AWS Glue Job Method pyWriteDynamicFrame does not exist - pyspark

Question

My goal is to read dataframe from existing catalog table, make some transformations and create a new table out of it. So according to https://docs.aws.amazon.com/glue/latest/dg/update-from-job.html, I use the sink.writeFrame method:
datasource0 = glueContext.create_dynamic_frame.from_catalog(database = "my_db", table_name = "table1", transformation_ctx = "datasource0")
datasource1 = datasource0.toDF().withColumn("date", current_date().cast("string"))
datasource2 = DynamicFrame.fromDF(datasource1, glueContext, "datasource2")
sink = glueContext.getSink(connection_type="s3", path="s3://my_bucket/output", enableUpdateCatalog=True)
sink.setFormat("json")
sink.setCatalogInfo(catalogDatabase='my_db', catalogTableName='table2')
sink.writeFrame(datasource2)
job.commit()
But as a result I get a misleading error, that method pyWriteDynamicFrame doesn't exist:
Traceback (most recent call last):
File "/tmp/test", line 39, in <module>
sink.writeFrame(datasource1)
File "/opt/amazon/lib/python3.6/site-packages/awsglue/data_sink.py", line 31, in writeFrame
return DynamicFrame(self._jsink.pyWriteDynamicFrame(dynamic_frame._jdf, callsite(), info), dynamic_frame.glue_ctx, dynamic_frame.name + "_errors")
File "/opt/amazon/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
answer, self.gateway_client, self.target_id, self.name)
File "/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw)
File "/opt/amazon/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 332, in get_return_value
format(target_id, ".", name, value))
py4j.protocol.Py4JError: An error occurred while calling o75.pyWriteDynamicFrame. Trace:
py4j.Py4JException: Method pyWriteDynamicFrame([class org.apache.spark.sql.Dataset, class java.lang.String, class java.lang.String]) does not exist
at py4j.reflection.ReflectionEngine.getMethod(ReflectionEngine.java:318)
at py4j.reflection.ReflectionEngine.getMethod(ReflectionEngine.java:326)
at py4j.Gateway.invoke(Gateway.java:274)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Versions:
Spark: 2.4, Python: 3, Glue: 2

Answer 1

You can use Glue native transformation Map class which will builds a new DynamicFrame by applying a function to all records in the input DynamicFrame.
So in your case to derive a column date you can use below snippet to achieve the it.
from datetime import datetime
def addDate(d):
d["date"] = datetime.today()
return d
datasource1 = Map.apply(frame = datasource0, f = addDate)