Oracle cursor for updating every row in same table adult singles dating thurston nebraska

Although the number of physical disk blocks and Current Mode Gets are about the same in each test, the Hash Join method performs multi-block reads, resulting in fewer visits to the disk.

All 8 methods above were benchmarked on the assumption that the target table is arbitrarily large and the subset of rows/blocks to be updated are relatively small.

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 (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.

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.

Here's the function: CREATE OR REPLACE FUNCTION test_parallel_update ( test_cur IN SYS_REFCURSOR ) RETURN test_num_arr PARALLEL_ENABLE (PARTITION test_cur BY ANY) PIPELINED IS PRAGMA AUTONOMOUS_TRANSACTION; test_rec TEST%ROWTYPE; 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; cnt INTEGER := 0; BEGIN LOOP FETCH test_cur BULK COLLECT INTO pk_tab, fk_tab, fill_tab LIMIT 1000; EXIT WHEN pk_tab. This is a feature of Oracle's parallel-enabled functions; they will apportion the rows of a single Ref Cursor amongst many parallel slaves, with each slave running over a different subset of the input data set. Parallel PL/SQL 28.2 27.2 6.3 Let's see how a Foreign Key constraint affects things. Although not shown here, this effect is magnified with each additional bitmap index.

Update-wise, it looks as though it should perform the same as the Explicit Cursor Loop.

The difference is that the Implicit Cursor internally performs bulk fetches, which should be faster than the Explicit Cursor because of the reduced context switches. I generally recommend against it for high-volume updates because the SET sub-query is nested, meaning it is performed once for each row updated. Using BULK COLLECT and FORALL statements is the new de-facto standard for PL/SQL programmers concerned about performance because it reduces context switching overheads between the PL/SQL and SQL engines.

If the proportion of updated blocks increases, then the average cost of finding those rows decreases; the exercise becomes one of tuning the data access rather than tuning the update.

Why is the Parallel PL/SQL (Method 8) approach much faster than the Parallel DML MERGE (Method 7)? Below we see the trace from the Parallel Coordinator session of Method 7: MERGE /* first_rows */ INTO test USING test5 new ON (= new.pk) WHEN MATCHED THEN UPDATE SET fk = , fill = call count cpu elapsed disk query current rows ------- ------ -------- ---------- ---------- ---------- ---------- ---------- Parse 1 0.02 0.02 0 4 1 0 Execute 1 1.85 57.91 1 7 2 100000 Fetch 0 0.00 0.00 0 0 0 0 ------- ------ -------- ---------- ---------- ---------- ---------- ---------- total 2 1.87 57.94 1 11 3 100000 Misses in library cache during parse: 1 Optimizer mode: FIRST_ROWS Parsing user id: 140 Rows Row Source Operation ------- --------------------------------------------------- 128 PX COORDINATOR (cr=7 pr=1 pw=0 time=57912088 us) 0 PX SEND QC (RANDOM) : TQ10002 (cr=0 pr=0 pw=0 time=0 us) 0 INDEX MAINTENANCE TEST (cr=0 pr=0 pw=0 time=0 us)(object id 0) 0 PX RECEIVE (cr=0 pr=0 pw=0 time=0 us) 0 PX SEND RANGE : TQ10001 (cr=0 pr=0 pw=0 time=0 us) 0 MERGE TEST (cr=0 pr=0 pw=0 time=0 us) 0 PX RECEIVE (cr=0 pr=0 pw=0 time=0 us) 0 PX SEND HYBRID (ROWID PKEY) : TQ10000 (cr=0 pr=0 pw=0 time=0 us) 0 VIEW (cr=0 pr=0 pw=0 time=0 us) 0 NESTED LOOPS (cr=0 pr=0 pw=0 time=0 us) 0 PX BLOCK ITERATOR (cr=0 pr=0 pw=0 time=0 us) 0 TABLE ACCESS FULL TEST5 (cr=0 pr=0 pw=0 time=0 us) 0 TABLE ACCESS BY INDEX ROWID TEST (cr=0 pr=0 pw=0 time=0 us) 0 INDEX UNIQUE SCAN TEST_PK (cr=0 pr=0 pw=0 time=0 us)(object id 141439) Elapsed times include waiting on following events: Event waited on Times Max.

Leave a Reply