Moving data from Kinesis -> RDS using Spark with AWS Glue implementation locally - apache-spark

Question

I have a Spark project with AWS Glue implementation running locally.
I listen to a Kinesis stream so when Data is arrived in JSON format, I can storage to S3 correctly.
I want to store in AWS RDS instead of storing in S3.
I have tried to use:
dataFrame.write
.format("jdbc")
.option("url","jdbc:mysql://aurora.cluster.region.rds.amazonaws.com:3306/database")
.option("user","user")
.option("password","password")
.option("dbtable","test-table")
.option("driver","com.mysql.jdbc.Driver")
.save()
Spark project get data from a Kinesis stream using AWS glue job.
I want to add the data to Aurora database.
It fails with error
Caused by: java.sql.SQLSyntaxErrorException: You have an error in your SQL syntax; check the manual that corresponds to your MySQL
server version for the right syntax to use near '-glue-table (`label2` TEXT , `customerid` TEXT , `sales` TEXT , `name` TEXT )' a
t line 1
This is the test dataFrame Im using, dataFrame.show():
+------+----------+-----+--------------------+
|label2|customerid|sales| name|
+------+----------+-----+--------------------+
| test6| test| test|streamingtesttest...|
+------+----------+-----+--------------------+

Answer 1

Using Spark DynamicFrame instead of DataFrame and using the glueContext sink to publish to Aurora:
So the final code could be:
lazy val mysqlJsonOption = jsonOptions(MYSQL_AURORA_URI)
//Write to Aurora
val dynamicFrame = DynamicFrame(joined, glueContext)
glueContext.getSink("mysql", mysqlJsonOption).writeDynamicFrame(dynamicFrame)