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  1. Preface
  2. Introduction to PowerExchange for Amazon Redshift
  3. PowerExchange for Amazon Redshift Configuration
  4. Amazon Redshift Connections
  5. PowerExchange for Amazon Redshift Data Objects
  6. Amazon Redshift Mappings
  7. Pushdown Optimization
  8. Amazon Redshift Lookup
  9. Appendix A: Amazon Redshift Datatype Reference
  10. Appendix B: Troubleshooting

PowerExchange for Amazon Redshift User Guide

PowerExchange for Amazon Redshift User Guide

Amazon Redshift Mapping Example

Amazon Redshift Mapping Example

Your organization has a large amount of customers data from for all regions in flat files. You organization needs to analyze customer data in the US region in a short span of time. Create a mapping that reads all the customer records and write the records to Amazon Redshift table.
You can use the following objects in a Amazon Redshift mapping:
Flat file input
The input file is a flat file that contains the customer names and other details about customers.
Create a flat file data object. Configure the flat file connection and specify the flat file that contains the customer data as a resource for the data object. Drag the data object into a mapping as a read data object.
Transformations
Add Filter transformation to get customer data in a particular region.
The Filter transformation filters the source data based on the value you specify for the region ID column. The Data Integration Service returns the rows that meet the filter condition.
Amazon Redshift output
Create an Amazon Redshift data object write operation. Configure the Amazon Redshift connection and specify the Amazon Redshift object as a target for the data object. Drag the data object into a mapping as a target data object.
The following image shows the Amazon Redshift mapping example:
You can view the mapping that reads from the flat file object and writes to the Amazon Redshift object, ADOO_load_customer.
When you run the mapping, the customer records are read from the flat file and written to the Amazon Redshift table.

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