Query performance decreases dramatically after adding 0AGE characteristic
Hi gurus,
I've added 0AGE as a free characteristic to a query based on 0PAPA_C02 cube and the query performance falls down dramatically.
In transaction RSRT I have compared statistics for two identical queries, one with 0AGE, and one without it.
Total DBTRANS changed from 1.528 to 284.342
Total DBSEL didn't change.
"OLAP: Data Selection" changed from 0,207267 to 232,879858
There is also a new line: OLAP: USER_EXIT with long duration: 289,386668 and counter: 6.840.863
And I am not using any user exit variable!!!! or anything...
What may be wrong and how can I fix that?
Regards,
Dorota
Found the answer.
There is a BAPI for 0PAPA_C01 InfoCube which makes 0AGE a virtual characteristic.
It needs to be deactivated.
The BAPI name is RS_BCT_PA.
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Query performance decreases dramatically after replacing equal clause
I have a Select statement that performs well as long as I join the project code to a fixed value in the WHERE clause.
But when this fixed value is replaced by a sub SELECT (which in fact retrieves that same fixed value) the result of the query takes 5 minutes longer.
It's Oracle 8i database.
It's not clear to me why Oracle follows a complete other execution plan and also introduces a lot of FULL table scans with such a minor change
Select statement and explain plan with fixed value in WHERE
SELECT PVN.PJT_CODE PJT_CODE
, L_PJT.DESCRIPTION PJT_DESCRIPTION
, PVN.CODE VERSION
, PVN.DESCRIPTION VERSION_DESCRIPTION
-- , NVL(L_PJT.EXRATE_TENDER, 1) EXRATE_TENDER
, KBA.BQI_CODE BOQ_ITEM
, KBA.BQI_DESCRIPTION BOQ_ITEM_DESCRIPTION
, KBA.BQI_QUANTITY BOQ_ITEM_PAID_QUANTITY
, KBA.BQI_UNIT BOQ_ITEM_UNIT
-- , KBA.PVN_CODE PVN_CODE1
-- , KBA.PJT_CODE PJT_CODE2
, KGW.ACT_CODE ACT_CODE
, KGW.DESCRIPTION ACT_DESCRIPTION
, ROUND(KGW.EXECUTED) ACT_EXECUTED_QUANTITY
, KGW.UNIT_EXEC ACT_EXECUTED_UNIT
, ROUND(KGW.PAID) ACT_PAID_QUANTITY
, NVL(KGW.UNIT_PAID, KGW.UNIT_EXEC) ACT_PAID_UNIT
, KGW.HOURS_WEEK ACT_HOURS_WEEK
, KGW.PROD_HOUR ACT_PROD_HOUR
, KGW.HOURS_WEEK * KGW.PROD_HOUR ACT_PROD_WEEK
, NVL(KGW.WEEKS, 1) ACT_TOTAL_WEEKS -- WKUI: NVL, 1 toepassen.
