# 缓存加载

分布式加载允许用户高效地将数据从 UFS 加载到 Alluxio 集群。\
这可用于初始化 Alluxio 集群，以便在 Alluxio 上运行工作负载时能够立即提供缓存数据。\
例如，分布式加载可用于为机器学习作业预取数据，从而加快训练过程。\
分布式加载可利用[文件分片](https://documentation.alluxio.io/ee-ai-cn/ai-3.6/cache/pages/8hnuhjhRC07I02AVyrEw#大文件分段)\
和[多副本](/ee-ai-cn/ai-3.6/data-access/high-availability/multiple-replicas.md)来加强高并发数据访问场景中的文件分发。

## 使用方法

有两种触发分布式加载的推荐方法：

### 任务加载 CLI

`任务加载`命令可用于将数据从 UFS（底层文件系统）加载到 Alluxio 集群。\
CLI 会向 Alluxio coordinator 发送加载请求，coordinator 随后会将加载操作分发到所有 worker 节点。

```shell
bin/alluxio job load [flags] <path>

# 输出示例
Progress for loading path '/path':
        Settings:       bandwidth: unlimited    verify: false
        Job State: SUCCEEDED
        Files Processed: 1000
        Bytes Loaded: 125.00MB
        Throughput: 2509.80KB/s
        Block load failure rate: 0.00%
        Files Failed: 0
```

有关 CLI 的详细用法，请参阅 [job load](/ee-ai-cn/ai-3.6/reference/user-cli.md) 文档。

### REST API

与命令行工具类似，REST API 也可用于加载数据。\
请参阅 API 参考页面以获取更多详细信息。\
请注意，任务列表结果仅包含七天内的加载任务。历史任务的保留时间可以通过配置项 `alluxio.job.retention.time` 进行设置。


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