Parallel processing historical data

Patent metadata

Field	Value
Publication number	US-11055731-B2
Application number	US-201916373602-A
Country	US
Kind code	B2
Filing date	Apr 2, 2019
Priority date	Apr 8, 2013
Publication date	Jul 6, 2021
Grant date	Jul 6, 2021

Abstract

Disclosed are methods and apparatuses for generating simulations on the fly using large historical data and forecast data. To improve system performance, the large historical data are processed in parallel.

First claim

What is claimed is:

1. A method implemented with a processor for generating a report, comprising:
running a simulation based at least in part on a simulation period, simulation information, and a plurality of subsets of the simulation period at least by:
performing historical charting with parallel processing at least by:
building multiple thread groups for work, wherein the work is divided among a plurality of threads according to date ranges;
performing fetches of historical data in parallel via the plurality of threads; and
concatenating results from the fetches based at least in part upon an ordering of the date ranges processed by the plurality of threads; and

performing future forecast charting at least by:
receiving forecast data corresponding to one or more subsets of the plurality of subsets of the simulation period; and
generating data corresponding to the simulation period; and

generating the report of the simulation to be displayed to a user or saved on a database; and
updating a scaling to chart result data, wherein concatenating the results comprises concatenating the results from the fetches into an XML string structure based at least in part upon an ordering of the date ranges processed by the plurality of threads.

2. The method of claim 1 , further comprising receiving the simulation period, the simulation information, and the plurality of subsets of the simulation period corresponding to a first granularity of results to be provided in a report of a simulation, wherein a subset of the plurality of subsets of the simulation period corresponds to a time period within the simulation period, wherein a granularity of results is a unit of time corresponding to the results.

3. The method of claim 1 , wherein chart data within the XML string structure is concatenated with respective results from succeeding threads that respectively processed corresponding portions of the work according to the ordering of the date ranges.

4. The method of claim 2 , wherein the one or more subsets of the plurality of subsets of the simulation period comprise a second granularity of results.

5. The method of claim 4 , further comprising identifying a mismatch between the first granularity for the report of the simulation and the second granularity of results from the forecast data, wherein the mismatch is due to the first granularity for the report of the simulation being different than the second granularity of results from the forecast data.

6. The method of claim 1 , wherein the simulation period comprises a start date and a number of periods.

7. The method of claim 1 , wherein the simulation period includes both past and future time.

8. The method of claim 1 , wherein simulation information comprises product information, customer information, or product location information.

9. The method of claim 1 , further comprising loading a saved report and displaying the report with the saved report.

10. The method of claim 1 , wherein the forecast data is generated before receiving the simulation period and the simulation information.

11. A computer program product including a non-transitory computer readable medium having instructions which, when executed by a processor, causes the processor to perform a process for generating a report, the process comprising:
running a simulation based at least in part on a simulation period, simulation information, and a plurality of subsets of the simulation period at least by:
performing historical charting with parallel processing at least by:
building multiple thread groups for work, wherein the work is divided among a plurality of threads according to date ranges;
performing fetches of historical data in parallel via the plurality of threads; and
concatenating results from the fetches based at least in part upon an ordering of the date ranges processed by the plurality of threads; and

performing future forecast charting at least by:
receiving forecast data corresponding to one or more subsets of the plurality of subsets of the simulation period; and
generating data corresponding to the simulation period;

generating the report of the simulation to be displayed to a user or saved on a database; and
updating a scaling to chart result data, wherein concatenating the results comprises concatenating the results from the fetches into an XML string structure based at least in part upon an ordering of the date ranges processed by the plurality of threads.

12. The computer program product of claim 11 , wherein the process further comprises receiving the simulation period, the simulation information, and the plurality of subsets of the simulation period corresponding to a first granularity of results to be provided in a report of a simulation, wherein a subset of the plurality of subsets of the simulation period corresponds to a time period within the simulation period, wherein a granularity of results is a unit of time corresponding to the results.

13. The computer program product of claim 11 , wherein chart data within the XML string structure is concatenated with respective results from succeeding threads that respectively processed corresponding portions of the work according to the ordering of the date ranges.

14. The computer program product of claim 12 , wherein the one or more subsets of the plurality of subsets of the simulation period comprise a second granularity of results.

15. The computer program product of claim 14 , wherein the process further comprises identifying a mismatch between the first granularity for the report of the simulation and the second granularity of results from the forecast data, wherein the mismatch is due to the first granularity for the report of the simulation being different than the second granularity of results from the forecast data.

16. The computer program product of claim 11 , wherein the simulation period comprises a start date and a number of periods.

17. The computer program product of claim 11 , wherein the simulation period includes both past and future time.

18. The computer program product of claim 11 , wherein simulation information comprises product information, customer information, or product location information.

19. The computer program product of claim 11 , wherein the process further comprises loading a saved report and displaying the report with the saved report.

20. The computer program product of claim 11 , wherein the forecast data is generated before receiving the simulation period and the simulation information.

21. A system for generating a report, comprising:
a processor; and
a memory to hold program code instructions, in which the program code instructions comprises program code to perform:
running a simulation based at least in part on a simulation period, simulation information, and a plurality of subsets of the simulation period at least by:
performing historical charting with parallel processing at least by:
building multiple thread groups for work, wherein the work is divided among a plurality of threads according to date ranges;
performing fetches of historical data in parallel via the plurality of threads; and
concatenating results from the fetches based at least in part upon an ordering of the date ranges processed by the plurality of threads; and

performing future forecast charting at least by:
receiving forecast data corresponding to one or more subsets of the plurality of subsets of the simulation period; and
generating data corresponding to the simulation period;

Assignees

• Oracle Int Corp

Inventors

• Mitchell Kara
• Johnson Aaron
• Vance Eric

Classifications

• G06Q30/0201

  Market modelling; Market analysis; Collecting market data · CPC title

• G06Q30/0202 Primary

  Market predictions or forecasting for commercial activities · CPC title