, KGW.MY_CODE ACT_MY_CODE
, NVL(L_EQT.DESCRIPTION, WCS.DESCRIPTION) WCS_DESCRIPTION
, IAE.WCA_PJT_CODE WCA_PJT_CODE
, IAE.WCA_CODE WCA_CODE
, IAE.QUANTITY QUANTITY
, IAE.STANDBY_IDLE
, WCS.CODE WCS_CODE
, WCS.SQT_CODE WCS_SQT_CODE
, WCA.WCA_TYPE
, Kcs_Bqm_Dml.calc_wcs_costs
( iae.wca_pjt_code
, wcs.code
, kgw.hours_week
, iae.standby_idle
, iae.quantity
, wcs.sqt_code
, Kcs_Bqm_Dml.calc_working_weeks ( kgw.my_code
, kgw.pjt_code
, kgw.act_code
, kgw.pvn_code
FROM KCS_PROJECT_VERSIONS PVN
, PRR_PROJECTS L_PJT
, KCS_BOQ_ACT_VW KBA
, KCS_GAY_WCA_VW KGW
, KCS_INTS_WCA_WCS IAE
, KCS_WEEKLY_COST_ACTIVITIES WCA
, KCS_WEEKLY_COST_SPECIFICATIONS WCS
, KCS_EQUIPMENT L_EQT
WHERE PVN.PJT_CODE = L_PJT.CODE
AND L_PJT.CODE IN ( '04.748' )
AND PVN.CODE = 'A'
AND KBA.PJT_CODE = PVN.PJT_CODE
AND KBA.PVN_CODE = PVN.CODE
AND KGW.PJT_CODE = PVN.PJT_CODE
AND KGW.PVN_CODE = PVN.CODE
AND KGW.BQI_CODE = KBA.BQI_CODE
AND KGW.ACT_CODE = WCA.CODE
AND KGW.PJT_CODE = WCA.PJT_CODE
AND IAE.WCS_CODE = WCS.CODE
AND IAE.WCS_PJT_CODE = WCS.PJT_CODE
AND WCS.EQT_CODE = L_EQT.CODE (+)
AND WCA.PJT_CODE = IAE.WCS_PJT_CODE
AND WCA.CODE = IAE.WCA_CODE
AND WCA.WCA_TYPE = 'PAY'
ORDER BY PVN.PJT_CODE
, PVN.CODE
, KBA.BQI_CODE
, KGW.ACT_CODE
, wcs.codeFast explain plan: OKAY
Operation Object Name Rows Bytes Cost Object Node In/Out PStart PStop
SELECT STATEMENT Optimizer Mode=CHOOSE 1 270
SORT ORDER BY 1 328 270
NESTED LOOPS OUTER 1 328 269
NESTED LOOPS 1 313 268
HASH JOIN 1 259 116
HASH JOIN 4 528 89
NESTED LOOPS 28 3 K 78
NESTED LOOPS 23 2 K 9
NESTED LOOPS 1 58 3
TABLE ACCESS BY INDEX ROWID PRR.PRR_PROJECTS 1 26 2
INDEX UNIQUE SCAN PRR.PRR_PJT_PK 1 1
TABLE ACCESS BY INDEX ROWID KCS.KCS_PROJECT_VERSIONS 1 32 1
INDEX UNIQUE SCAN KCS.KCS_PVN_PK 1
TABLE ACCESS BY INDEX ROWID KCS.KCS_WEEKLY_COST_SPECIFICATIONS 23 897 6
INDEX RANGE SCAN KCS.KCS_WCS_PJT_FK 23 2
TABLE ACCESS BY INDEX ROWID KCS.KCS_INTS_WCA_WCS 124 2 K 3
INDEX RANGE SCAN KCS.KCS_IAE_WCS_FK 124 2
TABLE ACCESS BY INDEX ROWID KCS.KCS_WEEKLY_COST_ACTIVITIES 18 234 10
INDEX RANGE SCAN KCS.KCS_WCA_PJT_FK 18 3
VIEW KCS.KCS_GAY_WCA_VW 3 381 27
SORT UNIQUE 3 229 27
UNION-ALL
NESTED LOOPS 1 75 9
NESTED LOOPS 1 72 9
NESTED LOOPS 1 58 7
TABLE ACCESS BY INDEX ROWID KCS.KCS_GENERAL_ACTIVITIES 1 45 4
