linrrarity
bc86a22d6f
Related PR: #63143 Problem Summary: The BE build previously configured and installed datasketches-cpp from `contrib/datasketches-cpp` into `thirdparty/installed` before configuring the BE itself. Its CMake cache was stored under `contrib/datasketches-cpp/build/Release`, which was **NOT** managed by `clean_be()`. As a result, `build.sh --be --clean` could still fail before reaching `clean_be()` when the cached compiler path belonged to another workspace or no longer existed. ```text install datasketches-cpp to thirdparty path before build be Update datasketches-cpp submodule ... /mnt/disk9/linzhenqi/d1/doris Current commit ID of datasketches-cpp submodule: de8553ba372e618382c2e7b44b0ffc9422b9458c, expected is de8553ba372e618382c2e7b44b0ffc9422b9458c -- The CXX compiler identification is unknown CMake Error at CMakeLists.txt:25 (project): The CMAKE_CXX_COMPILER: /mnt/disk7/linzhenqi/dv/version-toolchain/ldb_toolchain_v28/bin/clang++ is not a full path to an existing compiler tool. Tell CMake where to find the compiler by setting either the environment variable "CXX" or the CMake cache entry CMAKE_CXX_COMPILER to the full path to the compiler, or to the compiler name if it is in the PATH. -- Configuring incomplete, errors occurred! ``` The standalone installation also mixed a contrib dependency into the thirdparty installation directory without using the thirdparty build lifecycle. ### Release note - Keep datasketches-cpp as a contrib submodule. - Add datasketches-cpp to the BE CMake build tree with `add_subdirectory`. - Link `Exprs` against the upstream `DataSketches::HLL` interface target. - Mark the datasketches include directories as system headers so upstream warnings are not promoted to errors by Doris's `-Werror` settings. - Use the upstream build-tree include path for `hll.hpp`. - Remove the standalone CMake configure/install commands from `build.sh`. - Remove the now-unused `TP_INSTALLED_DIR` variable. The datasketches CMake state is now stored under the BE build directory and is removed together with the rest of the BE build artifacts by `clean_be()`.
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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