首页 > 解决方案 > PySpark 两个值的总和

问题描述

给定以下示例数据框:

advertiser_id| name | amount    | total             |max_total_advertiser|
4061         |source1|-434.955284|-354882.75336200005| -355938.53950700007
4061         |source2|-594.012216|-355476.76557800005| -355938.53950700007
4061         |source3|-461.773929|-355938.53950700007| -355938.53950700007

我需要将金额max_total_advertiser字段相加,以便在每一行中获得正确的总值。考虑到我需要按广告商 ID 划分的每个组的价值。(初始数据框中的总列不正确,这就是我要正确计算的原因)

应该是这样的:

w = Window.partitionBy("advertiser_id").orderBy("advertiser_id")

df.withColumn("total_aux", when( lag("advertiser_id").over(w) == col("advertiser_id"), lag("total_aux").over(w) + col("amount") ).otherwise( col("max_total_advertiser") + col("amount") ))

lag("total_aux")不起作用,因为该列尚未生成,这就是我想要实现的,如果它是组中的第一行,则将同一行中的列求和,如果没有将先前获得的值与当前金额字段相加。示例输出:

advertiser_id| name | amount    | total_aux             |
4061         |source1|-434.955284|-356373.494791    |
4061         |source2|-594.012216|-356967.507007    | 
4061         |source3|-461.773929|-357429.280936    |

谢谢。

标签: pythonpyspark

解决方案


我假设这name对于每个都是一个不同的值,advertiser_id因此您的数据集可以按name. 我还假设max_total_advertiser每个advertiser_id. 如果其中一个不是这种情况,请添加评论。

您需要的是一个rangeBetween窗口,它为您提供指定范围内的所有前后行。我们将使用Window.unboundedPreceding我们想要总结所有以前的值。

import pyspark.sql.functions as F
from pyspark.sql import Window

l = [
(4061, 'source1',-434.955284,-354882.75336200005, -355938.53950700007),
(4061, 'source2',-594.012216,-355476.76557800005, -345938.53950700007),
(4062, 'source1',-594.012216,-355476.76557800005, -5938.53950700007),
(4062, 'source2',-594.012216,-355476.76557800005, -5938.53950700007),
(4061, 'source3',-461.773929,-355938.53950700007, -355938.53950700007)
]

columns = ['advertiser_id','name' ,'amount', 'total', 'max_total_advertiser']

df=spark.createDataFrame(l, columns)

w = Window.partitionBy('advertiser_id').orderBy('name').rangeBetween(Window.unboundedPreceding, 0)

df = df.withColumn('total', F.sum('amount').over(w) + df.max_total_advertiser)
df.show()

输出:

+-------------+-------+-----------+-------------------+--------------------+ 
|advertiser_id|   name|     amount|              total|max_total_advertiser| 
+-------------+-------+-----------+-------------------+--------------------+ 
|         4062|source1|-594.012216|-6532.5517230000705|   -5938.53950700007| 
|         4062|source2|-594.012216| -7126.563939000071|   -5938.53950700007| 
|         4061|source1|-434.955284| -356373.4947910001| -355938.53950700007| 
|         4061|source2|-594.012216| -346967.5070070001| -345938.53950700007| 
|         4061|source3|-461.773929|-357429.28093600005| -355938.53950700007| 
+-------------+-------+-----------+-------------------+--------------------+

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