Decorator sql error when using Spark Big Query Connector

Question

I am migrating data from gcp to aws. For this, I'm following this aws glue solution [1] utilizing the Spark Big Query Connector [2]. This approach is working fine for full loads, however I want to modify the job to load data incrementally based on date partitions. When providing the 'datePartition' property mentioned in [2] to the glue job as an additional connection option, I get the following error:

'An error occurred while calling o94.getDynamicFrame. com.google.cloud.spark.bigquery.repackaged.io.grpc.StatusRuntimeException: INVALID_ARGUMENT: request failed: table decorators are not supported in standard SQL'

Can anyone help me out circumvening this, or guide me towards a different implementation of incremental loads? It would help me out tremendously.

[1] https://aws.amazon.com/blogs/big-data/migrating-data-from-google-bigquery-to-amazon-s3-using-aws-glue-custom-connectors/
[2] https://github.com/GoogleCloudDataproc/spark-bigquery-connector

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

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

# Script generated for node Google BigQuery Connector 0.24.2 for AWS Glue 3.0
GoogleBigQueryConnector0242forAWSGlue30_node1 = (
    glueContext.create_dynamic_frame.from_options(
        connection_type="marketplace.spark",
        connection_options={
            "datePartition": "20230501",
            "parentProject": "project_name",
            "dataset": "dataset_name",
            "table": "table_name",
            "connectionName": "connection_name",
        },
        transformation_ctx="GoogleBigQueryConnector0242forAWSGlue30_node1",
    )
)

# Script generated for node S3 bucket
S3bucket_node3 = glueContext.write_dynamic_frame.from_options(
    frame=GoogleBigQueryConnector0242forAWSGlue30_node1,
    connection_type="s3",
    format="glueparquet",
    connection_options={
        "path": "bucket_name",
        "partitionKeys": [],
    },
    format_options={"compression": "snappy"},
    transformation_ctx="S3bucket_node3",
)

job.commit()