TypeError: argument of type 'azureml.dataprep.rslex.StreamInfo' is not iterable

Hi, I encountered below error, I have azureml-opendatasets==1.55.0

Calling to_spark_dataframe()
Traceback (most recent call last):
File "/mnt/c/users/cruiseli/OneDrive - Microsoft/Desktop/workspace/SynapseML-Utils/test_aml.py", line 30, in
nyc_tlc_df2 = nyc_tlc.to_spark_dataframe()
File "/home/cruise/mambaforge/lib/python3.10/site-packages/azureml/opendatasets/accessories/_loggerfactory.py", line 139, in wrapper
return func(*args, **kwargs)
File "/home/cruise/mambaforge/lib/python3.10/site-packages/azureml/opendatasets/accessories/open_dataset_base.py", line 164, in to_spark_dataframe
return self._to_spark_dataframe()
File "/home/cruise/mambaforge/lib/python3.10/site-packages/azureml/opendatasets/accessories/open_dataset_base.py", line 305, in _to_spark_dataframe
return self._blob_accessor.get_spark_dataframe(
File "/home/cruise/mambaforge/lib/python3.10/site-packages/azureml/opendatasets/dataaccess/_blob_accessor.py", line 303, in get_spark_dataframe
paths = [wasab_format % (self._blob_container_name, self._blob_account_name,
File "/home/cruise/mambaforge/lib/python3.10/site-packages/azureml/opendatasets/dataaccess/_blob_accessor.py", line 304, in
self._get_relative_path(path)) for path in target_paths]
File "/home/cruise/mambaforge/lib/python3.10/site-packages/azureml/opendatasets/dataaccess/_blob_accessor.py", line 470, in _get_relative_path
if "blob.core.windows.net" in url:
TypeError: argument of type 'azureml.dataprep.rslex.StreamInfo' is not iterable

Code to reproduce:
```
import azureml.core
from azureml.core import Datastore, Dataset
from azureml.core.workspace import Workspace
from azureml.core.experiment import Experiment
from azureml.core.authentication import InteractiveLoginAuthentication

import logging
import pandas as pd
import time
import sys

print("Testing opendatasets -- start")
from azureml.opendatasets import NycTlcYellow
from datetime import datetime
from dateutil import parser

end_date = parser.parse('2018-05-30')
start_date = parser.parse('2018-05-28')
nyc_tlc = NycTlcYellow(start_date=start_date, end_date=end_date)

print("Calling to_pandas_dataframe()")
ts = time.time()
nyc_tlc_df = nyc_tlc.to_pandas_dataframe()
te = time.time()
print("Time taken to perform to_pandas_dataframe():" + str(te-ts))

print("Calling to_spark_dataframe()")
ts2 = time.time()
nyc_tlc_df2 = nyc_tlc.to_spark_dataframe()
te2 = time.time()
nyc_tlc_df2.show(2, truncate = False)
print("Time taken to perform to_spark_dataframe():" + str(te2-ts2))

print("Testing opendatasets -- end")
```

先使用 azureml-opendatasets==1.55.0 執行提供的 NycTlcYellow 重現，然後檢查 azureml/opendatasets/dataaccess/_blob_accessor.py，尤其是 get_spark_dataframe 和 _get_relative_path。追蹤 target_paths 包含 StreamInfo 的原因，並比較 pandas 和 Spark 路徑；當 to_spark_dataframe 在沒有發生所回報的 TypeError 的情況下完成時，即表示完成。

由索引模型根據 Issue 內容生成。