HBase to Hive incremental data load using Pyspark - pyspark

Question

I have a table in HBase and I want to perform incremental load to HIVE table using Pyspark. I am fairly new to this.
In my project, they are using MYSQL table for creating JSON which is used as schema to load HBase to Spark Data Frame.
Now my question is how do I perform incremental load if there are changes in HBase tables.
Here is MYSQL table structure-
+----------------+-------------+---------------+----------------+--------------+-----------+------------+-----------+---------------------+---------------------+
| tgt_table_name | col_name | col_data_type | map_table_name | map_col_name | weightage | action_set | is_active | created_datetime | modified_datetime |
+----------------+-------------+---------------+----------------+--------------+-----------+------------+-----------+---------------------+---------------------+
| employee | id | STRING | emp | id | 0 | COPY | y | 2023-02-15 00:00:00 | 2023-02-15 00:00:00 |
| employee | name | STRING | emp | name | 0 | COPY | y | 2023-02-15 00:00:00 | 2023-02-15 00:00:00 |
| employee | city | STRING | emp | city | 0 | COPY | y | 2023-02-15 00:00:00 | 2023-02-15 00:00:00 |
| employee | designation | STRING | emp | designation | 0 | COPY | y | 2023-02-15 00:00:00 | 2023-02-15 00:00:00 |
| employee | salary | STRING | emp | salary | 0 | COPY | y | 2023-02-15 00:00:00 | 2023-02-15 00:00:00 |
+----------------+-------------+---------------+----------------+--------------+-----------+------------+-----------+---------------------+---------------------+
tgt_table_name represent - Hive Table
col_name - Hive col name
map_table_name - HBase table name
map_col_name-Hbase column
Here is the sample data frame which I have created from HBase.Spark DF from HBase
I have inserted this data frame to a Hive external table.