Comments in line. On 01/22/2004 12:24:26 PM, Tracy Rahmlow wrote:
This statement is from a batch program within a pl/sql procedure. (Also, I have many similar ones within the process) The policy table has approximately 6.2 million rows. The procedure is to incrementally(daily) build an extract table from multiple tables. The extract table is then used for reporting purposes. The statement performs well per policy, however it is being executed 43,000+ times. Is there a design option available to me to reduce the number of executions and be more scaleable?
ALTER DATABSE ENABLE OPTIMAL [DW|OLTP] DESIGN; statement will work
in Oracle 18e ("E" comes from expensive). Until then, I'd try materialized views. What you are trying to do is to build one table
based on selecting records from several others. If you reformulate
the previous sentence, you'll get the definition of a MV.
I am considering the creation of an index to incorporate both the policy_number and the pol_eff_date hopefully eliminating the table access.
We are currently on 8.1.7.
***************************************************************************************
SELECT MIN(P.POL_EFF_DATE) FROM PHXADM.POLICY P WHERE P.POLICY_NUMBER = :b1
call count cpu elapsed disk query current rows ------- ------ -------- ---------- ---------- ---------- ---------- ---------- Parse 1 0.00 0.01 0 0 0 0 Execute 43814 1.95 1.57 0 0 0 0 Fetch 43814 55.88 599.11 408248 568098 0 43814 ------- ------ -------- ---------- ---------- ---------- ---------- ---------- total 87629 57.83 600.69 408248 568098 0 43814
Misses in library cache during parse: 1 Optimizer goal: CHOOSE Parsing user id: 547 (RPTADM) (recursive depth: 1)
Rows Execution Plan ------- --------------------------------------------------- 0 SELECT STATEMENT GOAL: CHOOSE 0 SORT (AGGREGATE) 0 TABLE ACCESS GOAL: ANALYZED (BY INDEX ROWID) OF 'POLICY' 0 INDEX GOAL: ANALYZED (RANGE SCAN) OF 'POLICY_PK' (UNIQUE) American Express made the following annotations on 01/22/2004 10:24:24 AM ------------------------------------------------------------------------------ ******************************************************************************
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