Using components: Amazon Redshift Source

Use the Amazon Redshift source component to read data stored in an Amazon Redshift table, view or using a query.

The source component uses Amazon Redshift's UNLOAD statement to pull data into files in Amazon S3 and then read the files.

Connection

Select an existing Amazon Redshift connection or create a new one.

Source Properties

  • Access mode - select table to extract an entire table/view or query to execute a query.
  • Source schema - the source table's schema. If empty, the default schema is used.
  • Source table/view - the table or view name from which the data will be imported.
  • where clause - optional. You can add predicates clauses to the WHERE clause as part of the SQL query that is built in order to get the data from the database. Make sure to skip the keyword WHERE.
    Goodprod_category = 1 AND prod_color = 'red'
    BadWHERE prod_category = 1 AND prod_color = 'red'
  • Query - type in a SQL query. Make sure to name all columns uniquely.
  • Null string - NULL values in string columns will be replaced with the string specified here. By default NULL values will appear like empty strings.

Source Schema

After defining the source table/view/query select the fields to use in the source.

With table access mode, the fields you select are used to build the query that will be executed to read the data.

With query access mode, select all the fields that are defined in the query and make sure to use the same column names

Define the data type for the field. Use the following table when matching Redshift data types to Xplenty data types.

Amazon Redshift Xplenty
varchar, nvarchar, text String
smallint, int Integer
bigint Long
decimal, real Float
double precision Double
timestamp, date DateTime

Creating packages

  1. Creating a new package in New Xplenty
  2. Creating a workflow
  3. Working in the new package designer
  4. Validating a package
  5. Using components: Amazon Redshift Source
  6. Using components: Bing Ads Source
  7. Using components: Database Source
  8. Using components: Facebook Ads Insights Source
  9. Using components: File Storage Source
  10. Using components: Google Adwords source
  11. Using components: Google Analytics Source
  12. Using components: Google BigQuery Source
  13. Using components: Google Cloud Spanner Source
  14. Using components: MongoDB Source
  15. Using components: NetSuite Source
  16. Using components: Salesforce source
  17. Using components: Rest API Source
  18. Using components: Aggregate Transformation
  19. Using components: Assert Transformation
  20. Using components: Clone transformation
  21. Using components: Cross Join Transformation
  22. Using components: Distinct Transformation
  23. Using components: Filter Transformation
  24. Using components: Join Transformation
  25. Using components: Limit Transformation
  26. Using components: Rank Transformation
  27. Using components: Select Transformation
  28. Using components: Sort Transformation
  29. Using components: Union Transformation
  30. Using components: Window Transformation
  31. Using components: Sample Transformation
  32. Using components: Cube transformation
  33. Using components: Amazon Redshift Destination
  34. Using components: Database Destination
  35. Using components: File Storage Destination
  36. Using components: Google BigQuery Destination
  37. Using components: Google Spanner Destination
  38. Using components: MongoDB Destination
  39. Using components: Salesforce Destination
  40. Using components: Snowflake Destination (beta)
  41. Using and setting variables in your packages
  42. System and pre-defined variables
  43. Using pattern-matching in source component paths
  44. Using ISO 8601 string functions
  45. Using Expressions in Xplenty
  46. Xplenty Functions

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