london chat online dating - Oracle sql updating multiple rows

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.

oracle sql updating multiple rows-64

Wait Total Waited ---------------------------------------- Waited ---------- ------------ cursor: pin S wait on X 3 0.02 0.06 PX Deq: Execution Msg 16 1.96 10.94 PX Deq: Msg Fragment 2 0.00 0.00 latch: parallel query alloc buffer 7 5.89 7.52 db file sequential read 825 0.10 12.00 read by other session 17 0.06 0.18 log buffer space 1 0.03 0.03 PX Deq Credit: send blkd 1 0.02 0.02 PX Deq: Table Q Normal 28 0.19 0.35 latch: cache buffers chains 1 0.01 0.01 db file parallel read 1 0.11 0.11 From this, we can see that of the 30.3 seconds the Co-ordinator spent waiting for the parallel threads, this one spent 7.52 waiting for shared resources (latches) held by other parallel threads, and just 12 seconds reading blocks from disk.

For comparison, here is the trace of the Co-ordinator session of a Parallel PL/SQL run: SELECT sum(column_value) FROM TABLE(test_parallel_update( CURSOR(SELECT * FROM TEST7) )) call count cpu elapsed disk query current rows ------- ------ -------- ---------- ---------- ---------- ---------- ---------- Parse 1 0.05 0.13 7 87 1 0 Execute 1 0.20 12.47 0 3 0 0 Fetch 2 0.21 20.13 0 0 0 1 ------- ------ -------- ---------- ---------- ---------- ---------- ---------- total 4 0.46 32.74 7 90 1 1 Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 140 Rows Row Source Operation ------- --------------------------------------------------- 1 SORT AGGREGATE (cr=3 pr=0 pw=0 time=32609316 us) 128 PX COORDINATOR (cr=3 pr=0 pw=0 time=252152371 us) 0 PX SEND QC (RANDOM) : TQ10000 (cr=0 pr=0 pw=0 time=0 us) 0 SORT AGGREGATE (cr=0 pr=0 pw=0 time=0 us) 0 VIEW (cr=0 pr=0 pw=0 time=0 us) 0 COLLECTION ITERATOR PICKLER FETCH TEST_PARALLEL_UPDATE (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 TEST7 (cr=0 pr=0 pw=0 time=0 us) Elapsed times include waiting on following events: Event waited on Times Max.

Wait Total Waited ---------------------------------------- Waited ---------- ------------ db file scattered read 37 0.20 0.72 db file sequential read 94936 0.39 781.52 buffer exterminate 1 0.97 0.97 SQL*Net message to client 1 0.00 0.00 SQL*Net message from client 1 0.05 0.05 ********************************************************************************MERGE INTO test USING test2 new ON (= new.pk) WHEN MATCHED THEN UPDATE SET fk = , fill = --------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes |Temp Spc| Cost (%CPU)| --------------------------------------------------------------------------- | 0 | MERGE STATEMENT | | 95331 | 7261K| | 46318 (3)| | 1 | MERGE | TEST | | | | | | 2 | VIEW | | | | | | | 3 | HASH JOIN | | 95331 | 8937K| 5592K| 46318 (3)| | 4 | TABLE ACCESS FULL| TEST2 | 95331 | 4468K| | 170 (3)| | 5 | TABLE ACCESS FULL| TEST | 10M| 458M| | 16949 (4)| --------------------------------------------------------------------------- call count cpu elapsed disk query current rows ------- ------ -------- ---------- ---------- ---------- ---------- ---------- Parse 1 0.03 0.40 1 4 1 0 Execute 1 54.50 123.48 94547 82411 533095 100000 Fetch 0 0.00 0.00 0 0 0 0 ------- ------ -------- ---------- ---------- ---------- ---------- ---------- total 2 54.53 123.88 94548 82415 533096 100000 Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 140 Rows Row Source Operation ------- --------------------------------------------------- 1 MERGE TEST (cr=82411 pr=94547 pw=0 time=123480418 us) 100000 VIEW (cr=75424 pr=74949 pw=0 time=48081374 us) 100000 HASH JOIN (cr=75424 pr=74949 pw=0 time=47981370 us) 100000 TABLE ACCESS FULL TEST2 (cr=750 pr=335 pw=0 time=1207771 us) 9999999 TABLE ACCESS FULL TEST (cr=74674 pr=74614 pw=0 time=10033917 us) Elapsed times include waiting on following events: Event waited on Times Max.

Wait Total Waited ---------------------------------------- Waited ---------- ------------ db file sequential read 19606 0.37 41.24 db file scattered read 4720 0.52 34.20 SQL*Net message to client 1 0.00 0.00 SQL*Net message from client 1 0.03 0.03 That's a pretty significant difference: the same method (MERGE) is 6-7 times faster when performed as a Hash Join.

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.

Here is the statement that calls the Parallel Enabled Table Function: Note that we are using a SELECT statement to call a function that performs an UPDATE. You need to make the function an AUTONOMOUS TRANSACTION to stop it from throwing an error. For this round, I have created a parent table and a Foreign Key on the FK column. Given that most bitmap-indexed tables would have several such indexes (as bitmap indexes are designed to be of most use in combination), this shows that PL/SQL is virtually non-viable as a means of updating a large number of rows.

But just bear with me, it is the closest PL/SQL equivalent I can make to a third-party ETL Tool such as Data Stage with native parallelism. For brevity, this time we'll just flush the buffer cache and run about 5 minutes worth of indexed reads to cycle the disk cache. Although we are updating only 1% of the rows in the table, those rows are almost perfectly distributed throughout the table.

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.

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