Oracle sql updating multiple tables

I include it here because it allows us to compare the cost of context-switches to the cost of updates.DECLARE CURSOR c1 IS SELECT * FROM test6; rec_cur c1%rowtype; BEGIN OPEN c1; LOOP FETCH c1 INTO rec_cur; EXIT WHEN c1%notfound; UPDATE test SET fk = rec_, fill = rec_WHERE pk =; END LOOP; CLOSE C1; END; / This is the simplest PL/SQL method and very common in hand-coded PL/SQL applications.Update-wise, it looks as though it should perform the same as the Explicit Cursor Loop.

To support this method, I needed to create an index on TEST8. The biggest drawback to this method is readability. LAST UPDATE test SET fk = fk_tab(i) , fill = fill_tab(i) WHERE pk = pk_tab(i); END LOOP; CLOSE rec_cur; END; / The modern equivalent of the Updateable Join View. Parallel PL/SQL ORA-00060: deadlock detected Well, if further proof was needed that Bitmap indexes are inappropriate for tables that are maintained by multiple concurrent sessions, surely this is it.

Since Oracle does not yet provide support for record collections in FORALL, we need to use scalar collections, making for long declarations, INTO clauses, and SET clauses. Gaining in popularity due to its combination of brevity and performance, it is primarily used to INSERT and UPDATE in a single statement. Note that I have included a FIRST_ROWS hint to force an indexed nested loops plan. The Deadlock error raised by Method 8 occurred because bitmap indexes are locked at the block-level, not the row level.

DECLARE CURSOR rec_cur IS SELECT * FROM test4; TYPE num_tab_t IS TABLE OF NUMBER(38); TYPE vc2_tab_t IS TABLE OF VARCHAR2(4000); pk_tab NUM_TAB_T; fk_tab NUM_TAB_T; fill_tab VC2_TAB_T; BEGIN OPEN rec_cur; LOOP FETCH rec_cur BULK COLLECT INTO pk_tab, fk_tab, fill_tab LIMIT 1000; EXIT WHEN pk_tab. This is to keep the playing field level when comparing to the other methods, which also perform primary key lookups on the target table. With hundreds of rows represented by each block in the index, the chances of two sessions attempting to lock the same block are quite high.

What I love about writing SQL Tuning articles is that I very rarely end up publishing the findings I set out to achieve. We have a table containing years worth of data, most of which is static; we are updating selected rows that were recently inserted and are still volatile. For the purposes of the test, we will assume that the target table of the update is arbitrarily large, and we want to avoid things like full-scans and index rebuilds.

With this one, I set out to demonstrate the advantages of PARALLEL DML, didn't find what I thought I would, and ended up testing 8 different techniques to find out how they differed. The methods covered include both PL/SQL and SQL approaches.

), how I might cluster rows together that are subject to updates, and what I might do if I just get too many updates to handle. The fastest way to update every row in the table is to rebuild the table from scratch. Case 2 is common in Data Warehouses and overnight batch jobs.

I worry about how ETL tools apply updates (did you know Data Stage applys updates singly, but batches inserts in arrays? The two most common forms of Bulk Updates are: Case 1 is uninteresting.

I spend an inordinate proportion of design time of an ETL system worrying about the relative proportion of rows inserted vs updated.

I want to test on a level playing field and remove special factors that unfairly favour one method, so there are some rules: TEST{n} (Update Source) - 100K rows TEST (Update target) - 10M rows Name Type Name Type ------------------------------ ------------ ------------------------------ ------------ PK NUMBER PK NUMBER FK NUMBER FK NUMBER FILL VARCHAR2(40) FILL VARCHAR2(40) Not many people code this way, but there are some Pro*C programmers out there who are used to Explicit Cursor Loops (OPEN, FETCH and CLOSE commands) and translate these techniques directly to PL/SQL.

The UPDATE portion of the code works in an identical fashion to the Implicit Cursor Loop, so this is not really a separate "UPDATE" method as such.

The interesting thing about this method is that it performs a context-switch between PL/SQL and SQL for every FETCH; this is less efficient.

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