Updating bulk of code in query

1) By default, the UPDATE STATISTICS statement updates both index and column statistics.

Using the COLUMNS option of this statement will update column statistics only.

It is a general concept that encompasses lists, arrays, and other familiar datatypes.

Each element has a unique subscript that determines its position in the collection.

Using UPDATE STATISTICS WITH FULLSCAN will scan the entire table.

3) Rebuilding an index, for example by using the ALTER INDEX …

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?

To use collections in an application, you define one or more PL/SQL types, then define variables of those types.

Using the INDEX option will update index statistics only.

2) By default, the UPDATE STATISTICS statement uses only a sample of records of the table.

You can define collection types in a procedure, function, or package.

You can pass collection variables as parameters, to move data between client-side applications and stored subprograms.

What I've done before is perform a bulk insert from the data into a temp table, and then use a command or stored procedure to update the data relating the temp table with the destination table.

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