Question

我有一个火花数据框，我想根据当前行数量值和基于groupid和id的Amount值的上一行总和计算一个运行总计。让我拿出df

import findspark
findspark.init()
import pyspark 
from pyspark.sql import SparkSession
spark = SparkSession.builder.getOrCreate()
import pandas as pd


 sc = spark.sparkContext
data1 = {'date': {0: '2018-04-03', 1: '2018-04-04', 2: '2018-04-05', 3: '2018-04-06', 4: '2018-04-07'},
         'id': {0: 'id1', 1: 'id2', 2: 'id1', 3: 'id3', 4: 'id2'},
         'group': {0: '1', 1: '1', 2: '1', 3: '2', 4: '1'},
         'amount': {0: 50, 1: 40, 2: 50, 3: 55, 4: 20}}
df1_pd = pd.DataFrame(data1, columns=data1.keys())

df1 = spark.createDataFrame(df1_pd)
df1.show()


+----------+---+-----+------+
|      date| id|group|amount|
+----------+---+-----+------+
|2018-04-03|id1|    1|    50|
|2018-04-04|id2|    1|    40|
|2018-04-05|id1|    1|    50|
|2018-04-06|id3|    2|    55|
|2018-04-07|id2|    1|    20|
+----------+---+-----+------+

我正在寻找的输出

+----------+---+-----+------+---+
|      date| id|group|amount|sum|
+----------+---+-----+------+---+
|2018-04-03|id1|    1|    50|50 |
|2018-04-04|id2|    1|    40|90 |
|2018-04-05|id1|    1|    50|140|
|2018-04-06|id3|    2|    55|55 |
|2018-04-07|id2|    1|    20|160|
+----------+---+-----+------+---+

Answer 1

窗口定义：

from pyspark.sql.window import Window
from pyspark.sql.functions import sum

w = Window.partitionBy("group").orderBy("date").rowsBetween(
    Window.unboundedPreceding,  # Take all rows from the beginning of frame
    Window.currentRow           # To current row
)

和：

(df1.withColumn("sum", sum("amount").over(w))
    .orderBy("date")   # Sort for easy inspection. Not necessary
    .show())

结果：

+----------+---+-----+------+---+      
|      date| id|group|amount|sum|
+----------+---+-----+------+---+
|2018-04-03|id1|    1|    50| 50|
|2018-04-04|id2|    1|    40| 90|
|2018-04-05|id1|    1|    50|140|
|2018-04-06|id3|    2|    55| 55|
|2018-04-07|id2|    1|    20|160|
+----------+---+-----+------+---+

使用Window函数添加当前行的上一行

1 个答案: