UPDATING CACHED DATABASE QUERY RESULTS

• US 20140052750A1
• Filed: 08/14/2012
• Published: 02/20/2014
• Est. Priority Date: 08/14/2012
• Status: Active Grant

• Current Assignee: Amadeus (Amadeus Global Travel Distribution S.A.)
• Original Assignee: Amadeus (Amadeus Global Travel Distribution S.A.)
• Inventors: Ciabrini, Damien, Legrand, Guillaume, Janin, Benoit, Isnardy, Luc, Maillot, Nicolas, Robelin, Charles-Antoine, Daniello, Rudy
• Granted Patent: US 9,235,620 B2
• Time in Patent Office: Days
• US Class Current: 707/769
• CPC Class Codes: G06F 16/24552 Database cache management
• CPC Class Codes: G06Q 10/02 Reservations, e.g. for tickets, services or events

Abstract

A data cache platform maintains pre-computed database query results computed by a computation platform based on data maintained in the computation platform and is configured to determine probabilities of the cached database query results being outdated, to automatically issue re-computation orders to the computation platform for updating cached database query results on the basis of the determined probabilities of the pre-computed database query results being outdated and to receive the updated pre-computed database query results as results of the re-computation orders. The probability determination depends on a probabilistic model and on the occurrence of asynchronous real-time events. The real-time events are indeterministic with regard to the expiration of the cached database query results and only have a probabilistic influence on the discrepancies between the cached database query results maintained in the data cache platform and presumed actual database query results.

Claims

1. A method of updating cached database query results in a distributed database system, wherein the distributed database system comprises a data cache platform maintaining the pre-computed database query results and a computation platform for computing the cached database query results based on data maintained in the computation platform, the method comprising:

determining, by the data cache platform, probabilities of the cached database query results being outdated, wherein

the determination depends on a probabilistic model and on the occurrence of asynchronous real-time events,

the probabilistic model models discrepancies between the cached database query results maintained in the data cache platform and presumed actual database query results,

the real-time events are indeterministic with regard to the expiration of the cached database query results and only have a probabilistic influence on the discrepancies between the cached database query results maintained in the data cache platform and presumed actual database query results,

the probabilities are generally determined based on the probabilistic model and are possibly amended on the occurrence of asynchronous real-time events;

automatically issuing, by the data cache platform, re-computation orders to the computation platform for updating cached database query results on the basis of the determined probabilities of the pre-computed database query results being outdated, wherein cached database query results having a higher probability of being outdated than others are ordered to be re-computed; and

receiving, at the data cache platform, the updated pre-computed database query results as results of the re-computation orders.

2. The method of claim 1, wherein the probabilistic model models a volatility of the data maintained in the computation platform based on statistical historic data.

3. The method of claim 1 further comprising

analyzing, at the data cache platform, whether incoming asynchronous real-time events are represented in the probabilistic model;

for real-time events which are not represented in the probabilistic model, issuing re-computation orders regarding the respective particular cached database query results as soon as possible;

for real-time events which are represented in the probabilistic model, accumulating such real-time events over a certain period of time, comparing the actually occurred and accumulated real-time events with their representation in the probabilistic model and, if the actually occurred accumulated real-time events deviate from their representation in the probabilistic model to a predetermined extent, issuing re-computation orders with respect to potentially affected cached database query results as soon as possible.

4. The method of claim 1, wherein the data cache platform, when determining the probabilities of the cached database query results of being outdated and issuing the re-computation, considers grids of cached database query results corresponding to groups of adjacent sets of data maintained in the computation platform.

5. The method of claim 1, wherein the data cache platform issues the re-computation orders based on the amount of available computation resources at the computation platform.

6. The method of claim 1, wherein the distributed database system is a travel reservation system, wherein the computation platform maintains information on travel availability and fares and the data cache platform maintains priced travel recommendations calculated from the travel availability information and the fares.

7. The method of claim 6, wherein the real-time events comprise flight fare changes, airplane seat availability changes, client flight ticket requests and/or flight cancellations.

8. The method of claim 1, wherein the distributed database system comprises at least one application platform connected to the computation platform, the at least one application platform maintaining and organizing the pre-computed database query results, the database query results stored in the at least one application platform being populated and/or updated by the computation platform as a result of the re-computation orders issued by the data cache platform.

9. A data cache platform maintaining pre-computed database query results computed by a computation platform based on data maintained in the computation platform, the data cache platform configured to:

determine probabilities of the cached database query results being outdated,

wherein the determination depends on a probabilistic model and on the occurrence of asynchronous real-time events,

wherein the probabilistic model modeling discrepancies between the cached database query results maintained in the data cache platform and presumed actual database query results,

wherein the real-time events are indeterministic with regard to the expiration of the cached database query results and only have a probabilistic influence on the discrepancies between the cached database query results maintained in the data cache platform and presumed actual database query results,

wherein the probabilities are generally determined based on the probabilistic model and are possibly amended on the occurrence of asynchronous real-time events;

automatically issue re-computation orders to the computation platform for updating cached database query results on the basis of the determined probabilities of the pre-computed database query results being outdated, wherein cached database query results having a higher probability of being outdated than others are ordered to be re-computed; and

receive the updated pre-computed database query results as results of the re-computation orders.

