问题
I need help to convert below code in Pyspark code or Pyspark sql code.
df["full_name"] = df.apply(lambda x: "_".join(sorted((x["first"], x["last"]))), axis=1)
Its basically adding one new column name full_name which have to concatenate values of the columns first and last in a sorted way.
I have done below code but don't know how to apply to sort in a columns text value.
df= df.withColumn('full_name', f.concat(f.col('first'),f.lit('_'), f.col('last')))
回答1:
From Spark-2.4+:
We can use array_join, array_sort functions for this case.
Example:
df.show()
#+-----+----+
#|first|last|
#+-----+----+
#| a| b|
#| e| c|
#| d| a|
#+-----+----+
from pyspark.sql.functions import *
#first we create array of first,last columns then apply sort and join on array
df.withColumn("full_name",array_join(array_sort(array(col("first"),col("last"))),"_")).show()
#+-----+----+---------+
#|first|last|full_name|
#+-----+----+---------+
#| a| b| a_b|
#| e| c| c_e|
#| d| a| a_d|
#+-----+----+---------+
来源：https://stackoverflow.com/questions/60970602/how-to-sort-value-before-concatenate-text-columns-in-pyspark