How to sort only one column within a spark dataframe using pyspark?

Question

I have a Spark Dataframe looking like this:

|  time  | col1 | col2 |
|----------------------|
| 123456 |   2  |  A   |
| 123457 |   4  |  B   |
| 123458 |   7  |  C   |
| 123459 |   5  |  D   |
| 123460 |   3  |  E   |
| 123461 |   1  |  F   |
| 123462 |   9  |  G   |
| 123463 |   8  |  H   |
| 123464 |   6  |  I   |

Now I need to sort the "col1" - Column, but the other columns have to remain in the same order: (Using pyspark)

|  time  | col1 | col2 | col1_sorted |
|-----------------------------------|
|  same  | same | same |   sorted   |
|-----------------------------------|
| 123456 |   2  |  A   |     1      |
| 123457 |   4  |  B   |     2      |
| 123458 |   7  |  C   |     3      |
| 123459 |   5  |  D   |     4      |
| 123460 |   3  |  E   |     5      |
| 123461 |   1  |  F   |     6      |
| 123462 |   9  |  G   |     7      |
| 123463 |   8  |  H   |     8      |
| 123464 |   6  |  I   |     9      |

Thanks in advance for any help!

Answer 1

For Spark 2.3.1, you can try pandas_udf, see below (assume the original dataframe is sorted by the time column)

from pyspark.sql.functions import pandas_udf, PandasUDFType
from pyspark.sql.types import StructType

schema = StructType.fromJson(df.schema.jsonValue()).add('col1_sorted', 'integer')

@pandas_udf(schema, PandasUDFType.GROUPED_MAP)
def get_col1_sorted(pdf):
  return pdf.sort_values(['time']).assign(col1_sorted=sorted(pdf["col1"]))
  
df.groupby().apply(get_col1_sorted).show()
+------+----+----+-----------+
|  time|col1|col2|col1_sorted|
+------+----+----+-----------+
|123456|   2|   A|          1|
|123457|   4|   B|          2|
|123458|   7|   C|          3|
|123459|   5|   D|          4|
|123460|   3|   E|          5|
|123461|   1|   F|          6|
|123462|   9|   G|          7|
|123463|   8|   H|          8|
|123464|   6|   I|          9|
+------+----+----+-----------+