Here are some bullet points in terms of how I have things setup:
- I have CSV files uploaded to S3 and a Glue crawler setup to create the table and schema.
- I have a Glue job setup that writes the data from the Glue table to our Amazon Redshift database using a JDBC connection. The Job also is in charge of mapping the columns and creating the redshift table.
By re-running a job, I am getting duplicate rows in redshift (as expected). However, is there way to replace or delete rows before inserting the new data, using a key or the partitions setup in glue?
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
from awsglue.dynamicframe import DynamicFrame
from awsglue.transforms import SelectFields
from pyspark.sql.functions import lit
## @params: [TempDir, JOB_NAME]
args = getResolvedOptions(sys.argv, ['TempDir','JOB_NAME'])
sc = SparkContext()
glueContext = GlueContext(sc)
spark = glueContext.spark_session
job = Job(glueContext)
job.init(args['JOB_NAME'], args)
columnMapping = [
("id", "int", "id", "int"),
("name", "string", "name", "string"),
]
datasource1 = glueContext.create_dynamic_frame.from_catalog(database = "db01", table_name = "table01", transformation_ctx = "datasource0")
applymapping1 = ApplyMapping.apply(frame = datasource1, mappings = columnMapping, transformation_ctx = "applymapping1")
resolvechoice1 = ResolveChoice.apply(frame = applymapping1, choice = "make_cols", transformation_ctx = "resolvechoice1")
dropnullfields1 = DropNullFields.apply(frame = resolvechoice1, transformation_ctx = "dropnullfields1")
df1 = dropnullfields1.toDF()
data1 = df1.withColumn('platform', lit('test'))
data1 = DynamicFrame.fromDF(data1, glueContext, "data_tmp1")
## Write data to redshift
datasink1 = glueContext.write_dynamic_frame.from_jdbc_conf(frame = data1, catalog_connection = "Test Connection", connection_options = {"dbtable": "table01", "database": "db01"}, redshift_tmp_dir = args["TempDir"], transformation_ctx = "datasink1")
job.commit()