KEDU - reduce the waiting time

Hello Dear all,
To ensure that all data remains consistent, the system excludes any data posted in the last 30 minutes before execution (so-called "safety delta"). Consequently, the time of execution shown in the log is always half an hour before the actual time of execution.
In KEDU click Shift + F1
Users ask me to reduce this time, is it possible ? and how ?
Thanks
Edited by: Tarek AYACHI on Jul 21, 2010 2:44 PM

I order it by the org_lineage to get the first person. So it is a result problem? The order by doesn't give you the first person, it gives you a sorted result set (of which there may be zero, one, or thousands).
If you only want one row from that, then you're spending a lot of time tuning the wrong query.
How do you know which ORG_LINEAGE row you want?
Maybe it would help if you posted some sample data.

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Here is the SQL, three-table join and joining conditions are:
ms_ets_cntrl.ims_cntrt_oid=ims_alctn.ims_alctn_oid
ims_alctn.ims_trde_oid=ims_trde.ims_trde_oid
SELECT 'MCH' Type, ims_ets_cntrl.STTS tp_stts, count(*) Count FROM ims_ets_cntrl where ims_ets_cntrl.ims_cntrt_oid in
(select ims_alctn.ims_alctn_oid FROM ims_alctn, ( select ims_trde.ims_trde_oid from ims_trde
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AND (IMS_TRDE.GRS_TRX_TYPE IN ('INJECTION','WITHDRAWAL','PAYMENT') OR IMS_TRDE.SSC_INVST_TYPE = 'FC' AND 1=1 and IMS_TRDE.SERVICE_TYPE='FS' )) TRDE
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SQL> show parameter optimizer
NAME                                 TYPE        VALUE
optimizer_dynamic_sampling           integer     1
optimizer_features_enable            string      9.2.0
optimizer_index_caching              integer     0
optimizer_index_cost_adj             integer     100
optimizer_max_permutations           integer     2000
optimizer_mode                       string      CHOOSE
SQL>select pname, pval1, pval2 from sys.aux_stats$ where sname='SYSSTATS_INFO';
DSTART          11-16-2009 10:23
DSTOP          11-16-2009 10:23
FLAGS     1
STATUS          NOWORKLOADHere is autotrace output:
Execution Plan
   0      SELECT STATEMENT Optimizer=CHOOSE
   1    0   SORT (GROUP BY)
   2    1     VIEW
   3    2       SORT (UNIQUE)
   4    3         TABLE ACCESS (BY INDEX ROWID) OF 'IMS_ETS_CNTRL'
   5    4           NESTED LOOPS
   6    5             NESTED LOOPS
   7    6               TABLE ACCESS (BY INDEX ROWID) OF 'IMS_TRDE'
   8    7                 INDEX (RANGE SCAN) OF 'IMS_TRDE_INDX4' (NON- UNIQUE)
   9    6               TABLE ACCESS (BY INDEX ROWID) OF 'IMS_ALCTN'
10    9                 INDEX (RANGE SCAN) OF 'IMS_ALCTN_INDX1' (NON -UNIQUE)
11    5             INDEX (RANGE SCAN) OF 'IMS_ETS_CNTRL_INDX1' (NON -UNIQUE)
Statistics
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          0 db block gets
     244608 consistent gets
      58856 physical reads
          0 redo size
        497 bytes sent via SQL*Net to client
        499 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          2 sorts (memory)
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call     count       cpu    elapsed       disk      query    current        rows
Parse        1      0.00       0.00          0          0          0           0
Execute      1      0.00       0.00          0          0          0           0
Fetch        2      4.85     129.72      53863     244608          0           1
total        4      4.85     129.72      53863     244608          0           1
Misses in library cache during parse: 1
Optimizer goal: CHOOSE
Parsing user id: 63
Rows     Row Source Operation
      1 SORT GROUP BY
12972   VIEW
12972    SORT UNIQUE
12972     TABLE ACCESS BY INDEX ROWID IMS_ETS_CNTRL
46236      NESTED LOOPS
19134       NESTED LOOPS
19744        TABLE ACCESS BY INDEX ROWID IMS_TRDE
176922         INDEX RANGE SCAN IMS_TRDE_INDX4 (object id 34099)
19134        TABLE ACCESS BY INDEX ROWID IMS_ALCTN
19134         INDEX RANGE SCAN IMS_ALCTN_INDX1 (object id 34094)
27101       INDEX RANGE SCAN IMS_ETS_CNTRL_INDX1 (object id 34101)
********************************************************************************Explain plan output:
PLAN_TABLE_OUTPUT
| Id | Operation                         | Name                | Rows | Bytes | Cost |
|   0 | SELECT STATEMENT                  |                      |       |       |       |
|   1 | SORT GROUP BY                    |                      |       |       |       |
|   2 |   VIEW                            |                      |       |       |       |
|   3 |    SORT UNIQUE                    |                      |       |       |       |
|* 4 |     TABLE ACCESS BY INDEX ROWID   | IMS_ETS_CNTRL        |       |       |       |
|   5 |      NESTED LOOPS                 |                      |       |       |       |
|   6 |       NESTED LOOPS                |                      |       |       |       |
|* 7 |        TABLE ACCESS BY INDEX ROWID| IMS_TRDE             |       |       |       |
|* 8 |         INDEX RANGE SCAN          | IMS_TRDE_INDX4       |       |       |       |
|   9 |        TABLE ACCESS BY INDEX ROWID| IMS_ALCTN            |       |       |       |
|* 10 |         INDEX RANGE SCAN          | IMS_ALCTN_INDX1      |       |       |       |
|* 11 |       INDEX RANGE SCAN            | IMS_ETS_CNTRL_INDX1 |       |       |       |
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10 - access("IMS_ALCTN"."IMS_TRDE_OID"="IMS_TRDE"."IMS_TRDE_OID")
11 - access("IMS_ETS_CNTRL"."IMS_CNTRT_OID"="IMS_ALCTN"."IMS_ALCTN_OID")
Note: rule based optimizationCould you please help tune this sql?
How can I reduce the elapsed time? How can I reduce query read?
If there is any other info that you need, please let me know!
thank you very much!

