Dataframe 如何将2个或更多数据帧与pyspark合并

我有3个pyspark df as，我需要通过合并所有df来单个df，如

+--------+
|        |
|  name  |
|        |
|--------|    
| orange |  
+--------+

+--------+
|        |
|  age   |
|        |
|--------|    
|  10    |  
+--------+

+---------+
|         |
|  place  |
|         |
|---------|    
|  delhi  |  
+---------+

输出df应该如下所示

+---------+---------+---------+
|         |         |         |
|  name   |  age    |  place  |
|         |         |         |
|---------+---------+---------+    
|         |         |         |
| orange  |  10     |  delhi  |
|         |         |         |
+---------+---------+---------+

有人知道解决办法吗

---

提前感谢

对于这种情况，请使用

交叉连接

，

行号

示例：

df=spark.createDataFrame([('orange',)],['name'])
df1=spark.createDataFrame([(10,)],['age'])
df2=spark.createDataFrame([('delhi',)],['place'])

df.crossJoin(df1).crossJoin(df2).show()
#+------+---+-----+
#|  name|age|place|
#+------+---+-----+
#|orange| 10|delhi|
#+------+---+-----+

#using window
from pyspark.sql import *
from pyspark.sql.functions import *
w=Window.orderBy(lit(1))
df=df.withColumn("rn",row_number().over(w))
df1=df1.withColumn("rn",row_number().over(w))
df2=df2.withColumn("rn",row_number().over(w))
df.join(df1,['rn'],'inner').join(df2,['rn'],'inner').drop('rn').show()
#+------+---+-----+
#|  name|age|place|
#+------+---+-----+
#|orange| 10|delhi|
#+------+---+-----+