h3 index converted to Geocoordinates: how to export to geojson

从 H3.instance.h3ToGeoBoundary 入口点以及 issue 中的两个 Spark UDF 示例开始，包括针对 List 的 UnsupportedOperationException。确定 GeoJSON、GeoMesa 或 GeoSpark 的预期表示形式，并将完成定义为：提供一种受支持且有文档说明的方式来处理多个索引，而不是仅将边界转换为字符串。

Hi,
I had 2 quesions related to using h3ToGeoBoundary:
Question 1:
I am doing some preprocessing in spark using h3, and I want to save my results into a format that can easily be exported. My goal is to load the data in geomesa/geoserver. I notice that using h3ToGeoBoundary I get results that are a list of GeoCoord like this:
[GeoCoord{lat=50.346809, lng=14.153511}, GeoCoord{lat=50.316251, lng=14.138129}, GeoCoord{lat=50.294416, lng=14.173950}, GeoCoord{lat=50.303130, lng=14.225160}, GeoCoord{lat=50.333686, lng=14.240581}, GeoCoord{lat=50.355530, lng=14.204753}]
I assume this is the google coordinate type: https://pub.dev/documentation/google_directions_api/latest/google_directions_api/GeoCoord-class.html.
But is this compatible with geospark/geomesa?

It would be very helpful, if there was an option to save this as let's say geojson like there is for h3-js (https://github.com/uber/h3-js#module_h3.h3ToGeoBoundary where a boolean decides how it is saved).
Is there an example somewhere, if I have let's say 10k h3 indexes how to save it into a format that other geospatial tools (geomesa or geospark ) can read?

Question2:
Also when I want to apply a udf to a full column with h3 indexes, this works:
//works
val h3ToGeoBoundary = udf{ (h3Index: Long) =>
H3.instance.h3ToGeoBoundary(h3Index).toString()
}
but this does not:
//does not work
val h3ToGeoBoundaryGeoJson = udf{ (h3Index: Long) =>
H3.instance.h3ToGeoBoundary(h3Index)
}
//error:java.lang.UnsupportedOperationException: Schema for type java.util.List[com.uber.h3core.util.GeoCoord] is not supported
This means that if I want to create a dataframe with couple 1000 rows, I can only have that in string format, which does not allow me to do transformations on it (like selecting each element of the list, and using those coordinates to turn it myself into geojson).
Any clue how to solve this?

Thanks!
PS: great job-very user friendly and cool library.