Auto mapping recommender
Disclosed herein are system, method, and computer program product embodiments for providing an auto-mapping recommendation between a source asset and a target asset in an integration flow design tool. Because the number of fields passed from a source asset to a target asset may be multitudinous, by auto-recommending mappings between fields provided by the source asset to the target asset, an integration flow design tool may save time developers a significant amount of time and optimize the integration flow design process.
1. A method, comprising:
displaying, by one or more processors, in an integration flow design tool, an integration flow comprising a source application and a target application, wherein the source application sends one or more source fields to the target application as one or more target fields when the integration flow is executed;
determining, by the one or more processors, a map suggestion for the integration flow using a trained algorithm by applying a semantic dictionary to map the one or more source fields to the one or more target fields, wherein the map suggestion comprises one or more links between the one or more source fields and the one or more target fields; and
displaying, by the one or more processors, the map suggestion in a graphical representation that indicates the one or more links.
2. The method of claim 1 , further comprising:
receiving, by the one or more processors, a command to apply the map suggestion; and
populating, by the one or more processors, a target field in the one or more target fields with a source field in the one or more source fields when the integration flow is executed.
3. The method of claim 1 , further comprising:
receiving, by the one or more processors, a user modification to the map suggestion; and
training, by the one or more processors, the trained algorithm with the user modification to improve future recommendations.
4. The method of claim 1 , further comprising:
receiving, by the one or more processors, a discard indicator to the map suggestion; and
training, by the one or more processors, the trained algorithm based on the discard indicator to improve future recommendations.
5. The method of claim 1 , further comprising:
translating, by the one or more processors, the map suggestion into a script in an expression language; and
displaying, by the one or more processors, the script in association with the map suggestion.
6. The method of claim 5 , further comprising:
receiving, by the one or more processors, an edit to the script;
applying, by the one or more processors, the edit to the map suggestion; and
displaying, by the one or more processors, the graphical representation of the map suggestion based on the edit.
7. The method of claim 1 , wherein the map suggestion further suggests a data transformation to perform on a source field in the one or more source fields.
8. A system, comprising:
a memory; and
at least one processor coupled to the memory and configured to:
display an integration flow comprising a source application and a target application in an integration flow design tool, wherein the source application sends one or more source fields to the target application as one or more target fields when the integration flow is executed;
determine a map suggestion for the integration flow using a trained algorithm ty applying a semantic dictionary to map the one or more source fields to the one or more target fields, wherein the map suggestion comprises one or more links between the one or more source fields and the one or more target fields; and
display the map suggestion in a graphical representation that indicates the one or more links.
9. The system of claim 8 , the at least one processor further configured to:
receive a command to apply the map suggestion; and
populate a target field in the one or more target fields with a source field in the one or more source fields when the integration flow is executed.
10. The system of claim 8 , the at least one processor further configured to:
receive a user modification to the map suggestion; and
train the trained algorithm with the user modification to improve future recommendations.
11. The system of claim 8 , the at least one processor further configured to:
receive a discard indicator to the map suggestion; and
train the trained algorithm based on the discard indicator to improve future recommendations.
12. The system of claim 8 , the at least one processor further configured to:
translate the map suggestion into a script in an expression language; and
display the script in association with the map suggestion.
13. The system of claim 12 , the at least one processor further configured to:
receive an edit to the script;
apply the edit to the map suggestion; and
display the graphical representation of the map suggestion based on the edit.
14. The system of claim 8 , wherein the map suggestion further suggests a data transformation to perform on a source field in the one or more source fields.
15. A method, comprising:
displaying, by one or more processors, an integration flow comprising a source application and a target application in an integration flow design tool, wherein the source application sends one or more source fields to the target application as one or more target fields when the integration flow is executed;
determining a map suggestion for the integration flow using a trained algorithm, wherein the map suggestion comprises one or more links between the one or more source fields to the one or more target fields;
translating the map suggestion into a script in an expression language; and
displaying the map suggestion in association with the script in a graphical representation that indicates the one or more links.
16. The method of claim 15 , further comprising:
receiving a command to apply the map suggestion; and
populating a target field in the one or more target fields with a source field in the one or more source fields when the integration flow is executed.
17. The method of claim 15 , wherein the map suggestion further suggests a data transformation to perform on a source field in the one or more source fields.
18. The method of claim 15 , further comprising:
receiving a user modification to the map suggestion; and
training the trained algorithm with the user modification to improve future recommendations.
19. The method of claim 15 , further comprising:
receiving a discard indicator to the map suggestion; and
training the trained algorithm based on the discard indicator to improve future recommendations.
20. The method of claim 15 , further comprising:
receiving an edit to the script;
applying the edit to the map suggestion; and
displaying the graphical representation of the map suggestion based on the edit.