Fill in null with previously known good value with pyspark

by

This uses last and ignores nulls.

Let’s re-create something similar to the original data:

import sys
from pyspark.sql.window import Window
import pyspark.sql.functions as func

d = [{'session': 1, 'ts': 1}, {'session': 1, 'ts': 2, 'id': 109}, {'session': 1, 'ts': 3}, {'session': 1, 'ts': 4, 'id': 110}, {'session': 1, 'ts': 5},  {'session': 1, 'ts': 6}]
df = spark.createDataFrame(d)

df.show()
# +-------+---+----+
# |session| ts|  id|
# +-------+---+----+
# |      1|  1|null|
# |      1|  2| 109|
# |      1|  3|null|
# |      1|  4| 110|
# |      1|  5|null|
# |      1|  6|null|
# +-------+---+----+

Now, let’s use window function last:

df.withColumn("id", func.last('id', True).over(Window.partitionBy('session').orderBy('ts').rowsBetween(-sys.maxsize, 0))).show()

# +-------+---+----+
# |session| ts|  id|
# +-------+---+----+
# |      1|  1|null|
# |      1|  2| 109|
# |      1|  3| 109|
# |      1|  4| 110|
# |      1|  5| 110|
# |      1|  6| 110|
# +-------+---+----+

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