More Statistics from your Batch Jobs, UBE performance statistics

 

F986114 is great, shows you some good statistical data for when the job actually run and ended, not taking into consideration queue time.

The query below is extracting the UBE performance data between 15/12/2016 and 19/12/2016.  Note that the times written in F986114 are UTC, so in the example below, I needed to add 13 hours to get the NZ timezone (+interval ‘13’ hour) for the data I was reporting on.  You need to workout your own offset https://en.wikipedia.org/wiki/List_of_UTC_time_offsets

SELECT JCPID as REPORT_NAME, JCVERS as VERSION, simd || vrjd AS DESCRIPTION, TO_CHAR((JCSTDTIM + interval '13' hour),'DDMMYYYY HH24:MI:SS') AS "START TIME", TO_CHAR((JCETDTIM + interval '13' hour),'DDMMYYYY HH24:MI:SS') AS "END TIME",  jcjobnbr
  from svm900.f986114,ol900.f9860, py900.f983051
  where trim(jcpid) = trim(siobnm) and trim(jcvers) = trim (vrvers) and trim(jcpid) = trim (vrpid) and jcjobsts = 'D'
  and (JCETDTIM + interval '13' hour) < TO_DATE('25122016','DDMMYYYY') and (JCETDTIM + interval '13' hour) >= TO_DATE('19122016', 'DDMMYYYY')
;

You can then put this data into excel and run any number of pivot tables over the top to extract slow jobs / fast jobs etc.

Regular analysis will allow you to eval trends and also work out if you have problems somewhere in JDE.