pyspark执行df: pyspark.sql.DataFrame = [features: vector, label: string]时报错File "<stdin>", line 1 df: pyspark.sql.DataFrame = [features: vector, label: string] ^SyntaxError: invalid syntax

这个错误是因为你在定义DataFrame时使用了类型注解，但是Python 2不支持这种语法。在Python 2中，可以这样定义DataFrame:

from pyspark.sql.types import StringType, StructField, StructType
from pyspark.ml.linalg import Vectors

schema = StructType([
    StructField("features", Vectors.dense(1.0, 2.0, 3.0), True),
    StructField("label", StringType(), True)
])

data = [(Vectors.dense(1.0, 2.0, 3.0), "a"), (Vectors.dense(4.0, 5.0, 6.0), "b")]
df = spark.createDataFrame(data, schema)

在Python 3中，你可以使用类型注解来定义DataFrame：

from pyspark.sql.types import StringType, StructField, StructType
from pyspark.ml.linalg import Vectors
from typing import List, Tuple

schema = StructType([
    StructField("features", Vector, True),
    StructField("label", StringType(), True)
])

def create_dataframe(data: List[Tuple[List[float], str]]) -> DataFrame:
    data = [(Vectors.dense(features), label) for (features, label) in data]
    return spark.createDataFrame(data, schema)

data = [([1.0, 2.0, 3.0], "a"), ([4.0, 5.0, 6.0], "b")]
df = create_dataframe(data)