By Giri Mandalika-Oracle on Sep 24, 2012
Different batch processes in Oracle Payroll flow have the ability to spawn multiple child processes (or threads) to complete the work in hand. The number of child processes to fork is controlled by the
THREADS parameter in
The default value for
THREADS parameter is 1, which is fine for a single-processor system but not optimal for the modern multi-core multi-processor systems. Setting the
THREADS parameter to a value equal to or less than the total number of [virtual] processors available on the system may improve the performance of payroll processing. However on the down side, since multiple child processes operate against the same set of payroll tables in HR schema, database may experience undesired consequences such as buffer busy waits and index contention, which results in giving up some of the gains achieved by using multiple child processes/threads to process the work. Couple of other action parameters,
CHUNK_SHUFFLE, help alleviate the database contention.
Set a value for
THREADS parameter as shown below.
CONNECT APPS/APPS_PASSWORD UPDATE PAY_ACTION_PARAMETERS SET PARAMETER_VALUE = DESIRED_VALUE WHERE PARAMETER_NAME = 'THREADS'; COMMIT;
(I am not aware of any maximum value for
The size of each commit unit for the batch process is controlled by the
CHUNK_SIZE action parameter. In other words, chunking is the act of splitting the assignment actions into commit groups of desired size represented by the
CHUNK_SIZE parameter. The default value is 20, and each thread processes one chunk at a time -- which means each child process inserts or processes 20 assignment actions at any time.
When multiple threads are configured, each thread picks up a chunk to process, completes the assignment actions and then picks up another chunk. This is repeated until all the chunks are exhausted.
It is possible to use different chunk sizes in different batch processes. During the initial phase of processing,
CHUNK_SIZE number of assignment actions are inserted into relevant table(s). When multiple child processes are inserting data at the same time into the same set of tables, as explained earlier, database may experience contention. The default value of 20 is mostly optimal in such a case. Experiment with different values for the initial phase by +/-10 for
CHUNK_SIZE parameter and observe the performance impact. A larger value may make sense during the main processing phase. Again experimentation is the key in finding the suitable value for your environment. Start with a large value such as 2000 for the chunk size, then increment or decrement the size by 500 at a time until an optimal value is found.
Set a value for
CHUNK_SIZE parameter as shown below.
CONNECT APPS/APPS_PASSWORD UPDATE PAY_ACTION_PARAMETERS SET PARAMETER_VALUE = DESIRED_VALUE WHERE PARAMETER_NAME = 'CHUNK_SIZE'; COMMIT;
CHUNK_SIZE action parameter accepts a value that is as low as 1 or as high as 16000.
CHUNK SHUFFLE parameter
By default, chunks of assignment actions are processed sequentially by all threads - which may not be a good thing especially given that all child processes/threads performing similar actions against the same set of tables almost at the same time. By saying not a good thing, I mean to say that the default behavior leads to contention in the database (in data blocks, for example).
It is possible to relieve some of that database contention by randomizing the processing order of chunks of assignment actions. This behavior is controlled by the
CHUNK SHUFFLE action parameter. Chunk processing is not randomized unless explicitly configured.
Set chunk shuffling as shown below.
CONNECT APPS/APPS_PASSWORD UPDATE PAY_ACTION_PARAMETERS SET PARAMETER_VALUE = 'Y' WHERE PARAMETER_NAME = 'CHUNK SHUFFLE'; COMMIT;
Finally I recommend checking the following document out for additional details and additional pay action tunable parameters that may speed up the processing of Oracle Payroll.
My Oracle Support Doc ID: 226987.1 Oracle 11i & R12 Human Resources (HRMS) & Benefits (BEN) Tuning & System Health Checks
Also experiment with different combinations of parameters and values until the right set of action parameters and values are found for your deployment.