INDEX RANGE SCAN KCS.KCS_GAY_PK 1 3
TABLE ACCESS BY INDEX ROWID KCS.KCS_GENERAL_SPECIFICATIONS 4 52 3
INDEX RANGE SCAN KCS.KCS_GSN_GAY_FK 4 2
INDEX RANGE SCAN KCS.KCS_ISC_GSN_FK 5 70 2
INDEX UNIQUE SCAN KCS.KCS_SCG_PK 20 60
NESTED LOOPS 1 66 5
NESTED LOOPS 1 63 5
TABLE ACCESS BY INDEX ROWID KCS.KCS_INTS_GAY_SCT 1 18 3
INDEX RANGE SCAN KCS.KCS_IAC_GAY_FK 1 2
TABLE ACCESS BY INDEX ROWID KCS.KCS_GENERAL_ACTIVITIES 1 45 2
INDEX UNIQUE SCAN KCS.KCS_GAY_PK 1 1
INDEX UNIQUE SCAN KCS.KCS_SCG_PK 20 60
NESTED LOOPS 1 88 7
NESTED LOOPS 1 84 6
TABLE ACCESS BY INDEX ROWID KCS.KCS_INTS_WCA_PVN 1 22 4
INDEX RANGE SCAN KCS.KCS_IAV_PVN_FK 1 3
TABLE ACCESS BY INDEX ROWID KCS.KCS_WEEKLY_COST_ACTIVITIES 71 K 4 M 2
INDEX UNIQUE SCAN KCS.KCS_WCA_PK 71 K 1
TABLE ACCESS BY INDEX ROWID KCS.KCS_SYS_COST_GROUP 20 80 1
INDEX UNIQUE SCAN KCS.KCS_SCG_PK 20
VIEW KCS.KCS_BOQ_ACT_VW 2 108
SORT UNIQUE 2 102 153
UNION-ALL
NESTED LOOPS 1 51 113
TABLE ACCESS BY INDEX ROWID KCS.KCS_BOQ_ITEMS 27 1 K 5
INDEX RANGE SCAN KCS.KCS_BQI_PJT_FK 27 3
TABLE ACCESS BY INDEX ROWID KCS.KCS_GENERAL_ACTIVITIES 1 12 4
INDEX RANGE SCAN KCS.KCS_GAY_BQI_FK 1 2
NESTED LOOPS 1 51 36
TABLE ACCESS BY INDEX ROWID KCS.KCS_INTS_WCA_PVN 1 12 34
INDEX RANGE SCAN KCS.KCS_IAV_BQI_FK 1 3
TABLE ACCESS BY INDEX ROWID KCS.KCS_BOQ_ITEMS 27 1 K 2
INDEX UNIQUE SCAN KCS.KCS_BQI_PK 27 1
TABLE ACCESS BY INDEX ROWID KCS.KCS_EQUIPMENT 1 K 17 K 1
INDEX UNIQUE SCAN KCS.KCS_EQT_PK 1 K Select statement and explain plan with subselect in WHERE
SELECT PVN.PJT_CODE PJT_CODE
, L_PJT.DESCRIPTION PJT_DESCRIPTION
, PVN.CODE VERSION
, PVN.DESCRIPTION VERSION_DESCRIPTION
-- , NVL(L_PJT.EXRATE_TENDER, 1) EXRATE_TENDER
, KBA.BQI_CODE BOQ_ITEM
, KBA.BQI_DESCRIPTION BOQ_ITEM_DESCRIPTION
, KBA.BQI_QUANTITY BOQ_ITEM_PAID_QUANTITY
, KBA.BQI_UNIT BOQ_ITEM_UNIT
-- , KBA.PVN_CODE PVN_CODE1
-- , KBA.PJT_CODE PJT_CODE2
, KGW.ACT_CODE ACT_CODE
, KGW.DESCRIPTION ACT_DESCRIPTION
, ROUND(KGW.EXECUTED) ACT_EXECUTED_QUANTITY
, KGW.UNIT_EXEC ACT_EXECUTED_UNIT
, ROUND(KGW.PAID) ACT_PAID_QUANTITY
, NVL(KGW.UNIT_PAID, KGW.UNIT_EXEC) ACT_PAID_UNIT
, KGW.HOURS_WEEK ACT_HOURS_WEEK
, KGW.PROD_HOUR ACT_PROD_HOUR
, KGW.HOURS_WEEK * KGW.PROD_HOUR ACT_PROD_WEEK
, NVL(KGW.WEEKS, 1) ACT_TOTAL_WEEKS -- WKUI: NVL, 1 toepassen.
