Python 从UDF返回列表列表：构建ClassDict（对于numpy.core.multiarray.\u）需要零参数

我想输出作为map返回的两列，其中一列是浮点数的

nd.array

。在PySpark中，我无法将其转换为正确的返回类型

def get_vectors(feature_map):
    ids, inputs = zip(*[
        (k,  v) for d in feature_map for k, v in d.items()
    ])

   #vectors object will be returned by another method, this is just dummy code to simulate the data. It is an nd.array of floating point numbers
    vectors = []
    for item in inputs :
      vectors.append([1.0,2.0,3.0])
    vectors = np.array(vectors,float)
    return dict(zip(ids, list(vectors)))

gen_vectors_udf  = f.udf(get_vectors,t.MapType(t.StringType(),t.ArrayType(t.ArrayType(t.FloatType()))))

当我调用此udf时，出现以下错误

构造ClassDict（对于numpy.core.multiarray.\u重构）需要零参数

有人能帮助我理解如何将

nd.array

转换为PySpark类型吗

另一方面，如果我将

nd.array

转换为字符串列表，它似乎工作得非常好：

def get_vectors(feature_map):
    ids, inputs = zip(*[
        (k,  v) for d in feature_map for k, v in d.items()
    ])

    #vectors object will be returned by another method, this is just dummy code to simulate the data. It is an nd.array of floating point numbers
    vectors = []

    for item in inputs:
      vectors.append([1.0,2.0,3.0])
    vectors = np.array(vectors,float)
    output = [str(k) for k in vectors]
    return dict(zip(ids, output ))

gen_vectors_udf = f.udf(get_vectors,t.MapType(t.StringType(),t.StringType()))