在Pyspark中有条件地向数据框添加列

问题描述

我在PySpark中有一个数据框.我想有条件地在数据框中添加一列.

I have a data frame in PySpark. I would like to add a column to the data frame conditionally.

说如果数据框没有该列，则添加具有null值的列.如果存在该列，则不执行任何操作，并返回与新数据帧相同的数据帧

Say If the data frame doesn’t have the column then add a column with null values.If the column is present then do nothing and return the same data frame as a new data frame

如何在PySpark中传递条件语句

How do I pass the conditional statement in PySpark

推荐答案

这并不难，但是您需要的不仅仅是列名.必需进口

It is not hard but you'll need a bit more than a column name to do it right. Required imports

from pyspark.sql import types as t
from pyspark.sql.functions import lit
from pyspark.sql import DataFrame

示例数据:

df = sc.parallelize([("a", 1, [1, 2, 3])]).toDF(["x", "y", "z"])

辅助函数(用于旧的Python版本带状类型注释):

def add_if_not_present(df: DataFrame, name: str, dtype: t.DataType) -> DataFrame:
    return (df if name in df.columns
        else df.withColumn(name, lit(None).cast(dtype)))

示例用法:

add_if_not_present(df, "foo", t.IntegerType())

DataFrame[x: string, y: bigint, z: array<bigint>, foo: int]

add_if_not_present(df, "x", t.IntegerType())

DataFrame[x: string, y: bigint, z: array<bigint>]

add_if_not_present(df, "foobar",
  t.StructType([
      t.StructField("foo", t.IntegerType()),
      t.StructField("bar", t.IntegerType())]))

DataFrame[x: string, y: bigint, z: array<bigint>, foobar: struct<foo:int,bar:int>]

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