Generate in-memory views from universe schema
View Patent ↗In one aspect, a Universe designed and built in a database is used for modeling data in an in-memory database. The Universe is loaded in a front-end development application to display a universe schema contained in the Universe. The logic built in the front-end development application enables parsing the universe schema, to determine patterns matching in-memory views such as attribute views and analytic views. The determined patterns are generated as attribute views and analytic views, and displayed for user selection. Selected attribute views and analytic views are stored in the in-memory database.
1. An article of manufacture including a non-transitory computer readable storage medium to tangibly store instructions, which when executed by a computer, cause the computer to:
determine a first pattern comprising a first table with one join and a one-to-many join relationship with a second table;
based on the determined first pattern, generate a first attribute view with the first table and the second table;
determine a second pattern comprising a fact table with more than two joins, more than one numeric field and a many-to-one join relationship with one or more adjoining tables in a star schema;
based on the determined second pattern, generate an analytic view with the fact table and the one or more adjoining tables of the fact table;
determine a fourth pattern comprising a fourth table with more than two joins and a many-to-one join relationship with a fifth table, wherein the fourth table is not the fact table; and
based on the determined fourth pattern, generate a second attribute view with the fourth table and the fifth table.
2. The article of manufacture of claim 1 , further comprising instructions which when executed by the computer further causes the computer to:
determine a third pattern comprising the second table with two joins and a one-to-many join relationship with a third table; and
based on the determined third pattern, add the third table to the generated attribute view.
3. The article of manufacture of claim 1 , further comprising instructions which when executed by the computer further causes the computer to:
load a universe schema at a front-end development application, wherein the universe schema defines relationships between tables and joins; and
parse the universe schema to traverse the tables.
4. The article of manufacture of claim 1 , further comprising instructions which when executed by the computer further causes the computer to:
display the generated attribute view and the generated analytic view in a front-end development application for user selection; and
based on the user selection, store the selected attribute view and the selected analytic view in an in-memory database.
5. The article of manufacture of claim 1 , wherein the attribute view is an in-memory attribute view and the analytic view is an in-memory analytic view.
6. The article of manufacture of claim 1 , further comprising instructions which when executed by the computer further causes the computer to:
determine a fifth pattern comprising a seventh table with more than two joins and a many-to-one join relationship with the second table, wherein the seventh table is not the fact table and the second table is in the first attribute view; and
based on the determined fifth pattern, add the seventh table to the generated first attribute view.
7. A computer implemented method for generating in-memory views from universe, the method comprising:
determining a first pattern comprising a first table with one join and a one-to-many join relationship with a second table;
based on the determined first pattern, generating a first attribute view with the first table and the second table;
determining a second pattern comprising a fact table with more than two joins, more than one numeric field and a many-to-one join relationship with one or more adjoining tables in a star schema;
based on the determined second pattern, generating an analytic view with the fact table and the one or more adjoining tables of the fact table;
determining a fourth pattern comprising a fourth table with more than two joins and a many-to-one join relationship with a fifth table, wherein the fourth table is not the fact table; and
based on the determined fourth pattern, generate a second attribute view with the fourth table and the fifth table.
8. The method of claim 7 , further comprising:
determining a third pattern comprising the second table with two joins and a one-to-many join relationship with a third table; and
based on the determined third pattern, add the third table to the generated attribute view.
9. The method of claim 7 , further comprising:
loading a universe schema at a front-end development application, wherein the universe schema defines relationships between tables and joins; and
parsing the universe schema to traverse the tables.
10. The method of claim 7 , further comprising:
displaying the generated attribute view and the generated analytic view in a front-end development application for user selection; and
based on the user selection, storing the selected attribute view and the selected analytic view in an in-memory database.
11. The method of claim 7 , wherein the attribute view is an in-memory attribute view and the analytic view is an in-memory analytic view.
12. The method of claim 7 , further comprising:
determining a fifth pattern comprising a seventh table with more than two joins and a many-to-one join relationship with the second table, wherein the seventh table is not the fact table and the second table is in the first attribute view; and
based on the determined fifth pattern, add the seventh table to the generated first attribute view.
13. A computer system for in-memory analysis scenario builder, comprising:
a computer memory to store program code; and
a processor to execute the program code to:
determine a first pattern comprising a first table with one join and a one-to-many join relationship with a second table;
based on the determined first pattern, generate a first attribute view with the first table and the second table;
determine a second pattern comprising a fact table with more than two joins, more than one numeric field and a many-to-one join relationship with one or more adjoining tables in a star schema; and
based on the determined second pattern, generate an analytic view with the fact table and the one or more adjoining tables of the fact table;
determine a fourth pattern comprising a fourth table with more than two joins and a many-to-one join relationship with a fifth table, wherein the fourth table is not the fact table; and
based on the determined fourth pattern, generate a second attribute view with the fourth table and the fifth table.
14. The system of claim 13 , wherein the processor further executes the program code to:
load a universe schema at a front-end development application, wherein the universe schema defines relationships between tables and joins; and
parse the universe schema to traverse the tables.
15. The system of claim 13 , wherein the processor further executes the program code to:
display the generated attribute view and the generated analytic view in a front-end development application for user selection; and
based on the user selection, store the selected attribute view and the selected analytic view in an in-memory database.
16. The system of claim 13 , wherein the attribute view is an in-memory attribute view and the analytic view is an in-memory analytic view.
17. The system of claim 13 , wherein the processor further executes the program code to:
determine a fifth pattern comprising a seventh table with more than two joins and a many-to-one join relationship with the second table, wherein the seventh table is not the fact table and the second table is in the first attribute view; and
based on the determined fifth pattern, add the seventh table to the generated first attribute view.
18. A computer system of claim 13 , wherein the processor further executes the program code:
determine a third pattern comprising the second table with two joins and a one-to-many join relationship with a third table; and
based on the determined third pattern, add the third table to the generated attribute view.