, KGW.MY_CODE ACT_MY_CODE
, NVL(L_EQT.DESCRIPTION, WCS.DESCRIPTION) WCS_DESCRIPTION
, IAE.WCA_PJT_CODE WCA_PJT_CODE
, IAE.WCA_CODE WCA_CODE
, IAE.QUANTITY QUANTITY
, IAE.STANDBY_IDLE
, WCS.CODE WCS_CODE
, WCS.SQT_CODE WCS_SQT_CODE
, WCA.WCA_TYPE
, Kcs_Bqm_Dml.calc_wcs_costs
( iae.wca_pjt_code
, wcs.code
, kgw.hours_week
, iae.standby_idle
, iae.quantity
, wcs.sqt_code
, Kcs_Bqm_Dml.calc_working_weeks ( kgw.my_code
, kgw.pjt_code
, kgw.act_code
, kgw.pvn_code
FROM KCS_PROJECT_VERSIONS PVN
, PRR_PROJECTS L_PJT
, KCS_BOQ_ACT_VW KBA
, KCS_GAY_WCA_VW KGW
, KCS_INTS_WCA_WCS IAE
, KCS_WEEKLY_COST_ACTIVITIES WCA
, KCS_WEEKLY_COST_SPECIFICATIONS WCS
, KCS_EQUIPMENT L_EQT
WHERE PVN.PJT_CODE = L_PJT.CODE
AND L_PJT.CODE = (SELECT EMP.PJT_CODE FROM PRR_EMPLOYEES EMP WHERE EMP.INITIALS = USER) /* <-- This is the only difference with previous query, columns are indexed, and result is same as dixed value */
AND PVN.CODE = 'A'
AND KBA.PJT_CODE = PVN.PJT_CODE
AND KBA.PVN_CODE = PVN.CODE
AND KGW.PJT_CODE = PVN.PJT_CODE
AND KGW.PVN_CODE = PVN.CODE
AND KGW.BQI_CODE = KBA.BQI_CODE
AND KGW.ACT_CODE = WCA.CODE
AND KGW.PJT_CODE = WCA.PJT_CODE
AND IAE.WCS_CODE = WCS.CODE
AND IAE.WCS_PJT_CODE = WCS.PJT_CODE
AND WCS.EQT_CODE = L_EQT.CODE (+)
AND WCA.PJT_CODE = IAE.WCS_PJT_CODE
AND WCA.CODE = IAE.WCA_CODE
AND WCA.WCA_TYPE = 'PAY'
ORDER BY PVN.PJT_CODE
, PVN.CODE
, KBA.BQI_CODE
, KGW.ACT_CODE
, wcs.codeExpensive explain plan BAD
Operation Object Name Rows Bytes Cost Object Node In/Out PStart PStop
SELECT STATEMENT Optimizer Mode=CHOOSE 1 5052
SORT ORDER BY 1 328 5052
NESTED LOOPS OUTER 1 328 5051
NESTED LOOPS 1 313 5050
NESTED LOOPS 1 274 5048
NESTED LOOPS 1 252 4677
NESTED LOOPS 1 239 4675
NESTED LOOPS 1 185 3418
NESTED LOOPS 1 58 3
TABLE ACCESS BY INDEX ROWID PRR.PRR_PROJECTS 1 26 2
INDEX UNIQUE SCAN PRR.PRR_PJT_PK 1 1
TABLE ACCESS BY INDEX ROWID PRR.PRR_EMPLOYEES 1 7 1
INDEX UNIQUE SCAN PRR.PRR_EME_PK 2
TABLE ACCESS BY INDEX ROWID KCS.KCS_PROJECT_VERSIONS 41 1 K 1
INDEX UNIQUE SCAN KCS.KCS_PVN_PK 41
VIEW KCS.KCS_GAY_WCA_VW 471 58 K
SORT UNIQUE 471 40 K 3416
UNION-ALL
NESTED LOOPS 1 75 2143
NESTED LOOPS 6 366 2131
HASH JOIN 6 348 2131
TABLE ACCESS FULL KCS.KCS_GENERAL_ACTIVITIES 713 31 K 558
