python,pyspark:获取pyspark数据帧列值的总和

Question

说我有这样的数据帧

name age city
abc   20  A
def   30  B

我想在数据框的末尾添加一个摘要行,所以结果就像

name age city
abc   20  A
def   30  B
All   50  All

所以String'All',我可以很容易地说,但是如何得到sum(df ['age'])###列对象是不可迭代的

data = spark.createDataFrame([("abc", 20, "A"), ("def", 30, "B")],["name", "age", "city"])
data.printSchema()
#root
 #|-- name: string (nullable = true)
 #|-- age: long (nullable = true)
 #|-- city: string (nullable = true)
res = data.union(spark.createDataFrame([('All',sum(data['age']),'All')], data.columns))  ## TypeError: Column is not iterable
#Even tried with data['age'].sum() and got error.   If i am using [('All',50,'All')], it is doing fine. 

我经常处理Pandas数据帧和Spark新手.关于火花数据框架可能不是那么成熟.

请建议如何获得pyspark中dataframe-column的总和.如果有更好的方法来添加/追加一行到数据帧的末尾.谢谢.

Answer 1

Spark SQL有一个专用的列函数模块pyspark.sql.functions.
所以它的工作方式是:

from pyspark.sql import functions as F
data = spark.createDataFrame([("abc", 20, "A"), ("def", 30, "B")],["name", "age", "city"])

res = data.unionAll(
    data.select([
        F.lit('All').alias('name'), # create a cloumn named 'name' and filled with 'All'
        F.sum(data.age).alias('age'), # get the sum of 'age'
        F.lit('All').alias('city') # create a column named 'city' and filled with 'All'
    ]))
res.show()

打印:

+----+---+----+
|name|age|city|
+----+---+----+
| abc| 20|   A|
| def| 30|   B|
| All| 50| All|
+----+---+----+