Method and system for data processing in a shared database environment

1 . A system for data processing in a shared database environment, comprising:

a data frame source for providing data frames; and

a configurable data processing device for a plurality of processes operating in parallel on one or more than one database entry in the database, the configurable data processing device for classifying each process as a contributing process or a synchronizing process, the contributing process providing data associated with the data frame, the synchronizing process implementing atomic read and update to the database entry based on the data provided by one or more than one contributing process.

2 . A system as claimed in claim 1 , wherein when one synchronizing process is executing in its critical section for the database entry, the configurable data processing device prohibits the other processes from accessing that database entry.

3 . A system as claimed in claim 1 , wherein the synchronizing process amalgamates data from the one or more than one contributing process into a single database update.

4 . A system as claimed in claim 1 , wherein the configurable data processing device allows a process to implement the behavior of the contributing process or the synchronization process.

5 . A system as claimed in claim 1 , wherein the configurable data processing device includes a module for determining a state of update operation, and wherein the configurable data processing device allows a process to implement the behavior of the contributing process or the synchronization process in dependence upon the state.

6 . A system as claimed in claim 5 , wherein the configurable data processing device includes a counting semaphore “a” that is atomically incremented or decremented by the process, and wherein the state of update operation is determined in dependence upon “a”.

7 . A system as claimed in claim 6 , wherein the configurable data processing device allocates contributing processes and synchronizing processes at the rate of b: 1 where “b” is a positive integer, and wherein each process has an identification number “c”, and wherein the state of update operation is determined in dependence upon a combination of “a”, “b” and “c”.

8 . A system as claimed in claim 1 , wherein the synchronizing process implements reading the database entry, performing a function, updating the database entry based on the data collected from the one or more contributing processes, and communicating the result to the contributing process.

9 . A system as claimed in claim 1 , wherein the plurality of processes are associated with at least one database related operation including policing and metering, financial transaction processing and telemetry processing.

10 . A system as claimed in claim 9 , wherein the database includes a record to be atomically updated.

11 . A system as claimed in claim 1 , wherein the update includes a non-trivial function of the database entry's current state and the state of the updating process.

12 . A system as claimed in claim 1 , wherein the aggregate arrival rate of the data frames is greater than a single process's database update rate.

13 . A method for data processing with a plurality of processes operating in parallel on one or more than one database entry in a database, comprising the steps of:

receiving data frames; and

classifying each process as a contributing process or a synchronizing process, the contributing process providing data associated with the data frame, the synchronizing process implementing atomic read and update to the database entry based on the data provided by one or more than one contributing process.

14 . A method as claimed in claim 13 , further comprising the step of:

when one synchronizing process is executing in its critical section for the database entry, prohibiting the other processes for accessing that database entry.

15 . A method as claimed in claim 13 , further comprising the step of:

in the synchronizing process, amalgamating data from the one or more than one contributing process into a single database update.

16 . A method as claimed in claim 13 , wherein the classifying step includes the step of:

allowing a process to implement the behavior of the contributing process or the synchronization process.

17 . A method as claimed in claim 13 , wherein the classifying step includes the steps of:

determining a state of update operation; and

allowing a process to implement the behavior of the contributing process or the synchronization process in dependence upon the state.

18 . A method as claimed in claim 17 , further comprising the step of:

atomically incrementing or decrementing a counting semaphore “a” by the process,

and wherein the determining step determines the state of update operation in dependence upon “a”.

19 . A method as claimed in claim 18 , further comprising the steps of:

allocating contributing processes and synchronizing processes at the rate of b: 1 where “b” is a positive integer; and

setting an identification number “c” to each process,

and wherein the determining step determines the state of update operation in dependence upon a combination of “a”, “b” and “c”.

20 . A method as claimed in claim 13 , further comprising the steps of:

in the synchronizing process,

reading the database entry;

performing a function;

updating the database entry based on the data collected from the one or more contributing processes; and

communicating the result to the contributing process.

21 . A method as claimed in claim 13 , wherein the plurality of processes are associated with at least one database related operation including policing and metering, financial transaction processing and telemetry processing.

22 . A method as claimed in claim 21 , further comprising the step of:

implementing atomic read and update of a record in the database.

23 . A method as claimed in claim 13 , wherein the update includes a non-trivial function of the database entry's current state and the state of the updating process.

24 . A method as claimed in claim 13 , wherein the aggregate arrival rate of the data frames is greater than a single process's database update rate.