Modifying an analytic flow
US-2016154634-A1 · Jun 2, 2016 · US
US10419586B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10419586-B2 |
| Application number | US-201514665825-A |
| Country | US |
| Kind code | B2 |
| Filing date | Mar 23, 2015 |
| Priority date | Mar 23, 2015 |
| Publication date | Sep 17, 2019 |
| Grant date | Sep 17, 2019 |
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The present disclosure describes methods, systems, and computer program products for data-centric integration modeling in an application integration system. One computer-implemented method includes receiving, by operation of an integration system, a logic integration program comprising a plurality of logic integration patterns that are defined in a data-centric logic integration language; generating a logical model graph based on the logic integration program, the logical model graph being runtime-independent; converting the logical model graph into a physical model graph, the physical model graph being runtime-specific; and generating logic integration runtime codes executable by the integration system based on the physical model graph.
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What is claimed is: 1. A computer-implemented method comprising: receiving, by operation of an integration system, a logic integration program comprising a plurality of logic integration patterns that are defined in a data-centric logic integration language; generating a logical model graph based on the logic integration program, the logical model graph being runtime-independent; bi-directionally converting the logical model graph into a physical model graph, the physical model graph being runtime-specific, wherein converting the logical model graph into a physical model graph comprises: detecting logic integration patterns of the logical model graph as detected logic integration patterns; and synthesizing one or more message channels based on the detected logic integration patterns; and generating logic integration runtime codes executable by the integration system based on the physical model graph. 2. The method of claim 1 , further comprising defining the logic integration program using the data-centric logic integration language for declarative integration programming. 3. The method of claim 2 , wherein defining a logic integration program comprises: analyzing integration logic represented by the logical model graph; and adding integration artifacts. 4. The method of claim 1 , wherein the logical model graph comprises one or more annotations defined by the data-centric logic integration language as one or more nodes of the logical model graph. 5. The method of claim 1 , wherein the logical model graph comprises no cycles. 6. The method of claim 1 , wherein converting the logical model graph into the physical model graph comprises: detecting patterns on the logical model graph; and performing a rule-based transformation of the patterns on the logical model graph; and mapping into implementation-specific messaging channels. 7. The method of claim 6 , further comprising optimizing the logical model graph. 8. A non-transitory, computer-readable medium storing computer-readable instructions executable by a computer and configured to: receive a logic integration program comprising a plurality of logic integration patterns that are defined in a data-centric logic integration language; generate a logical model graph based on the logic integration program, the logical model graph being runtime-independent; bi-directionally convert the logical model graph into a physical model graph, the physical model graph being runtime-specific, wherein converting the logical model graph into a physical model graph comprises: detect logic integration patterns of the logical model graph as detected logic integration patterns; and synthesize one or more message channels based on the detected logic integration patterns; and generate logic integration runtime codes executable by the integration system based on the physical model graph. 9. The medium of claim 8 , the instructions further executable by the computer and configured to define the logic integration program using the data-centric logic integration language for declarative integration programming. 10. The medium of claim 9 , wherein defining a logic integration program comprises: analyzing integration logic represented by the logical model graph; and adding integration artifacts. 11. The medium of claim 8 , wherein the logical model graph comprises one or more annotations defined by the data-centric logic integration language as one or more nodes of the logical model graph. 12. The medium of claim 8 , wherein the logical model graph comprises no cycles. 13. The medium of claim 8 , wherein converting the logical model graph into the physical model graph comprises: detecting patterns on the logical model graph; and performing a rule-based transformation of the patterns on the logical model graph; and mapping into implementation-specific messaging channels. 14. The medium of claim 13 , the instructions further executable by the computer and configured to optimize the logical model graph. 15. A system, comprising: a memory; at least one hardware processor interoperably coupled with the memory and configured to: receive a logic integration program comprising a plurality of logic integration patterns that are defined in a data-centric logic integration language; generate a logical model graph based on the logic integration program, the logical model graph being runtime-independent; bi-directionally convert the logical model graph into a physical model graph, the physical model graph being runtime-specific, wherein converting the logical model graph into a physical model graph comprises: detect logic integration patterns of the logical model graph as detected logic integration patterns; and synthesize one or more message channels based on the detected logic integration patterns; and generate logic integration runtime codes executable by the integration system based on the physical model graph. 16. The system of claim 15 , the processor further configured to define the logic integration program using the data-centric logic integration language for declarative integration programming. 17. The system of claim 15 , wherein defining a logic integration program comprises: analyzing integration logic represented by the logical model graph; and adding integration artifacts. 18. The system of claim 15 , wherein the logical model graph comprises one or more annotations defined by the data-centric logic integration language as one or more nodes of the logical model graph. 19. The system of claim 15 , wherein the logical model graph comprises no cycles. 20. The system of claim 15 , wherein converting the logical model graph into the physical model graph comprises: detecting patterns on the logical model graph; optimizing the logical model graph; and performing a rule-based transformation of the patterns on the logical model graph; and mapping into implementation-specific messaging channels.
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