Gabriel
ec7f806fa3
### What problem does this PR solve? Issue Number: N/A Related PR: #69672, #69723 External ES regression suites fail during setup or retain expectations from the previous indexed-value predicate behavior: - Read the deprecated scanner option through `SELECT @@enable_file_scanner_v2`, whose compatibility name remains valid when SHOW prefixes deprecated names. - On ES 8.3.3, fall back from the specifically unsupported `_source.mode` mapping syntax to `enabled:false`, retaining the disabled-source row and alias checks. Other HTTP failures remain fatal; supporting ES8 versions still exercise the mode syntax. - Compare LIKE, REGEXP, NULL and `level` predicates against unfiltered rows materialized into internal tables, then update only the affected runner-generated golden blocks. - Make the date-string equality test explicitly use source reads, test midnight as the matching value, and retain 08:00 as a negative control. - Check that a residual predicate prevents early termination while a safe numeric docvalue predicate still permits LIMIT pushdown. ### Release note None ### Check List (For Author) - Test - [x] Regression test - [ ] Unit Test - [x] Manual test Validation uses fresh FE and ASAN BE artifacts built from this PR commit (`6386f5f83a51b548c86ab3cff83d53cb48fb18df`) with the standard `./build.sh --fe --be -j64` entry point. The complete build exited successfully, and both finished artifact versions match that commit. No production source is changed by this PR. - On the same fresh binaries and reset ES 5.6.16, 6.8.23, 7.17.5 and 8.3.3 fixtures, the parent suites/golden files reproduced all ten failures; the final PR suites passed all ten in normal comparison, with zero failed, fatal or skipped suites. The passing run executed 2,154 golden checks and 1,798 independent query comparisons, without force-generation or further golden edits. - The complete `test_es_query` passed all four ES versions and both scroll settings, including its unchanged complex-array golden blocks (276 result checks and 20 independent comparisons). - Independent SQLite/Python evaluation of the unchanged raw fixture JSON passed 38 comparisons and covered all 17 changed golden blocks. Real ES requests also confirmed that `ignore_above` omits matching index values while retaining source strings, and that the constant-keyword index matches documents whose source `level` is absent. - Captured ES search requests verified the date modes: the original four-column projection reads source, returns midnight values and rejects the 08:00 predicate. A date-only docvalue projection correctly returns 08:00 in the +08:00 session. The revised test explicitly fixes the source contract and retains the 08:00 negative control. - The complete fallback suite additionally passed normal comparison on ES 8.11.3: 304 golden checks and 304 independent comparisons. The actual mappings and document responses confirmed absent source for both the ES 8.3.3 `enabled:false` fallback and the supported ES 8.11.3 `mode:disabled` branch. - The existing `test_es_file_scanner_v2` compatibility suite also passed on the fresh build across all four fixture versions. The deprecated option is accepted; this does not claim two distinct physical reader implementations on current master. - Direct variable probes confirmed the old exact SHOW name returns no rows, the wildcard SHOW name exposes its deprecated prefix, and the scalar compatibility name remains readable. - `git diff --check` passed. ES9 compatibility is not claimed. - Behavior changed: - [x] No production behavior change; regression fixtures and expectations are corrected. - [ ] Yes. - Does this need documentation? - [x] No. - [ ] Yes. ### Check List (For Reviewer who merge this PR) - [ ] Confirm the release note - [ ] Confirm test cases - [ ] Confirm document - [ ] Add branch pick label
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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