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It might be you have too many partitions and thus trying to use too many connections which Redshift might not accept.
You can you the option numPartitions to control this parallelism (or just repartition the data).
Please note using JDBC on Redshift as the data grows is inefficient, the Glue connector will scale much better (you can convert your DataFrame to DynamicFrame): https://docs.aws.amazon.com/glue/latest/dg/aws-glue-programming-etl-connect-redshift-home.html#aws-glue-programming-etl-connect-redshift-write
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