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For efficient geospatial analysis on a large dataset in Spark, which approach is best for handling spatial queries like range searches and nearest neighbor?
A
Storing data in a geospatial database and querying it from Spark for heavy lifting.
B
Using DataFrames with UDFs to implement custom geospatial algorithms.
C
Leveraging geospark library to extend Spark SQL and DataFrame APIs for spatial operations.
D
Integrating a spatial index (e.g., R-tree) as a broadcast variable to optimize spatial queries.
