您可以展开一系列时间戳:

You can explode a sequence of timestamps:

import pyspark.sql.functions as F

df2 = df.withColumn(
    'Date',
    F.expr("""
        explode(
            sequence(
                timestamp(Date),
                add_months(timestamp(Date), `Interval` - 1),
                interval 1 month
            )
        )
    """)
)

df2.show(99)
+------------------+----------+-------------------+---------------+--------+
|     OpptyHeaderID|   OpptyID|               Date|BaseAmountMonth|Interval|
+------------------+----------+-------------------+---------------+--------+
|0067000000i6ONPAA2|OP-0164615|2014-07-27 00:00:00|    4375.800000|      12|
|0067000000i6ONPAA2|OP-0164615|2014-08-27 00:00:00|    4375.800000|      12|
|0067000000i6ONPAA2|OP-0164615|2014-09-27 00:00:00|    4375.800000|      12|
|0067000000i6ONPAA2|OP-0164615|2014-10-27 00:00:00|    4375.800000|      12|
|0067000000i6ONPAA2|OP-0164615|2014-11-27 00:00:00|    4375.800000|      12|
|0067000000i6ONPAA2|OP-0164615|2014-12-27 00:00:00|    4375.800000|      12|
|0067000000i6ONPAA2|OP-0164615|2015-01-27 00:00:00|    4375.800000|      12|
|0067000000i6ONPAA2|OP-0164615|2015-02-27 00:00:00|    4375.800000|      12|
|0067000000i6ONPAA2|OP-0164615|2015-03-27 00:00:00|    4375.800000|      12|
|0067000000i6ONPAA2|OP-0164615|2015-04-27 00:00:00|    4375.800000|      12|
|0067000000i6ONPAA2|OP-0164615|2015-05-27 00:00:00|    4375.800000|      12|
|0067000000i6ONPAA2|OP-0164615|2015-06-27 00:00:00|    4375.800000|      12|
|0065w0000215k5kAAA|OP-0218055|2020-12-23 00:00:00|    4975.000000|       7|
|0065w0000215k5kAAA|OP-0218055|2021-01-23 00:00:00|    4975.000000|       7|
|0065w0000215k5kAAA|OP-0218055|2021-02-23 00:00:00|    4975.000000|       7|
|0065w0000215k5kAAA|OP-0218055|2021-03-23 00:00:00|    4975.000000|       7|
|0065w0000215k5kAAA|OP-0218055|2021-04-23 00:00:00|    4975.000000|       7|
|0065w0000215k5kAAA|OP-0218055|2021-05-23 00:00:00|    4975.000000|       7|
|0065w0000215k5kAAA|OP-0218055|2021-06-23 00:00:00|    4975.000000|       7|
+------------------+----------+-------------------+---------------+--------+