AWS glue creates full data from oracle source to s3 target every time even when there is a job bookmark

I have below python script in AWS Glue job. For incremental load logic i have now set the Job bookmark option to enable and also provided temporary path.

I have "btb" table in oracle database. The daily data inserted in this "btb" table with new modtime. Using job bookmark in glue, I want to perform incremental load logic on this oracle table such that it should create files in s3 bucket with the new data only. Thats why i tried to use modtime field as job bookmark key.

When i use create_dynamic_frame.from_catalog then it creates files for entire "btb" table in s3 bucket everytime. But i want only files with new data to be created in s3 bucket. I have seen few aws job bookmark article but could not find any help.

import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.job import Job
import datetime


args = getResolvedOptions(sys.argv, ['target_BucketName', 'JOB_NAME'])
sc = SparkContext()
glueContext = GlueContext(sc)
spark = glueContext.spark_session
job = Job(glueContext)
job.init(args['JOB_NAME'], args)

outputbucketname = args['target_BucketName']

timestamp = datetime.datetime.now().strftime("%Y%m%d")
filename = f"btb{timestamp}"
output_path = f"{outputbucketname}/{filename}"


# Script generated for node AWS Glue Data Catalog
AWSGlueDataCatalog_node1712075257312 = glueContext.create_dynamic_frame.from_catalog(
    database="checks", 
    table_name="_bst_rw_omuc_baag__bst1_btb",
    additional_options = {"jobBookmarkKeys":["modtime"],"jobBookmarkKeysSortOrder":"desc"}, 
    transformation_ctx="AWSGlueDataCatalog_node1712075257312")

# Script generated for node Amazon S3
AmazonS3_node1712075284688 = glueContext.write_dynamic_frame.from_options(frame=AWSGlueDataCatalog_node1712075257312, connection_type="s3", format="csv", format_options={"separator": "|"}, connection_options={"path": output_path, "compression": "gzip", "partitionKeys": []}, transformation_ctx="AmazonS3_node1712075284688")


job.commit()