Spark DataFrame组按降序排序(pyspark) [英] Spark DataFrame groupBy and sort in the descending order (pyspark)
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问题描述
我正在使用pyspark(Python 2.7.9/Spark 1.3.1),并且有一个数据框GroupObject,我需要对其进行过滤和过滤;降序排列.试图通过这段代码来实现它.
I'm using pyspark(Python 2.7.9/Spark 1.3.1) and have a dataframe GroupObject which I need to filter & sort in the descending order. Trying to achieve it via this piece of code.
group_by_dataframe.count().filter("`count` >= 10").sort('count', ascending=False)
但是会引发以下错误.
sort() got an unexpected keyword argument 'ascending'
推荐答案
在PySpark 1.3中,sort
方法不采用升序参数.您可以改用desc
方法:
In PySpark 1.3 sort
method doesn't take ascending parameter. You can use desc
method instead:
from pyspark.sql.functions import col
(group_by_dataframe
.count()
.filter("`count` >= 10")
.sort(col("count").desc()))
或desc
函数:
from pyspark.sql.functions import desc
(group_by_dataframe
.count()
.filter("`count` >= 10")
.sort(desc("count"))
两种方法均可与Spark> = 1.3(包括Spark 2.x)一起使用.
Both methods can be used with with Spark >= 1.3 (including Spark 2.x).
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