Directly load files in Redshift

When to use this Flow type

This Flow loads CSV files directly into Redshift. The files can be anywhere, so long as Etlworks Integrator can read them: server storage, FTP, FTPS, SFTP, cloud storage, etc.

This is just a bulk load. Files must already exist.

Create Flow

Step 1. Create a source Connection which can either be file storage, cloud storage, or HTTP Listener.

Step 2. Create and test the Redshift Connection as explained here.

Step 3. Create a Connection to the Amazon S3 bucket that will be used as a staging area, as explained here. When configuring the S3 Connection, select GZip as the value for the Archive file before copying to S3 field.

Step 4. Start creating the Redshift Flow as explained here.

Step 5. Select Load files into Redshift.

Step 6. Continue by defining the source and destination.

Step 7. For the source FROM, select the Connection created in Step 1 and enter a file name or a wildcard file name, for example, *.CSV.

Step 8. For the destination TO, select the Connection created in Step 3.

Step 9. Select the Redshift Connection created in step 2, for the final destination, as explained here.

Step 10. Continue by defining the parameters. The only required parameter is Copy SQL:

Step 11. Define the other parameters (the rest are optional):

• Action: if Move is selected (default), the file(s) will be copied to the S3 bucket and removed from the original source. If Copy is selected, the file(s) will be copied to the S3 bucket and retain in the original source.
• Add Suffix to the Destination File Name: you can select one of the predefined suffixes for the files created using this file operation. For example, if you select uuid as a suffix, and the original filename is dest.csv, Etlworks Integrator will create files with the name dest_uuid.csv, where uuid is a globally unique identifier such as 21EC2020-3AEA-4069-A2DD-08002B30309D. The default value for this field is uuid.
• Do not process files that have been already processed: if this option is enabled, the system will skip files that have already been loaded into Redshift.
• Maximum Simultaneous Operations: Etlworks Integrator can copy or move each file in its own thread. Use this property to set the maximum number of simultaneous file operations.
• Purge File(s) if Error: if this option is enabled (by default), the staging files will be automatically deleted if the COPY command was executed with an error.
• Name(s) of the File(s) to Purge: having Purge File(s) if Error enabled makes it possible to configure which files you want the system to delete if an error occurs while executing the COPY command. Wildcard file names are allowed. If not specified, the system will use the same wildcard file name it used for the COPY command.
• Before COPY INTO SQL: this SQL will be executed on the Redshift Connection Before COPY INTO SQL.
• Ignore errors when executing Before COPY SQL: if this option is enabled, and there is an error when Before COPY SQL is executed, the error will be ignored.
• After COPY SQL: this SQL will be executed on the Redshift Connection After COPY SQL.
• Ignore errors when executing After COPY SQL: if this option is enabled, and there is an error when After COPY SQL is executed, the error will be ignored.

Step 12. Save and run the Flow.