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Hello Dimitriy,
I don't think AWS Glue provides native support for connecting to Greenplum databases. However, you can use a JDBC connection to connect to Greenplum from AWS Glue.
Here's how I would approach it:
-
Set Up a JDBC Connection:
- Go to the AWS Glue Console.
- Create or edit a Glue connection. In the connection settings, select "JDBC" as the connection type.
- Provide the necessary connection details for your Greenplum database, including the JDBC URL, username, and password.
-
Use PySpark with JDBC:
- In your AWS Glue Python script, you can use PySpark to interact with the Greenplum database using the JDBC connection you set up.
- Use the
spark.read.jdbc
method to read data from Greenplum into a DataFrame andspark.write.jdbc
to write data back.
Here's an example of how you can read data from Greenplum using PySpark in an AWS Glue Python script:
from pyspark.context import SparkContext from pyspark.sql import SparkSession # Initialize SparkContext and SparkSession sc = SparkContext() spark = SparkSession(sc) # JDBC connection properties jdbc_url = "jdbc:postgresql://your-greenplum-hostname:5432/your-database" properties = { "user": "your-username", "password": "your-password", "driver": "org.postgresql.Driver" } # Read data from Greenplum into a DataFrame df = spark.read.jdbc(url=jdbc_url, table="your-table-name", properties=properties) # Perform DML operations or DDL as needed # Example: df.show() or df.write.jdbc(...) for writing data
Make sure to replace your-greenplum-hostname
, your-database
, your-username
, your-password
, and your-table-name
with your actual Greenplum database and table details.
Also, please note that AWS Glue is a managed ETL service, and it's primarily designed for data transformation and preparation tasks. While you can use PySpark to perform various data operations, including DML, it's not a replacement for a full-fledged database management tool. For extensive DDL operations, you may still need to use Greenplum-specific tools or interfaces.
Please give a thumbs up if it helps
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You can access the connection parameters through Glue API so they don't get exposed in code.
Good day, thank You for response!
The first option does not work for Greenplum, here is the link where it's highlited: https://aws.amazon.com/ru/blogs/big-data/use-aws-glue-to-run-etl-jobs-against-non-native-jdbc-data-sources/
For the second option I always get error: "An error occurred while calling o82.jdbc. The connection attempt failed." And it seems that the problem has something to do with driver