Debut some issues in aurora dataloader

        "WALLTIME_SECONDS", "RUNTIME_SECONDS", "USERNAME_GENID", "LOCATION"

    ]

    for chunk in pd.read_csv(filepath, chunksize=chunksize, on_bad_lines='warn'):

    for chunk in pd.read_csv(filepath, chunksize=chunksize, on_bad_lines='warn', nrows=100):

        # Drop rows where essential timestamp data is missing

        chunk.dropna(subset=['QUEUED_TIMESTAMP', 'START_TIMESTAMP', 'END_TIMESTAMP'], inplace=True)

        for _, row in chunk.iterrows():

            try:

            submit_time = int(pd.to_datetime(row["QUEUED_TIMESTAMP"]).timestamp())

            start_time = int(pd.to_datetime(row["START_TIMESTAMP"]).timestamp())

            end_time = int(pd.to_datetime(row["END_TIMESTAMP"]).timestamp())

                nodes_required=int(row.get("NODES_REQUESTED", 0)),

                cpu_cores_required=int(row.get("CORES_REQUESTED", 0)),

                account=str(row.get("USERNAME_GENID", "N/A")),

                    scheduled_nodes=str(row.get("LOCATION", "")).split(','),

                #scheduled_nodes=str(row.get("LOCATION", "")).split(','),

                scheduled_nodes=[], #str(row.get("LOCATION", "")),

                # The following are placeholders as they are not in the CSV

                gpu_trace=0,

                cpu_trace=0,

                trace_quanta=1,

            )

            jobs.append(Job(job))

            except (ValueError, TypeError) as e:

                print(f"Skipping row due to parsing error: {e}. Row: {row}")

                continue

    if not jobs:

        return WorkloadData(jobs=[], telemetry_start=0, telemetry_end=0, start_date=datetime.now(timezone.utc))