Unfortunately, there isn't a built-in Spark SQL method to directly use a schema file when creating views or tables.

You could try to create a custom SQL function that reads the schema file and returns it as a string. Then use this function in your SQL commands.

1. First, create a custom UDF (User Defined Function) in Scala or Python that reads the schema file:
   
   

   import org.apache.spark.sql.SparkSession
   import org.apache.spark.sql.functions.udf
   
   def readSchemaFile(path: String): String = {
     // Read the schema file and return its contents as a string
     scala.io.Source.fromFile(path).getLines().mkString
   }
   
   val spark = SparkSession.builder().getOrCreate()
   spark.udf.register("read_schema_file", readSchemaFile _)

   
   
   
2. Then use this function in your SQL command:
   

   CREATE OR REPLACE VIEW entity_view AS
   SELECT *
   FROM read_files(
     'dbfs:/mnt/.../entity.*json',
     format => 'json',
     schema => read_schema_file('/path/to/schema/entity.json'),
     rescuedDataColumn => '_rescued_data'
   )