# 缓存预加载

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[文件分割](/ee-ai-cn/ai-3.4/feature/file-segmentation.md) 和[多重复制](/ee-ai-cn/ai-3.4/feature/file-replication.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-3.4/reference/user-cli.md) 文档。

### REST API

与 CLI 类似，REST API 也可用于加载数据。 请求直接发送到coordinator。

```shell
curl -H "Content-Type: application/json"  -v -X POST http://coordinator_host:19999/api/v1/master/submit_job/load -d '{
    "path": "s3://alluxiow/testm/dir-1/",
    "options": {
         "replicas":"2",
         "batchSize": "300",
         "partialListing": "true",
         "loadMetadataOnly": "true",
         "skipIfExists": "true"
    }
}'
```

可以通过发送路径相同的 GET 请求查询参数来检查进度。

```shell
curl -H "Content-Type: application/json"  -v -X GET http://coordinator_host:19999/api/v1/master/progress_job/load -d '{
  "path or indexFile": "s3://bucket/dir-1/",
  "format": "TEXT[default] | JSON",
  "verbose": "true"
}'
```

可以通过相同路径发送 POST 请求来终止加载操作。

```shell
curl -H "Content-Type: application/json"  -v -X POST http://coordinator_host:19999/api/v1/master/stop_job/load -d '{
  "path || indexFile": "s3://alluxiow/testm/dir-1/"
}'
```

查询load任务列表。

```shell
curl http://ip:1999/api/v1/master/list_job?[job-type=LOAD[&job-state=[RUNNING|VERIFYING|STOPPED|SUCCEEDED|FAILED|ALL]]
```


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