Jack
a47d4613d2
### What problem does this PR solve? Issue Number: None Related PR: None Problem Summary: DorisSniiFileReader::read_batch submits every physical segment of a batch with more than one segment to the shared buffered-reader prefetch thread pool and waits on a latch. When the index file is in the page cache the reads take microseconds and 99% of the batches of a phrase workload are under 256 KB, so the submit, wake-up and wait cost more than the reads, and a query that issues thousands of batches from 16 scanner threads queues on the pool's lock. On 99M AgentLogs rows, 83% of the threads inside the SNII query path were blocked in ThreadPool::do_submit for the date-range phrase query. A batch of at most config::snii_inline_read_max_segments (default 4, 0 disables) segments and 256 KiB is now read on the calling thread when the index file is on the local filesystem and the moving average of recent small physical reads is below 20 us. Remote and cached-remote readers, larger batches and slow (page-cache miss) reads still fan out to the pool, because overlapping disk reads gain from it: with a fixed rule instead of the average, the cold run of two phrase queries was 4-8% slower. The serial read rounds counter counts one round per segment for a batch read inline. Measured on 99M AgentLogs rows (branch-4.2 build; the changed code is the same on master), same process, 25 queries, inline off against on, 16 samples each: date-range phrase query 0.39x, any-of-three-phrases top-N 0.70x, no query above 1.02x. Cold runs (restart, page cache evicted, three repetitions) of eight queries are within 2% of the pool.
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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