如何使用monotonically_increasing_id连接两个没有公共列的pyspark数据帧? [英] How to use monotonically_increasing_id to join two pyspark dataframes having no common column?

问题描述

我有两个具有相同行数的pyspark数据帧，但是它们没有任何公共列.因此，我使用monotonically_increasing_id()作为向它们两者添加新列

I have two pyspark dataframes with same number of rows but they don't have any common column. So I am adding new column to both of them using monotonically_increasing_id() as

from pyspark.sql.functions import monotonically_increasing_id as mi
id=mi()
df1 = df1.withColumn("match_id", id)
cont_data = cont_data.withColumn("match_id", id)
cont_data = cont_data.join(df1,df1.match_id==cont_data.match_id, 'inner').drop(df1.match_id)

但是在加入后，结果数据帧的行数较少. 我在这里想念什么.谢谢

But after join the resulting data frame has less number of rows. What am I missing here. Thanks

推荐答案

您只是没有.这不是monotonically_increasing_id的适用用例，根据定义是不确定的.相反:

You just don't. This not an applicable use case for monotonically_increasing_id, which is by definition non-deterministic. Instead:

• 转换为RDD
• zipWithIndex
• 转换回DataFrame.
• join

• convert to RDD
• zipWithIndex
• convert back to DataFrame.
• join

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