input data to spark job is not passed to job

### Operating System

Linux

### Version Information

az --version
ml 2.28.0

### Steps to reproduce

1. I am trying to submit a spark job as shown in https://github.com/Azure/azureml-examples/tree/main/cli/jobs/spark

2. The data has been uploaded as described here: https://github.com/Azure/azureml-examples/blob/main/cli/jobs/spark/data/README.md

3. This is the yml definition (partially shown)
```
$schema: https://azuremlschemas.azureedge.net/latest/sparkJob.schema.json
resources:
instance_type: standard_e4s_v3
runtime_version: "3.3"
type: spark
conf:
spark.driver.cores: 1
spark.driver.memory: 2g
spark.executor.cores: 2
spark.executor.memory: 2g
spark.executor.instances: 2
inputs:
input_data_step1:
type: uri_file
path: azureml://datastores/workspaceblobstorex/paths/data/titanic.csv
mode: direct
args: >-
--input_data_step1 ${{inputs.input_data_step1}}

```

4. The overview in the AML Studio shows the correct input data and I can navigate to it.

5. Now the issue: Inside my job which runs without problems the input data argument is expanded to something like:
/mnt/var/hadoop/tmp/nm-local-dir/usercache/trusted-service-user/appcache/application_1724844698277_0001/container_1724844698277_0001_01_000001/azureml:/subscriptions/xxxxxx/resourcegroups/weg-aml-v2/workspaces/weg-aml-v2/datastores/workspaceblobstore/paths/data/titanic.csv

However this path does not exist.
There is no indication in the logs what failed.

### Expected behavior

The input data should be passed to the spark application, such that it can be accessed.

### Actual behavior

The issue is that the input data is not passed to the spark application.

Inside the spark application which runs without problems the input data argument is expanded to something like:
/mnt/var/hadoop/tmp/nm-local-dir/usercache/trusted-service-user/appcache/application_1724844698277_0001/container_1724844698277_0001_01_000001/azureml:/subscriptions/xxxxxx/resourcegroups/weg-aml-v2/workspaces/weg-aml-v2/datastores/workspaceblobstore/paths/data/titanic.csv

However this path does not exist.
There is no indication in the logs what failed.

### Addition information

_No response_

Start with the Spark example under cli/jobs/spark and its data/README.md, then submit the YAML shown in the report and inspect the input-related job and application logs. Compare the resolved input argument with the documented data-upload flow; done means the Spark application receives a path it can access rather than a nonexistent azureml-prefixed local path.

Written by the indexing model from the issue text.