AWS Glue add new partitions and overwrite existing partitions

Question

I'm attempting to write pyspark code in Glue that lets me update the Glue Catalog by adding new partitions and overwrite existing partitions in the same call.

I read that there is no way to overwrite partitions in Glue so we must use pyspark code similar to this:

final_df.withColumn('year', date_format('date', 'yyyy'))\
            .withColumn('month', date_format('date', 'MM'))\
            .withColumn('day', date_format('date', 'dd'))\
            .write.mode('overwrite')\
            .format('parquet')\
            .partitionBy('year', 'month', 'day')\
            .save('s3://my_bucket/')

However with this method, the Glue Catalog does not get updated automatically so an msck repair table call is needed after each write. Recently AWS released a new feature enableUpdateCatalog, where newly created partitions are immediately updated in the Glue Catalog. The code looks like this:

additionalOptions = {"enableUpdateCatalog": True}
additionalOptions["partitionKeys"] = ["year", "month", "day"]
dyn_frame_catalog = glueContext.write_dynamic_frame_from_catalog(
            frame=partition_dyf,
            database = "my_db",
            table_name = "my_table",
            format="parquet",
            additional_options=additionalOptions,
            transformation_ctx = "my_ctx"
)

Is there a way to combine these 2 commands or will I need to use the pyspark method with write.mode('overwrite') and run an MSCK REPAIR TABLE my_table on every run of the Glue job?

Answer 1

If you have not already found your answer, I believe the following will work:

DataSink5 = glueContext.getSink(
    path = "s3://...", 
    connection_type = "s3", 
    updateBehavior = "UPDATE_IN_DATABASE", 
    partitionKeys = ["year", "month", "day"], 
    enableUpdateCatalog = True, 
    transformation_ctx = "DataSink5")

DataSink5.setCatalogInfo(
    catalogDatabase = "my_db",
    catalogTableName = "my_table")

DataSink5.setFormat("glueparquet")
DataSink5.writeFrame(partition_dyf)