在执行test = spark.sparkContext.textFile("file:///opt/module/spark/adult.test").map(lambda line: line.split(',')).map(lambda p: Row(**f(p))).toDF()时报错ValueError: could not convert string to float: '|1x3 Cross validator'怎么解决

这个错误提示是表明在执行转换操作时，将一个字符串转换为浮点数时出错。具体的原因可能是因为你的数据中包含了一些字符串而不是数字，导致转换失败。

为了解决这个问题，你可以检查一下原始数据文件中的每一行是否都是合法的，不包含任何非数字的字符。你还可以尝试将数据类型转换为字符串类型，然后再进行转换操作，例如：

test = spark.sparkContext.textFile("file:///opt/module/spark/adult.test").map(lambda line: line.split(',')).map(lambda p: Row(**f(p))).toDF()
test = test.selectExpr("cast(age as string) age", "cast(workclass as string) workclass", "cast(fnlwgt as string) fnlwgt", "cast(education as string) education", "cast(education_num as string) education_num", "cast(marital_status as string) marital_status", "cast(occupation as string) occupation", "cast(relationship as string) relationship", "cast(race as string) race", "cast(sex as string) sex", "cast(capital_gain as string) capital_gain", "cast(capital_loss as string) capital_loss", "cast(hours_per_week as string) hours_per_week", "cast(native_country as string) native_country", "cast(income as string) income")
test.show()

这样做可以避免非数字的字符对转换操作造成的影响。