log event is as shown in the above thread in my log event the error field is logged with multiple error codes for different item ids or no errors yet all in each event as shown below and requirement is to get each error code split up with percentages error=138021380=404.IMS.STORE.100;500.IMS.PRICE.103:42068997=400.IMS.STORE.100 number of itemids passed in each request is logged under responseSize field which is been extracted responseSize=3 So each event has different instances of errors and responseSize for example in a event there is 3 items passed but two items has 3 different error codes as above similarly another event has different instances of errors or no errors with different item size ,so i would like to compute error ratio like ratio = (each type of error code count)/(total num of items in all events) each type error code count = (event1 no of times (404.IMS.STORE.100) +event2 no of times(404.IMS.STORE.100) +...+eventN no of times (404.IMS.STORE.100)) second error code count = (event1 no of times (500.IMS.PRICE.103) +event2 no of times (500.IMS.PRICE.103) +...+eventN no of times(500.IMS.PRICE.103)) total no of items = (event1responseSize1+event2responseSize2+.....+eventNresponseSizeN) Note: responseSize has to be considered for all events not only error related as errorcode % is determined on all the item size from all events expected output error errorcount total_items errorratio 404.IMS.STORE.100 example 62 times example 14577(total items count) 62/14577 400.IMS.OFFER.103 example 54 times example 14577(total items count) 54/14577 500.IMS.PRICE.103 example 77 times example 14577(total items count) 77/14577 so basically all different error code split up with ratio of those error percentages is the expected outcome, hope i am able to present clearly
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