Updating a cursor

Even the idea create a temporary table holding only primary key and Column b, and then apply cursor to it is slow. Would u please help me how can i faster my procedure.u have given information 9i it same for oracle8i & dev6i.please help me Thank u very much for ur kind update information is really nice and working very insert----same prolem. That means -- just using math here -- that we have 600 seconds, 12,000 queries to run, 12000/60 = 20, so we are doing 20 per second -- or each query is taking 0.05 cpu seconds to run. do anything 12,000 times and you might have a problem tho! this might be one of the rare times that a temp table can be useful.

I am think of the way without using cursor, script as below. I don't understand what's the problem.i am going to give u full overview of my problem. The software is available in different portion of the country for data entry and report generation etc. What about: create global temporary table gtt ( id int primary key, cnt int ) on commit delete rows / you'll add that ONCE, it'll become part of your schema forever....

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 b.id=and 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?

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But the 2nd Where clause simply return the message of `more than one row is return', since the id is unpredictable and this create a `many to many' relationship in both tables. Many Thanks, (script) REM* the where-clause of the update cannot work UPDATE table b SET column_b1 = ( SELECT MAX(column_a1) FROM table_a a, table_b b WHERE a.id=GROUP BY a.id) WHERE table_IN (SELECT MIN(id) FROM table_a GROUP BY id); Your example is somewhat confusing -- you ask "update column a1 in table a where data in column b1 in table b" but your update shows you updating column b1 in table B with some data from table a. Every month the client office is to give data(NEW & EDITED) "BY DATE RANGWISE" to the headoffice in CD. Now, you "two step" it: insert into gtt select b.id, count(*) cnt from tabb b, taba a where = and a.cycle = b.cycle and b.site_id = 44 and b.rel_cd in ( 'code1', 'code2', 'code3' ) and b.groupid = '123' and is null group by / that gets all of the id/cnts for only the rows of interest.

Additionally -- given the way the where and set clauses are CODED in the above -- it would succeed. The Headoffice is merge the data into their system. For migration data first of all i create another temporary user named VISTEMP then cotinuing this kinds of code insert into VISTEMP. Now we can update the join: update ( select a.pop, from taba a, gtt b where = ) set pop = cnt / and thats it. Hi Tom, I’m selecting approximately 1 million records from some tables and populating another set of tables.

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