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test/s3tables/catalog_doris/README.md

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+# Apache Doris Iceberg Catalog Integration Test
+
+This directory contains an Apache Doris integration smoke test for SeaweedFS's
+Iceberg REST Catalog implementation.
+
+## What It Tests
+
+`TestDorisIcebergCatalog` verifies the Doris path end to end:
+
+1. Starts a local SeaweedFS mini cluster with S3 Tables and Iceberg REST enabled.
+2. Creates a SeaweedFS table bucket.
+3. Creates an Iceberg namespace and an empty table through the SeaweedFS REST
+   catalog OAuth flow.
+4. Creates a second table and populates it with three rows by running a
+   PyIceberg writer container (`Dockerfile.writer` + `append_rows.py`) before
+   Doris bootstraps, so the snapshot is part of Doris's first scan.
+5. Starts `apache/doris:doris-all-in-one-2.1.0` and waits for the FE MySQL
+   query port and at least one alive BE.
+6. Connects to Doris over the MySQL protocol and registers a Doris
+   `EXTERNAL CATALOG` of `type=iceberg` and `iceberg.catalog.type=rest` that
+   points at the SeaweedFS REST endpoint, using `credential = key:secret` for
+   the OAuth2 client-credentials flow.
+7. Runs subtests against the SeaweedFS-backed Iceberg tables:
+   - `BasicSelect`: Doris is alive and answering SQL.
+   - `CatalogVisible`: `SHOW CATALOGS` lists the SeaweedFS-backed catalog.
+   - `DatabaseVisible`: the seeded namespace is exposed as a Doris database.
+   - `TableVisible`: the seeded table appears under `SHOW TABLES FROM ...`.
+   - `CountEmptyTable`: catalog-to-table resolution and a scan of an empty table.
+   - `ColumnProjection`: `SELECT id, label` succeeds and the response columns
+     are `id, label`. Failure here means Doris could not parse the schema
+     returned by the SeaweedFS catalog.
+   - `ReadWrittenDataCount` and `ReadWrittenDataValues`: Doris reads back the
+     three PyIceberg-appended rows and the values match. This exercises the
+     actual data path (parquet reads via S3), not just metadata.
+
+The PyIceberg writer image is built on demand via Docker layer caching. The
+first build pulls `python:3.11-slim` and pip-installs PyIceberg + PyArrow
+(~1-2 min in CI); subsequent invocations are cheap.
+
+## Running Locally
+
+Build or install `weed`, then run:
+
+```bash
+cd test/s3tables/catalog_doris
+go test -v -timeout 25m .
+```
+
+The test requires Docker. The GitHub Actions job runs on `ubuntu-22.04` and
+executes the test for pull requests.
+
+## Configuration
+
+The test uses these fixed credentials for the local SeaweedFS IAM config:
+
+- S3 access key: `AKIAIOSFODNN7EXAMPLE`
+- S3 secret key: `wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY`
+- Region: `us-west-2`
+- Warehouse bucket: `iceberg-tables`
+
+Doris ports:
+
+- The all-in-one container exposes `9030` (FE MySQL/SQL) and `8030` (FE HTTP).
+  Only `9030` is mapped to a host port (allocated dynamically) so the Go
+  MySQL client can connect from the test process.
+- The Iceberg REST endpoint and the S3 endpoint are reached from inside the
+  Doris container via `host.docker.internal`, matching the Trino and Dremio
+  test paths.
+
+## Troubleshooting
+
+- Ensure Docker is running: `docker version`
+- Ensure `weed` is built or available on `PATH`
+- The Doris all-in-one image is large (~1 GB) and the FE+BE need
+  ~30-60 seconds to register before queries succeed; the test waits up to
+  4 minutes for the query port and 60 seconds for at least one alive BE.
+- If queries hang on metadata, run `REFRESH CATALOG iceberg_catalog` from a
+  Doris MySQL client and retry.
+- Container logs are printed in the failure message; you can also check
+  `docker logs <seaweed-doris-...>` while the test is running.