INDEX FAST FULL SCAN KCS.KCS_GSN_PK 5 K 74 K 1546
INDEX UNIQUE SCAN KCS.KCS_SCG_PK 20 60
INDEX RANGE SCAN KCS.KCS_ISC_GSN_FK 6 K 91 K 2
NESTED LOOPS 1 66 298
NESTED LOOPS 1 63 298
TABLE ACCESS FULL KCS.KCS_INTS_GAY_SCT 131 2 K 36
TABLE ACCESS BY INDEX ROWID KCS.KCS_GENERAL_ACTIVITIES 713 31 K 2
INDEX UNIQUE SCAN KCS.KCS_GAY_PK 713 1
INDEX UNIQUE SCAN KCS.KCS_SCG_PK 20 60
HASH JOIN 469 40 K 955
TABLE ACCESS FULL KCS.KCS_SYS_COST_GROUP 20 80 1
HASH JOIN 469 38 K 952
TABLE ACCESS FULL KCS.KCS_INTS_WCA_PVN 420 9 K 169
TABLE ACCESS FULL KCS.KCS_WEEKLY_COST_ACTIVITIES 71 K 4 M 490
VIEW KCS.KCS_BOQ_ACT_VW 1 K 62 K
SORT UNIQUE 1 K 59 K 1258
UNION-ALL
HASH JOIN 748 37 K 847
TABLE ACCESS FULL KCS.KCS_GENERAL_ACTIVITIES 713 8 K 558
TABLE ACCESS FULL KCS.KCS_BOQ_ITEMS 51 K 1 M 107
HASH JOIN 440 21 K 385
TABLE ACCESS FULL KCS.KCS_INTS_WCA_PVN 420 4 K 169
TABLE ACCESS FULL KCS.KCS_BOQ_ITEMS 51 K 1 M 107
TABLE ACCESS BY INDEX ROWID KCS.KCS_WEEKLY_COST_ACTIVITIES 35 K 454 K 2
INDEX UNIQUE SCAN KCS.KCS_WCA_PK 35 K 1
TABLE ACCESS FULL KCS.KCS_INTS_WCA_WCS 270 K 5 M 371
TABLE ACCESS BY INDEX ROWID KCS.KCS_WEEKLY_COST_SPECIFICATIONS 74 K 2 M 2
INDEX UNIQUE SCAN KCS.KCS_WCS_PK 74 K 1
TABLE ACCESS BY INDEX ROWID KCS.KCS_EQUIPMENT 1 K 17 K 1
INDEX UNIQUE SCAN KCS.KCS_EQT_PK 1 K I hope someone can give a clue
Thanks in advance
Auke QuistIn order to get more helpfull messages i used utlxpls.sql to format the plan table:
First the query where I hardcoded the assignment of the project code (this leads to fast result in 841 msecs)
Query with_assigned_project:
SELECT PVN.PJT_CODE PJT_CODE
, L_PJT.DESCRIPTION PJT_DESCRIPTION
, PVN.CODE VERSION
, PVN.DESCRIPTION VERSION_DESCRIPTION
, KBA.BQI_CODE BOQ_ITEM
, KBA.BQI_DESCRIPTION BOQ_ITEM_DESCRIPTION
, KBA.BQI_QUANTITY BOQ_ITEM_PAID_QUANTITY
, KBA.BQI_UNIT BOQ_ITEM_UNIT
, KGW.ACT_CODE ACT_CODE
, KGW.DESCRIPTION ACT_DESCRIPTION
, ROUND(KGW.EXECUTED) ACT_EXECUTED_QUANTITY
, KGW.UNIT_EXEC ACT_EXECUTED_UNIT
, ROUND(KGW.PAID) ACT_PAID_QUANTITY
, NVL(KGW.UNIT_PAID, KGW.UNIT_EXEC) ACT_PAID_UNIT
, KGW.HOURS_WEEK ACT_HOURS_WEEK
, KGW.PROD_HOUR ACT_PROD_HOUR
, KGW.HOURS_WEEK * KGW.PROD_HOUR ACT_PROD_WEEK
, NVL(KGW.WEEKS, 1) ACT_TOTAL_WEEKS -- WKUI: NVL, 1 toepassen.
