我有一个数据框,看起来像 -
+---+---+---+---+
| id| w1| w2| w3|
+---+---+---+---+
| 1|100|150|200|
| 2|200|400|500|
| 3|500|600|150|
+---+---+---+---+
我希望输出看起来像 -
full total_amt
w1 800
w2 1150
w3 850
我的代码是 -
df = spark.createDataFrame(
[(1, 100,150,200), (2, 200,400,500), (3, 500,600,150)], ("id", "w1","w2","w3"))
res = df.unionAll(
df.select([
F.lit('All').alias('id'),
F.sum(df.w1).alias('w1'),
F.sum(df.w2).alias('w2'),
F.sum(df.w3).alias('w3')
]))
res.show()
But output gives me -
+---+---+----+---+
| id| w1| w2| w3|
+---+---+----+---+
| 1|100| 150|200|
| 2|200| 400|500|
| 3|500| 600|150|
|All|800|1150|850|
+---+---+----+---+
我认为添加后需要创建枢轴。所有字段本质上都是数字。
尝试这个方法 -
首先聚合数据,然后使用 stack 函数将列转换为行
import pyspark.sql.functions as psf
#perform aggregation
df_agg = df.agg(psf.sum('w1').alias('w1'), psf.sum('w2').alias('w2'), psf.sum('w3').alias('w3'))
#let's have a look at aggregated dataframe
df_agg.show()
#+---+----+---+
#| w1| w2| w3|
#+---+----+---+
#|800|1150|850|
#+---+----+---+
#Use stack function to convert column to rows
df_agg.selectExpr("stack(3, 'w1', w1, 'w2', w2, 'w3', w3) as (full, total)").show()
#+----+-----+
#|full|total|
#+----+-----+
#| w1| 800|
#| w2| 1150|
#| w3| 850|
#+----+-----+
快速解决方案可能是
>>> df.createOrReplaceTempView('df')
>>> spark.sql('''
... select 'w1' as full, sum(w1) as total from df
... union
... select 'w2' as full, sum(w2) as total from df
... union
... select 'w3' as full, sum(w3) as total from df
... ''').show()
+----+-----+
|full|total|
+----+-----+
| w2| 1150|
| w3| 850|
| w1| 800|
+----+-----+