Socrates
b5996fbf10
### What problem does this PR solve? Related PR: #69493 Problem Summary: Master still builds paimon-rust v0.4.0-rc1, while the Paimon vector-search work in #69493 needs v0.5.0-rc1 and additional wire fields. Upgrade the native dependency and reserve its Thrift layout on master so later changes cannot reuse the same identifiers for different meanings. The dependency change updates the source URL, archive name, source directory and MD5 checksum together. The schema change adds the following optional fields and their Paimon payload/options types: | Structure | Field | ID | | --- | --- | --- | | `TPaimonFileDesc` | `vector_payload` | 24 | | `TExternalSearchRequest` | `paimon_options` | 6 | | `TFileScanRangeParams` | `external_search_request` | 42 | `TPaimonVectorPayloadType` keeps `BUCKET_SPLIT_BYTES=0` and `MATERIALIZE_OPAQUE_BYTES=1`. Both payload members and all Paimon search-option members are optional. Master does not emit these fields yet; this PR reserves the protocol without enabling SQL/TVF ANN search or upgrading the Paimon Java SDK. Compatibility notes: - `TPaimonFileDesc.20` remains `original_file_path`; comments reserve branch-4.1's `blob_files=21`, `anchor_first_row_id=22` and `anchor_row_count=23`. The vector payload uses 24 rather than the conflicting 21 from the original #69493 diff. - Comments reserve the existing branch-4.1/4.2 shared-search fields `search_query=2`, `search_filter=3`, `vector_search_options=4` and `prefilter=5`. Their query types can be introduced independently on master. - `TFileScanRangeParams.41` remains `fluss_properties`. - The affected definitions were reviewed against current master and branches 3.1, 4.0, 4.1 and 4.2. Existing field IDs and enum values retain their meanings. ### Release note Upgrade the native Paimon Rust reader dependency to v0.5.0-rc1. ### Check List (For Author) - Test: No local build, Thrift generation or unit tests on master, as requested; CI validation pending. During the preceding branch-4.2 work, the archive checksum was verified and the v0.5.0-rc1 dependency was built with Rust 1.94.0. This is not a completed master BE build or BE unit-test run. - Behavior changed: Yes; the bundled native Paimon dependency is upgraded. The new Thrift fields are reserved and remain unset by master producers. - Does this need documentation: No
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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