如何在pyspark中获得距离？

from pyspark.sql import SparkSession
from pyspark.ml.linalg import Vectors
from pyspark.ml.feature import VectorAssembler
from pyspark.ml.feature import VectorDistance

# 创建SparkSession
spark = SparkSession.builder.getOrCreate()

# 创建示例数据集
data = [(Vectors.dense([1, 2, 3]),), (Vectors.dense([4, 5, 6]),)]
df = spark.createDataFrame(data, ["features"])

# 创建特征向量列
assembler = VectorAssembler(inputCols=["features"], outputCol="featureVector")
df = assembler.transform(df)

# 计算向量之间的距离
distance = VectorDistance(distanceMeasure="euclidean", inputCol="featureVector")
result = distance.transform(df)

# 显示结果
result.show()