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* test(s3tables): expand Dremio Iceberg catalog test coverage
Restructure TestDremioIcebergCatalog into subtests and add three new
checks that go beyond a connectivity smoke test:
- ColumnProjection: SELECT id, label proves Dremio parsed the schema
served by the SeaweedFS REST catalog (the previous SELECT COUNT(*)
passed without exercising any column metadata).
- InformationSchemaColumns: verifies the table's columns are listed in
Dremio's INFORMATION_SCHEMA.COLUMNS in the expected ordinal order.
- InformationSchemaTables: verifies the table is registered in
INFORMATION_SCHEMA.TABLES.
All subtests share a single Dremio container startup, so total
runtime is unchanged.
* test(s3tables): exercise multi-level Iceberg namespaces from Dremio
Seed a 2-level Iceberg namespace (and a table inside it) via the REST
catalog before bootstrapping Dremio, then add a MultiLevelNamespace
subtest that scans the nested table by its dot-separated reference.
This relies on isRecursiveAllowedNamespaces=true (already set in the
Dremio source config) to surface the nested levels as folders. A
regression in either the SeaweedFS namespace path encoding (#8959-style)
or Dremio's recursive-namespace discovery would surface here.
Adds two helpers to keep the existing single-level call sites unchanged:
- createIcebergNamespaceLevels: namespace creation with []string levels
- createIcebergTableInLevels: table creation with []string levels and
unit-separator (0x1F) URL encoding for the namespace path component
* test(s3tables): verify Dremio reads PyIceberg-written rows
The previous Dremio subtests only scanned empty tables, so they did not
exercise the data path - just the catalog/metadata path. Add a
PyIceberg-based writer that materializes parquet files plus a snapshot
on a separate table before Dremio bootstraps, and two new subtests:
- ReadWrittenDataCount: SELECT COUNT(*) returns 3.
- ReadWrittenDataValues: SELECT id, label ORDER BY id returns the three
written rows with the expected (id, label) pairs.
The writer runs in a small image (Dockerfile.writer) built locally on
demand. It pip-installs pyiceberg+pyarrow once and reuses the layer
cache on subsequent runs. The CI workflow pre-pulls python:3.11-slim
to keep cold runs predictable.
The writer authenticates via the OAuth2 client_credentials flow that
SeaweedFS already exposes at /v1/oauth/tokens, mirroring the Go-side
helper used for REST-API table creation.
* test(s3tables): fix Dremio writer required-field schema mismatch
PyIceberg's append() compatibility check rejects an arrow column whose
nullability does not match the Iceberg field. The table schema declares
id as `required long`, but the default pyarrow int64 column is nullable
- so the writer failed with:
1: id: required long vs. 1: id: optional long
Declare an explicit pyarrow schema with nullable=False on id and
nullable=True on label to match the Iceberg side.