I want to get all values of a column in pyspark dataframe. I did some search, but I never find a efficient and short solution.
Assuming I want to get a values in the column called "name". I have a solution:
sum(dataframe.select("name").toPandas().values.tolist(),[])
It works, but it is not efficient since it converts to pandas then flatten the list... Is there a better and short solution?
Below Options will give better performance than sum
.
Using collect_list
import pyspark.sql.functions as f
my_list = df.select(f.collect_list('name')).first()[0]
Using RDD:
my_list = df.select("name").rdd.flatMap(lambda x: x).collect()
I am not certain but in my couple of stress test, collect_list
gives better performance. Will be great if someone can confirm.
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