How to get unique pairs of values in DataFrame

Question

Given a pySpark DataFrame, how can I get all possible unique combinations of columns col1 and col2 .

I can get unique values for a single column, but cannot get unique pairs of col1 and col2 :

df.select('col1').distinct().rdd.map(lambda r: r[0]).collect()

I tried this, but it doesn't seem to work:

df.select(['col1','col2']).distinct().rdd.map(lambda r: r[0]).collect()

Answer 1

The one I tried,

>>> df = spark.createDataFrame([(1,2),(1,3),(1,2),(2,3)],['col1','col2'])
>>> df.show()
+----+----+
|col1|col2|
+----+----+
|   1|   2|
|   1|   3|
|   1|   2|
|   2|   3|
+----+----+

>>> df.select('col1','col2').distinct().rdd.map(lambda r:r[0]).collect() ## your mapping
[1, 2, 1]
>>> df.select('col1','col2').distinct().show()
+----+----+
|col1|col2|
+----+----+
|   1|   3|
|   2|   3|
|   1|   2|
+----+----+
>>> df.select('col1','col2').distinct().rdd.map(lambda r:(r[0],r[1])).collect() 
[(1, 3), (2, 3), (1, 2)]

Answer 2

请尝试以下功能：

    `df[['col1', 'col2']].drop_duplicates()`