# Define date range
START_DATE = dt.datetime(2019,8,15,20,30,0)
END_DATE = dt.datetime(2019,8,16,15,43,0)

# Generate date range with pandas
timerange = pd.date_range(start=START_DATE, end=END_DATE, freq='15min')
# Convert to timestamp
timestamps = [int(x) for x in timerange.values.astype(np.int64) // 10 ** 9]

# Create pyspark dataframe from the above timestamps
(spark.createDataFrame(dates, IntegerType())
    .withColumn('value_date', sf.from_unixtime('value'))
    .drop('value')
    .withColumnRenamed('value_date', 'date').show())

+-------------------+
|               date|
+-------------------+
|2019-08-15 20:30:00|
|2019-08-15 20:45:00|
|2019-08-15 21:00:00|
|2019-08-15 21:15:00|
|2019-08-15 21:30:00|
|2019-08-15 21:45:00|
|2019-08-15 22:00:00|
|2019-08-15 22:15:00|
|2019-08-15 22:30:00|
|2019-08-15 22:45:00|
|2019-08-15 23:00:00|
|2019-08-15 23:15:00|
|2019-08-15 23:30:00|
|2019-08-15 23:45:00|
|2019-08-16 00:00:00|
|2019-08-16 00:15:00|
|2019-08-16 00:30:00|
|2019-08-16 00:45:00|
|2019-08-16 01:00:00|
|2019-08-16 01:15:00|
+-------------------+