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2 1 FILTER
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For all entries
Nested selects
Select using JOINS
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Use the aggregated functions
Select with view
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Select Into table
Select with selection list
Key access to multiple lines
Copying internal tables
Modifying a set of lines
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Large amount of data
Mixing processing and reading of data
Fast internal reprocessing of data
Fast
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Nested selects
The plus:
Small amount of data
Mixing processing and reading of data
Easy to code - and understand
The minus:
Large amount of data
when mixed processing isnt needed
Performance killer no. 1
Select using JOINS
The plus
Very large amount of data
Similar to Nested selects - when the accesses are planned by the programmer
In some cases the fastest
Not so memory critical
The minus
Very difficult to program/understand
Mixing processing and reading of data not possible
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SELECT * FROM SBOOK.
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ENDSELECT.
SELECT * FROM SBOOK
WHERE CARRID = 'LH' AND
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Use the aggregated functions
C4A = '000'.
SELECT * FROM T100
WHERE SPRSL = 'D' AND
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Select with view
SELECT * FROM DD01L
WHERE DOMNAME LIKE 'CHAR%'
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SELECT SINGLE * FROM DD01T
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ENDSELECT.
SELECT * FROM DD01V
WHERE DOMNAME LIKE 'CHAR%'
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Select with index support
SELECT * FROM T100
WHERE     ARBGB = '00'
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ENDSELECT.
SELECT * FROM T002.
SELECT * FROM T100
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Select Into table
REFRESH X006.
SELECT * FROM T006 INTO X006.
APPEND X006.
ENDSELECT
SELECT * FROM T006 INTO TABLE X006.
Select with selection list
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SELECT DOMNAME FROM DD01L
INTO DD01L-DOMNAME
WHERE DOMNAME LIKE 'CHAR%'
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Key access to multiple lines
LOOP AT TAB.
CHECK TAB-K = KVAL.
ENDLOOP.
LOOP AT TAB WHERE K = KVAL.
ENDLOOP.
Copying internal tables
REFRESH TAB_DEST.
LOOP AT TAB_SRC INTO TAB_DEST.
APPEND TAB_DEST.
ENDLOOP.
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IF TAB-FLAG IS INITIAL.
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ENDIF.
MODIFY TAB.
ENDLOOP.
TAB-FLAG = 'X'.
MODIFY TAB TRANSPORTING FLAG
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Deleting a sequence of lines
DO 101 TIMES.
DELETE TAB_DEST INDEX 450.
ENDDO.
DELETE TAB_DEST FROM 450 TO 550.
Linear search vs. binary
READ TABLE TAB WITH KEY K = 'X'.
READ TABLE TAB WITH KEY K = 'X' BINARY SEARCH.
Comparison of internal tables
DESCRIBE TABLE: TAB1 LINES L1,
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IF L1 <> L2.
TAB_DIFFERENT = 'X'.
ELSE.
TAB_DIFFERENT = SPACE.
LOOP AT TAB1.
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ENDIF.
IF TAB_DIFFERENT = SPACE.
ENDIF.
IF TAB1[] = TAB2[].
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Modify selected components
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TAB-DATE = SY-DATUM.
MODIFY TAB.
ENDLOOP.
WA-DATE = SY-DATUM.
LOOP AT TAB.
MODIFY TAB FROM WA TRANSPORTING DATE.
ENDLOOP.
Appending two internal tables
LOOP AT TAB_SRC.
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ENDLOOP
APPEND LINES OF TAB_SRC TO TAB_DEST.
Deleting a set of lines
LOOP AT TAB_DEST WHERE K = KVAL.
DELETE TAB_DEST.
ENDLOOP
DELETE TAB_DEST WHERE K = KVAL.
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SQL Trace (ST05)
Tips and Tricks tool
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Select DISTINCT
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Any WHERE clasuse that contains a subquery or IS NULL expression
JOIN s
A SELECT... FOR UPDATE
If you wnat to explicitly bypass the bufer, use the BYPASS BUFFER addition to the SELECR clause.
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The ORDER BY clause is executed on the database server while the ABAP SORT statement is executed on the application server. The datbase server will usually be the bottleneck, so sometimes it is better to move thje sort from the datsbase server to the application server.
If you are not sorting by the primary key ( E.g. using the ORDER BY PRIMARY key statement) but are sorting by another key, it could be better to use the ABAP SORT stament to sort the data in an internal table. Note however that for very large result sets it might not be a feasible solution and you would want to let the datbase server sort it.
Avoid ther SELECT DISTINCT Statement
As with the ORDER BY clause it could be better to avoid using SELECT DISTINCT, if some of the fields are not part of an index. Instead use ABAP SORT + DELETE ADJACENT DUPLICATES on an internal table, to delete duplciate rows.
Good Luck and thanks
AK

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KEDU - reduce the waiting time

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