, KGW.MY_CODE ACT_MY_CODE
FROM KCS_PROJECT_VERSIONS PVN
, KCS_BOQ_ACT_VW KBA
, KCS_GAY_WCA_VW KGW
, PRR_PROJECTS L_PJT
WHERE PVN.PJT_CODE = L_PJT.CODE
AND L_PJT.CODE = '04.748'
AND KBA.PJT_CODE = PVN.PJT_CODE
AND KBA.PVN_CODE = PVN.CODE
AND KGW.PJT_CODE = PVN.PJT_CODE
AND KGW.PVN_CODE = PVN.CODE
AND KGW.BQI_CODE = KBA.BQI_CODE
ORDER BY PVN.PJT_CODE
, PVN.CODE
, KBA.BQI_CODE
, KGW.ACT_CODE;The explain plan is OKAY and looks like:
Plan Table
| Operation | Name | Rows | Bytes| Cost | Pstart| Pstop |
| SELECT STATEMENT | | 1 | 242 | 212 | | |
| SORT ORDER BY | | 1 | 242 | 212 | | |
| NESTED LOOPS | | 1 | 242 | 211 | | |
| HASH JOIN | | 1 | 115 | 94 | | |
| NESTED LOOPS | | 3 | 183 | 5 | | |
| TABLE ACCESS BY INDEX ROWID |PRR_PROJECTS | 1 | 26 | 2 | | |
| INDEX UNIQUE SCAN |PRR_PJT_PK | 1 | | 1 | | |
| TABLE ACCESS BY INDEX ROWID |KCS_PROJECT_VERSIONS | 3 | 105 | 3 | | |
| INDEX RANGE SCAN |KCS_PVN_PJT_FK | 3 | | 1 | | |
| VIEW |KCS_BOQ_ACT_VW | 30 | 1K| 89 | | |
| SORT UNIQUE | | 30 | 1K| 89 | | |
| UNION-ALL | | | | | | |
| NESTED LOOPS | | 15 | 885 | 64 | | |
| TABLE ACCESS BY INDEX ROWID |KCS_BOQ_ITEMS | 15 | 660 | 4 | | |
| INDEX RANGE SCAN |KCS_BQI_PJT_FK | 15 | | 3 | | |
| TABLE ACCESS BY INDEX ROWID |KCS_GENERAL_ACTIVITIES | 50 | 750 | 4 | | |
| INDEX RANGE SCAN |KCS_GAY_BQI_FK | 50 | | 2 | | |
| HASH JOIN | | 15 | 885 | 21 | | |
| TABLE ACCESS BY INDEX ROWID |KCS_BOQ_ITEMS | 15 | 660 | 4 | | |
| INDEX RANGE SCAN |KCS_BQI_PJT_FK | 15 | | 3 | | |
| TABLE ACCESS BY INDEX ROWID |KCS_INTS_WCA_PVN | 31 | 465 | 16 | | |
| INDEX RANGE SCAN |KCS_IAV_BQI_FK | 31 | | 3 | | |
| VIEW |KCS_GAY_WCA_VW | 33 | 4K| | | |
| SORT UNIQUE | | 33 | 3K| 118 | | |
| UNION-ALL | | | | | | |
| NESTED LOOPS | | 1 | 90 | 17 | | |
| NESTED LOOPS | | 1 | 86 | 17 | | |
| HASH JOIN | | 1 | 35 | 15 | | |
| INDEX RANGE SCAN |KCS_GSN_PK | 403 | 6K| 6 | | |
| INDEX RANGE SCAN |KCS_ISC_GSN_FK | 497 | 8K| 6 | | |
