors.