varSchema = 'abfss://landing@[hidden].dfs.core.windows.net/'+parSourceSystemName+'/'+parDatasetName+'.json'
rdd = spark.sparkContext.wholeTextFiles(varSchema)
text = rdd.collect()[0][1]
schema_dict = json.loads(text)
dataSchema = StructType.fromJson(schema_dict)

使用模式创建一个空DataFrame

empty_DF = spark.createDataFrame([], dataSchema)

将实际数据加载到另一个DF

landing_data_DF = spark.read.format("csv").load("abfss://landing@[hidden].dfs.core.windows.net/path/to/datafile.csv")

获取schema中的字段数和着陆数据DF中的列数，并比较它们：（我假设您需要打印语句）

num_fields_in_schema = len(dataSchema)

num_columns_in_data = len(landing_data_DF.columns)

# I used print statements but you can do other methods according to your preference

if num_fields_in_schema == num_columns_in_data:
    print("No schema change.")
elif num_fields_in_schema < num_columns_in_data:
    print("The source system added new fields.")
else:
    print("The source system removed fields.")