f109e130f7
### What problem does this PR solve? Related to #67578 (partial A3). Flight SQL clients can obtain FlightInfo for GetTableTypes, but reading its ticket fails with UNIMPLEMENTED. GetTables also forwards only the first table_types entry to a service that treats only VIEW as a filter: [VIEW, BASE TABLE] loses base tables, while [BASE TABLE] or an unknown type can return excluded rows. Implement the type stream using the same Doris names as GetTables (BASE TABLE, SYSTEM VIEW and VIEW), sorted according to Flight SQL. Match the complete filter against the existing authorized listing before collecting optional schemas. Request only name/type metadata to avoid unused table statistics, and retain the session guard and Arrow buffer cleanup on failed sends. A type is the TABLE_TYPE that information_schema.tables reports for the object: table streams are VIEW, and external catalogs report their tables and views as BASE TABLE. The service lists every authorized object and the filter runs on that listing. Requested names match case-insensitively, and TABLE and SYSTEM TABLE, which Flight SQL calls commonly supported, select BASE TABLE and SYSTEM VIEW: the ADBC Flight SQL driver asks for `table` (Doris's own ADBC catalog lists a Doris source with `getObjects(..., {"table"})`), and JDBC tools ask for `TABLE`. Any other name matches only a type of that name, so UNKNOWN selects nothing. Because the filter now runs on the full listing, `FrontendServiceImpl.listTableStatus` refreshes a cloud follower's partition versions from the meta service only when UPDATE_TIME is requested, the one column that reads them. GetTables, which asks for names and types, never waits on those RPCs or is cut short when they fail, and information_schema.tables scans that do not read UPDATE_TIME skip the refresh too. Co-authored-by: morningman <yunyou@selectdb.com> Co-authored-by: Gabriel <liwenqiang@selectdb.com>
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Apache Doris is an open-source, real-time analytics and search database built on MPP architecture. It provides fast SQL analytics, lakehouse query acceleration, and hybrid search across structured, text, and vector data.
Explore the official website for the latest product overview, use cases, ecosystem updates, blogs, and user stories. For version updates, see all release notes.
📈 Use Cases
| Use Case | What it provides |
|---|---|
| Customer-Facing Analytics | Ship sub-second interactive analytics to external users. |
| Data Warehousing | Build one real-time warehouse across business domains. |
| Observability | Analyze high-throughput logs, events, and metrics with SQL. |
| Doris for AI | Use vector, text, JSON, and structured search in one SQL engine. |
🚀 Core Capabilities
Apache Doris is built around three core capabilities. The website is the source of truth for detailed product descriptions and examples.
| Capability | What it provides |
|---|---|
| Real-Time Analytics | Streaming ingestion, incremental transformation, and sub-second queries under high concurrency. |
| Lakehouse Analytics | Fast SQL analytics over open table formats such as Iceberg, Delta Lake, and Hudi. |
| Hybrid Search | SQL-native analytics across JSON, full-text, and vector data for AI and search workloads. |
🔌 Ecosystem
Doris sits at the center of the modern data stack. It connects upstream databases, streaming systems, and lakehouse storage with downstream BI, AI, analytics, and observability tools.
For the latest ecosystem coverage, visit the official website and the connection and integration documentation.
👣 Get Started
🧱 Architecture
Apache Doris supports both compute-storage coupled and compute-storage decoupled deployments. In decoupled mode, stateless compute groups run over shared object storage, so you can scale compute on demand and isolate workloads.
Learn more in the deployment guide and deployment mode guide.
📣 Project Updates
| Resource | What it provides |
|---|---|
| Community Report | Weekly updates on community activity, merged PRs, contributors, and feature progress. |
| Roadmap 2026 | The 2026 planning discussion for AI and hybrid search, query engine, storage, and data lake work. |
🧩 Components
Doris provides connectors and tools for common data engineering workflows.
- Doris Flink Connector
- Doris Spark Connector
- Doris Kafka Connector
- Doris Stream Loader
- Doris Kubernetes Operator
👨👩👧👦 Users
Apache Doris is used in production by thousands of companies worldwide across internet services, finance, retail, logistics, manufacturing, energy, telecommunications, AI, and other industries.
🙌 Contributors
Apache Doris graduated from the Apache Incubator and became an Apache Top-Level Project in June 2022. Thanks to all community contributors who help build Doris.
🌈 Community and Support
💬 Contact Us
🧰 Links
- Apache Doris official website: doris.apache.org
- X: @doris_apache
- Medium: @ApacheDoris
📜 License
Note
Some licenses of the third-party dependencies are not compatible with Apache 2.0 License. So you need to disable some Doris features to comply with Apache 2.0 License. For details, refer to the
thirdparty/LICENSE.txt