When to use this Flow type
This Flow bulk-loads data into Redshift using the user-defined COPY command. The data can be files in file-based or cloud storage, responses from APIs, email attachments, or objects stored in a NoSQL database.
Flows optimized for Redshift
|Flow type||When to use|
|When you need to extract data from any source, transform it and load it into Redshift.|
|Bulk load files in S3 into Redshift||When you need to bulk-load files that already exist in S3 without applying any transformations. The flow automatically generates the COPY command and MERGEs data into the destination.|
|Stream CDC events into Redshift||When you need to stream updates from the database which supports Change Data Capture (CDC) into Redshift in real-time.|
|Stream messages from queue into Redshift||When you need to stream messages from the message queue which supports streaming into Redshift in real-time.|
|COPY files into Redshift||You are here||When you need to bulk-load data from the file-based or cloud storage, API, or NoSQL database into Redshift without applying any transformations. This flow requires providing the user-defined COPY command. Unlike Bulk load files in S3 into Redshift, this flow does not support automatic MERGE.|
How it works
This flow copies files from the source to S3 and then executes the user-defined COPY command.
- The Redshift is up and running and available from the Internet.
- The Redshift user has
INSERTprivilege for the table(s).
- The Amazon S3 bucket is created, and Redshift is able to access the bucket.
Step 1. Create a source Connection.
Step 2. Create and test the Redshift Connection as explained here.
Step 3. Create an S3 connection. When configuring the S3 Connection, select
GZip as the value for the
Archive file before copying to S3 field.
Step 4. In Flows click Add flow button and enter
Select Flow Type.
Step 5. Select
Copy 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,
Step 8. For the destination
TO, select the Connection created in Step 3 and enter the base destination table name (without the database name and schema name).
Step 9. Select
Connections tab and select the Redshift Connection created in Step 2.
Step 10. Click
Parametersand continue by defining the parameters. The only required parameter is
Step 11. Define the other parameters (the rest are optional):
- Action: if
Moveis selected (default), the file(s) will be copied to the S3 bucket and removed from the original source. If
Copyis 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
uuidas a suffix, and the original filename is
dest.csv, Etlworks Integrator will create files with the name
uuidis a globally unique identifier such as
21EC2020-3AEA-4069-A2DD-08002B30309D. The default value for this field is
- 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
COPYcommand was executed with an error.
- Name(s) of the File(s) to Purge: having
Purge File(s) if Errorenabled makes it possible to configure which files you want the system to delete if an error occurs while executing the
COPYcommand. Wildcard file names are allowed. If not specified, the system will use the same wildcard file name it used for the
- 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 SQLis 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 SQLis executed, the error will be ignored.
Step 12. Save and run the Flow.
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