10. The data cache platform of claim 9, wherein the probabilistic model models a volatility of the data maintained in the computation platform based on statistical historic data.

11. The data cache platform of claim 9, being further configured to

analyze whether incoming asynchronous real-time events are represented in the probabilistic model;

for real-time events which are not represented in the probabilistic model, issue re-computation orders regarding the respective particular cached database query results as soon as possible;

for real-time events which are represented in the probabilistic model, accumulate such real-time events over a certain period of time, compare the actually occurred and accumulated real-time events with their representation in the probabilistic model and, if the actually occurred accumulated real-time events deviate from their representation in the probabilistic model to a predetermined extent, issue re-computation orders with respect to potentially affected cached database query results as soon as possible.

12. The data cache platform of claim 9, being further configured to consider grids of cached database query results corresponding to groups of adjacent sets of data maintained in the computation platform when determining the probabilities of the cached database query results of being outdated and issuing the re-computation.

13. The data cache platform of claim 9, being further configured to issue the re-computation orders based on the amount of available computation resources at the computation platform.

14. The data cache platform of claim 9, being arranged as a data cache platform in a travel reservation system, wherein the computation platform maintains information on travel availability and fares and the data cache platform maintains priced travel recommendations calculated from the travel availability information and the fares.

15. The data cache platform of claim 14, wherein the real-time events comprise flight fare changes, airplane seat availability changes, client flight ticket requests and/or flight cancellations.

16. A travel reservation system comprising a data cache platform maintaining cached priced travel recommendations computed by a computation platform based on travel availability data and fares maintained in the computation platform, the data cache platform configured to:

determine probabilities of the cached priced travel recommendations being outdated,

wherein the determination depends on a probabilistic model and on the occurrence of asynchronous real-time events,

wherein the probabilistic model modeling discrepancies between the cached priced travel recommendations maintained in the data cache platform and presumed actual priced travel recommendations,

wherein the real-time events are indeterministic with regard to the expiration of the cached priced travel recommendations and only have a probabilistic influence on the discrepancies between the cached priced travel recommendations maintained in the data cache platform and presumed actual priced travel recommendations,

wherein the probabilities are generally determined based on the probabilistic model and are possibly amended on the occurrence of asynchronous real-time events;

automatically issue re-computation orders to the computation platform for updating cached priced travel recommendations on the basis of the determined probabilities of the pre-computed priced travel recommendations being outdated, wherein cached priced travel recommendations having a higher probability of being outdated than others are ordered to be re-computed; and

receive the updated pre-computed priced travel recommendations as results of the re-computation orders.

17. The travel reservation system of claim 16, wherein the data cache platform is further configured to

analyze whether incoming asynchronous real-time events are represented in the probabilistic model;

for real-time events which are not represented in the probabilistic model, issue re-computation orders regarding the respective particular cached database query results as soon as possible;

for real-time events which are represented in the probabilistic model, accumulate such real-time events over a certain period of time, compare the actually occurred and accumulated real-time events with their representation in the probabilistic model and, if the actually occurred accumulated real-time events deviate from their representation in the probabilistic model to a predetermined extent, issue re-computation orders with respect to potentially affected cached database query results as soon as possible.

18. The travel reservation system of claim 16, further comprising:

at least one application platform connected to the computation platform, the at least one application platform maintaining and organizing the pre-computed priced travel recommendations to make them available for travel customers, the priced travel recommendations stored in the at least one application platform being populated or updated by the computation platform as a result of the re-computation orders issued by the data cache platform.

19. A computer readable storage medium having computer program instructions stored therein, which when executed on a computer system cause the computer system to:

determine probabilities of cached database query results being outdated,

wherein the determination depends on a probabilistic model and on the occurrence of asynchronous real-time events,

wherein the probabilistic model modeling discrepancies between the cached database query results maintained in the computer system and presumed actual database query results,

wherein the real-time events are indeterministic with regard to the expiration of the cached database query results and only have a probabilistic influence on the discrepancies between the cached database query results maintained in the computer system and presumed actual database query results,

wherein the probabilities are generally determined based on the probabilistic model and are possibly amended on the occurrence of asynchronous real-time events;

automatically issue re-computation orders for updating cached database query results on the basis of the determined probabilities of the pre-computed database query results being outdated, wherein cached database query results having a higher probability of being outdated than others are ordered to be re-computed; and

receive the updated pre-computed database query results as results of the re-computation orders.