Spark SQL Row_number()分区按排序方式描述

问题描述

我已经使用Window在Spark中成功创建了一个row_number() partitionBy，但是希望通过降序而不是默认的升序对它进行排序.这是我的工作代码:

I've successfully create a row_number() partitionBy by in Spark using Window, but would like to sort this by descending, instead of the default ascending. Here is my working code:

from pyspark import HiveContext
from pyspark.sql.types import *
from pyspark.sql import Row, functions as F
from pyspark.sql.window import Window

data_cooccur.select("driver", "also_item", "unit_count", 
    F.rowNumber().over(Window.partitionBy("driver").orderBy("unit_count")).alias("rowNum")).show()

这给了我这个结果:

 +------+---------+----------+------+
 |driver|also_item|unit_count|rowNum|
 +------+---------+----------+------+
 |   s10|      s11|         1|     1|
 |   s10|      s13|         1|     2|
 |   s10|      s17|         1|     3|

在这里，我将desc()添加到降序:

And here I add the desc() to order descending:

data_cooccur.select("driver", "also_item", "unit_count", F.rowNumber().over(Window.partitionBy("driver").orderBy("unit_count").desc()).alias("rowNum")).show()

并得到此错误:

我在做什么错了?

推荐答案

desc应该应用于不是窗口定义的列.您可以在列上使用任一方法:

desc should be applied on a column not a window definition. You can use either a method on a column:

from pyspark.sql.functions import col, row_number
from pyspark.sql.window import Window

F.row_number().over(
    Window.partitionBy("driver").orderBy(col("unit_count").desc())
)

或独立功能:

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

F.row_number().over(
    Window.partitionBy("driver").orderBy(desc("unit_count"))
)

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