lihangyuandClaude Opus 5
e2405875cf
### What problem does this PR solve? Issue Number: None Related PR: #66858 Problem Summary: After #66858 enabled Variant V2 by default, the V1 JSON parser in `be/src/util/json/json_parser.{h,cpp}` (`JSONDataParser`, `ParseConfig`, `ParseResult` and the `getValueAsField`/`writeValueAsJsonb` helpers) has no production caller; only tests still referenced it. This PR removes: - the parser itself (`be/src/util/json/json_parser.{h,cpp}`), including its `extern template class JSONDataParser<SimdJSONParser>` declaration and the matching explicit instantiation; - its dedicated test `be/test/core/jsonb/json_parser_test.cpp`, which covered nothing else; - the stale `#include "util/json/json_parser.h"` lines left in `segment_creator.cpp`, `function_variant_parse.cpp`, `variant_util.cpp`, `cast_to_decimal128_perf.cpp` and `index_storage_test_util.h`; - the never-read `IndexBatch::parse_to` test field (of type `ParseConfig::ParseTo`) and its single assignment in `index_storage_variant_debug_point_test.cpp`. `be/test/util/variant/variant_field_test.cpp` contained one case comparing the V1 parser against the V2 encoder; only its V2 `encode_json` assertions are kept, renamed to `VariantFieldTest.EncodeJsonStableSubset`. `util/json/simd_json_parser.h` and `util/json/path_in_data.{h,cpp}` are kept, as both still have production users. Note: `be/benchmark/benchmark_variant_segment.hpp` also references `ParseConfig`, but its V1 branch already fails to compile on master (it calls `ColumnVariant`, `variant_util::parse_json_to_variant` and `variant_util::select_storage_variant_parse_target`, none of which exist any more). It is built only with the BE benchmark target and is left for a separate fix. ### Release note None ### Check List (For Author) - Test: Unit Test - `build-support/check-build-hygiene.sh` passed - ASAN BE build (`./build.sh --be`) passed - `./run-be-ut.sh --run --filter='VariantFieldTest.*:IndexStorage*'` passed: 83 passed, 2 pre-existing skips - Behavior changed: No - Does this need documentation: No 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-authored-by: Claude Opus 5 <noreply@anthropic.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