![]() Use the pip utility to install the required modules and frameworks: pip install petl On the Configuration tab for the cluster, copy the cluster URL from the connection strings displayed.Īfter installing the CData Redshift Connector, follow the procedure below to install the other required modules and start accessing Redshift through Python objects.On the Clusters page, click the name of the cluster.You can obtain the Server and Port values in the AWS Management Console: Password: Set this to the password you want to use to authenticate to the Server.User: Set this to the username you want to use to authenticate to the Server.Or, leave this blank to use the default database of the authenticated user. Database: Set this to the name of the database.Port: Set this to the port of the cluster.Server: Set this to the host name or IP address of the cluster hosting the Database you want to connect to.To connect to Redshift, set the following: For this article, you will pass the connection string as a parameter to the create_engine function. Create a connection string using the required connection properties. ![]() When you issue complex SQL queries from Redshift, the driver pushes supported SQL operations, like filters and aggregations, directly to Redshift and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).Ĭonnecting to Redshift data looks just like connecting to any relational data source. With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Redshift data in Python. This article shows how to connect to Redshift with the CData Python Connector and use petl and pandas to extract, transform, and load Redshift data. With the CData Python Connector for Redshift and the petl framework, you can build Redshift-connected applications and pipelines for extracting, transforming, and loading Redshift data. The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. ![]()
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