# Cache Loading

Distributed load allows users to load data from UFS to Alluxio cluster efficiently.\
This can be used to initialize the Alluxio cluster to be able to immediately serve cached data when running workloads on top of Alluxio. For example, distributed load can be used to prefetch data for machine learning jobs, speeding up the training process.\
Distributed load can utilize [file segmentation](/ee-ai-en/ai-3.6/data-access/performance/file-reading.md) and [multi-replication](/ee-ai-en/ai-3.6/data-access/high-availability/multiple-replicas.md) to enhance file distribution in scenarios with highly concurrent data access.

## Usage

There are two recommended ways to trigger distributed load:

### job load CLI

The `job load` command can be used to load data from UFS (Under File System) to the Alluxio cluster.\
The CLI sends a load request to the Alluxio coordinator, which subsequently distributes the load operation to all worker nodes.

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

# Example output
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
```

For detailed usage of CLI, please refer to the [job load](/ee-ai-en/ai-3.6/reference/user-cli.md) documentation.

### REST API

Similar to the CLI, the REST API can also be used to load data.

Please refer to the [API reference page](/ee-ai-en/ai-3.6/reference/rest-api.md#Distributed-Load) for more details.

Note that the list results only include load tasks within seven days. The residence time of historical tasks can be configured through `alluxio.job.retention.time`.


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