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Posted by / 11-Aug-2015 15:24

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

A Hash join may or may not be faster, that's not the point - I could increase the size of the target TEST table to 500M rows and Hash would be slower for sure. The very clear lesson here: don't update bitmap indexed tables in parallel sessions; the only safe parallel method is PARALLEL DML.

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.

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.

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), 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.

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