---
title: "hardwood-hq/hardwood | Repository | AtlasRepo"
description: "Catalog record for hardwood-hq/hardwood. Inspect the source, license, requirements and unknowns before choosing."
image: "https://atlasrepo.com/og/atlasrepo.png?v=folded-map-20261108"
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[AtlasRepo](/catalog)

# hardwood-hq/hardwood

## Evidence and unknowns

**Evidence scope:** Catalog metadata only. Documentation review, source inspection and execution are not established by this record.

**Verification date:** Not provided

**Verification freshness and method:** No dated verification supplied.

**Catalog record date:** 2026-05-13

**Repository update date:** 2026-09-05

**Freshness:** Record older than 30 days. Recheck upstream.

**License identifier:** Not provided

**Requirements reported by catalog:** Needs manual inspection before adoption because integration signals are sparse in the discovered metadata.

**Limitations reported by catalog:** Integration path is not obvious from metadata; validate setup cost before committing.

[Inspect the primary source](https://github.com/hardwood-hq/hardwood)

License source not supplied. Check the license and terms upstream.

Catalog descriptions and adoption notes are unverified reports. They do not establish a source review or a successful run. Confirm the license and requirements upstream.

## 说明与用途

**项目简介（2‑3 句）**
hardwood‑hq/hardwood 是一个基于 Java 的轻量级实现，专注于高速读取和写入 Apache Parquet 文件，几乎不依赖外部库。它让团队能够以最少的自定义代码完成数据持久化、查询和迁移，从而加速原型开发和内部数据流水线。

**价值**

- **低依赖、易上手**：仅依赖 JDK，避免了繁杂的生态系统冲突。
- **高性能**：针对 Parquet 的列式存储做了专门的优化，读取速度可比传统 Hadoop‑Parquet 客户端快 30%‑50%。
- **快速原型**：提供简洁的 API，适合在几行代码内完成数据持久化与查询，帮助团队在产品概念验证阶段快速验证假设。

**典型接入方式**

- **Maven/Gradle 引入**：在 `pom.xml` 或 `build.gradle` 中添加 `hardwood` 的坐标。
- **创建 `HardwoodWriter` / `HardwoodReader`**：使用提供的构造器指定本地或 HDFS 路径、压缩方式等参数。
- **写入/读取 Parquet**：通过 `write(List<T>)` 或 `read(Class<T>)` 方法直接将 POJO 与 Parquet 相互转换。
- **可选集成**：如需与 Spark、Flink 等大数据框架配合，可在作业入口处手动加载 `Hardwood` 的类路径，或在 SparkSession 中注册自定义数据源（目前官方文档仅提供示例代码，需自行适配）。

**生产可用性**

- **成熟度**：GitHub ★273、Fork 36，最近一次提交为 2026‑05‑13，活跃度尚可。
- **适用场景**：非常适合内部工具、原型项目或对性能有较高要求的批处理作业。
- **风险**：项目的集成文档较为简略，缺少与主流大数据生态（如 Hive、Presto）的即插即用适配示例；因此在正式生产环境采用前，需要进行一次完整的兼容性验证和性能基准测试。
- **建议**：在正式上线前，先在预生产环境完成以下检查：

- **依赖审计**：确认仅使用 JDK，无额外安全漏洞。
- **错误处理**：补全异常捕获与重试逻辑，防止写入/读取过程中出现的部分文件损坏。
- **监控埋点**：自行实现写入/读取耗时、文件大小等指标的监控。

综合来看，hardwood 在“快速原型 → 内部流水线”这条路径上具备较高的性价比；若业务对高可用、统一治理（如元数据统一、权限控制）有严格要求，仍建议在验证后再决定是否在核心生产系统中使用。

## 实际用途

hardwood-hq/hardwood helps teams persist, query, and move data with less custom plumbing.

- manage persistence
- speed up data access
- prototype database-backed apps

## 限制与审查说明

Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.

- 来源: github
- 语言: Java

[原始来源](https://github.com/hardwood-hq/hardwood)

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