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There are one column in each table, call id, to link them. --For incremental/New data----- insert into A select * from B where column_name NOT IN (select column_name from B); --For Edited Data------- cursore C_AB select * from B minus select * from A For R in C_AB loop Update A set....where ... this shows how I would approach getting the first two columns -- just add the other 2 and use merge to keep filling temp -- and then update the join: [email protected] -1 5 group by urefitem ) b 6 on (temp.urefitem = b.urefitem) 7 when matched then update set amount = b.sum_total 8 when not matched then insert (urefitem,amount) values ( b.urefitem, b.sum_total) 9 / 398 rows merged. using a cursor means you are back to "slow=very_true" you already WERE updating on a bulk basis??? But when I run the following query, it takes up 50% of CPU. tab A has these columns: id, cycle, pop tab B has these columns: id, cycle, site_id,rel_cd,groupid update tab A a set pop= (select count(*) from tab B b where a.cycle = b.cycle and b.site_id=44 and b.rel_cd in('code1','code2','code3') and b.groupid='123') where pop is null and id in(select id from tab B); call count cpu elapsed disk query current rows ------- ------ -------- ---------- ---------- ---------- ---------- ---------- Parse 1 0.00 0.00 0 0 0 0 Execute 2 496.35 499.54 7530955 9902630 76532 11444 Fetch 0 0.00 0.00 0 0 0 0 ------- ------ -------- ---------- ---------- ---------- ---------- ---------- total 3 496.35 499.54 7530955 9902630 76532 11444 Misses in library cache during parse: 0 Optimizer goal: CHOOSE Parsing user id: 305 Rows Row Source Operation ------- --------------------------------------------------- 1 UPDATE tab A 11445 MERGE JOIN 5942 VIEW VW_NSO_1 5942 SORT UNIQUE 31227 TABLE ACCESS FULL tab B 17385 SORT JOIN 12601 TABLE ACCESS FULL tab A Now my questions are: 1. We have several such updates that creates the same problems on the server from time to time and I would appreciate some guidance to resolve this.

Using cursor is ok, but it brings with a un-toleratable speed when operating on a large table. end loop End; It's working but taking a huge time/sometimes hang the computer. [email protected] update ( select upd.purchase_no u_pno, upd.amount u_a, 2 temp.purchase_no t_pno, temp.amount t_a 3 from upd, temp 4 where upd.urefitem = temp.urefitem ) 5 set u_pno = t_pno, u_a = t_a 6 / 635 rows updated. Is this time, 10 minutes for 12000 rows tables an acceptable (expected) time? Thanks Anandhi = b.cycle and b.site_id=44 and b.rel_cd in('code1','code2','code3') and b.groupid='123' 12,000 times?

The oncilla's jaw is shortened, with fewer teeth, but with well-developed carnassials and canines.

The oncilla is a primarily terrestrial animal, but is also an adept climber.

Elisabeth Hauptmann, Brecht’s assistant and collaborator, introduced him to the piece and translated the English libretto into German.

rnst Josef Aufricht, a young actor who became a producer when he inherited a big chunk of money, acquired the Theater am Schiffbauerdamm early in 1928 and was looking for a show. When he heard Kurt Weill was writing the score, however, he balked–Weill was considered a difficult avant-garde composer of opera at that time, and Aufricht feared that audiences would stay away.

This may seem like a simple question: Update Column a1 in Table A with all data in Column b1 in Table B. I have a table named A containing say 100000 records. HSCODELIST 5 WHERE not exists 6 (SELECT NULL FROM VIStemp. Brao what I suggest then is not to do it in a single sql statement -- just proving that "there are exceptions to every rule". Type ----------------------------------------- -------- ---------------------------- BIN VARCHAR2(10) ACT_SL VARCHAR2(3) ACT_CODE VARCHAR2(11) ACT_VAL NUMBER(14,2) ENTRY_DATE DATE SQL DESC VIS. Type ----------------------------------------- -------- ---------------------------- BIN VARCHAR2(10) ACT_SL VARCHAR2(3) ACT_CODE VARCHAR2(11) ACT_VAL NUMBER(14,2) ENTRY_DATE DATE SQL UPDATE (SELECT DBHSCODELIST. the database needs to know that each row in dbhscodelist will map to AT MOST one row in hscodelist - this mandates a primary or unqiue key constraint on the join columns this is discussed in the original answer above.

But I am trapped by the method that without using cursor to achieve it. I have another table B containg 10,000 records of incremented and edited records of A table. I am using the following codes to append data from B to A. Normally, I would try to use a single sql statment -- here, due to the "data being spread all over the place", and being distributed and all. We have a 2 CPU machine where at normal times, the topmost entry in top command shows only .2 or .3 percentage of CPU use. This is on a test database where nothing else is going on concurrently.

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