Key not found "ADLSGen2" when using `to_spark_dataframe`

I'm creating a dataset directly using a URL (relying on identity-based access):
```python
dataset = Dataset.Tabular.from_parquet_files("https://.dfs.core.windows.net/")
```
(This prompts my browser to start a login-process.)

While `dataset.to_pandas_dataframe()` works fine, when I try `dataset.to_spark_dataframe()` I get the following Java traceback:
```
: java.util.NoSuchElementException: key not found: ADLSGen2
at scala.collection.MapLike.default(MapLike.scala:235)
at scala.collection.MapLike.default$(MapLike.scala:234)
at scala.collection.AbstractMap.default(Map.scala:63)
at scala.collection.MapLike.apply(MapLike.scala:144)
at scala.collection.MapLike.apply$(MapLike.scala:143)
at scala.collection.AbstractMap.apply(Map.scala:63)
at com.microsoft.dprep.io.StreamInfoFileSystem$.toFileSystemPath(StreamInfoFileSystem.scala:68)
at com.microsoft.dprep.execution.Storage$.expandHdfsPath(Storage.scala:37)
at com.microsoft.dprep.execution.executors.GetFilesExecutor$.$anonfun$getFiles$1(GetFilesExecutor.scala:18)
at scala.collection.TraversableLike.$anonfun$flatMap$1(TraversableLike.scala:245)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at scala.collection.TraversableLike.flatMap(TraversableLike.scala:245)
at scala.collection.TraversableLike.flatMap$(TraversableLike.scala:242)
at scala.collection.AbstractTraversable.flatMap(Traversable.scala:108)
at com.microsoft.dprep.execution.executors.GetFilesExecutor$.getFiles(GetFilesExecutor.scala:12)
at com.microsoft.dprep.execution.LariatDataset$.getFiles(LariatDataset.scala:32)
at com.microsoft.dprep.execution.PySparkExecutor.getFiles(PySparkExecutor.scala:225)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:566)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.base/java.lang.Thread.run(Thread.java:834)
```
This is using "com.microsoft.ml.spark:mmlspark_2.12:1.0.0-rc3-62-25d40cff-SNAPSHOT" and PySpark 3.1.2.

What might cause this error?

The Java code is called from a generated Python module which shows where the "ADLSGen2" key comes from:

```python
# ...
lds0 = jex.getFiles(
[{"searchPattern":"https://.dfs.core.windows.net/",
"handler":"ADLSGen2",
"arguments":{"credential":""}
}],
secrets
)
# ...
```

Start with the generated Python getFiles call containing handler ADLSGen2 and the traceback entry StreamInfoFileSystem.toFileSystemPath. Trace how that handler is registered for the stated Spark and mmlspark versions. Done means the cause is confirmed and to_spark_dataframe works with the identity-based URL.

Escrita pelo modelo de indexação a partir do texto da issue.