Mingyu Chen (Rayner) 339e087b11 [fix](be) Reject incompatible Arrow arrays without crashing Stream Load (#69872)
### What problem does this PR solve?

Issue Number: close #69858

Related PR: None

Problem Summary:

The shared Arrow BOOLEAN and DECIMAL SerDes dereference unchecked
`dynamic_cast` results. Passing an `Int32Array` to the BOOLEAN reader or
a `StringArray` to the DECIMAL64 reader can therefore terminate the BE
instead of returning a load error. MAP and STRUCT have the same
unchecked input-cast pattern.

Reject incompatible arrays before accessing buffers, decimal metadata,
or values, independently of `enable_arrow_input_validation`. Reject
mismatched STRUCT field counts before indexing children. Add the column
name and source/destination types to V1/V2 Arrow load errors.

The current V2 Stream Load reader already binds supported input types
with safe Arrow casts. Preserve those conversions, including valid
integer-to-BOOLEAN and string-to-DECIMAL inputs, and test the shared
SerDes directly for incompatible arrays.
2026-10-31 10:14:43 +08:00
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Apache Doris

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apache%2Fdoris | Trendshift

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.

Apache Doris ecosystem

For the latest ecosystem coverage, visit the official website and the connection and integration documentation.

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🧱 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.

Apache Doris compute-storage decoupled architecture

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.

👨‍👩‍👧‍👦 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.

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📜 License

Apache License, Version 2.0

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

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