| TABLE ACCESS BY INDEX ROWID |KCS_GENERAL_ACTIVITIES | 50 | 2K| 2 | | |
| INDEX UNIQUE SCAN |KCS_GAY_PK | 50 | | 1 | | |
| INDEX UNIQUE SCAN |KCS_SCG_PK | 20 | 80 | | | |
| NESTED LOOPS | | 1 | 78 | 24 | | |
| HASH JOIN | | 1 | 74 | 24 | | |
| TABLE ACCESS BY INDEX ROWID |KCS_INTS_GAY_SCT | 19 | 437 | 4 | | |
| INDEX RANGE SCAN |KCS_IAC_GAY_FK | 19 | | 2 | | |
| TABLE ACCESS BY INDEX ROWID |KCS_GENERAL_ACTIVITIES | 50 | 2K| 19 | | |
| INDEX RANGE SCAN |KCS_GAY_PVN_FK | 50 | | 3 | | |
| INDEX UNIQUE SCAN |KCS_SCG_PK | 20 | 80 | | | |
| HASH JOIN | | 31 | 3K| 71 | | |
| NESTED LOOPS | | 31 | 2K| 69 | | |
| TABLE ACCESS BY INDEX ROWID |KCS_INTS_WCA_PVN | 31 | 837 | 7 | | |
| INDEX RANGE SCAN |KCS_IAV_PVN_FK | 31 | | 3 | | |
| TABLE ACCESS BY INDEX ROWID |KCS_WEEKLY_COST_ACTIVITI | 71K| 4M| 2 | | |
| INDEX UNIQUE SCAN |KCS_WCA_PK | 71K| | 1 | | |
| TABLE ACCESS FULL |KCS_SYS_COST_GROUP | 20 | 120 | 1 | | |
---------------------------------------------------------------------------------------------------------Secondly the query where I derived the the project code (this leads to a slow result in 10.6 minutes)
Query with_assigned_project:
SELECT PVN.PJT_CODE PJT_CODE
, L_PJT.DESCRIPTION PJT_DESCRIPTION
, PVN.CODE VERSION
, PVN.DESCRIPTION VERSION_DESCRIPTION
, KBA.BQI_CODE BOQ_ITEM
, KBA.BQI_DESCRIPTION BOQ_ITEM_DESCRIPTION
, KBA.BQI_QUANTITY BOQ_ITEM_PAID_QUANTITY
, KBA.BQI_UNIT BOQ_ITEM_UNIT
, KGW.ACT_CODE ACT_CODE
, KGW.DESCRIPTION ACT_DESCRIPTION
, ROUND(KGW.EXECUTED) ACT_EXECUTED_QUANTITY
, KGW.UNIT_EXEC ACT_EXECUTED_UNIT
, ROUND(KGW.PAID) ACT_PAID_QUANTITY
, NVL(KGW.UNIT_PAID, KGW.UNIT_EXEC) ACT_PAID_UNIT
, KGW.HOURS_WEEK ACT_HOURS_WEEK
, KGW.PROD_HOUR ACT_PROD_HOUR
, KGW.HOURS_WEEK * KGW.PROD_HOUR ACT_PROD_WEEK
, NVL(KGW.WEEKS, 1) ACT_TOTAL_WEEKS -- WKUI: NVL, 1 toepassen.
, KGW.MY_CODE ACT_MY_CODE
FROM KCS_PROJECT_VERSIONS PVN
, KCS_BOQ_ACT_VW KBA
, KCS_GAY_WCA_VW KGW
, (SELECT * FROM PRR_PROJECTS WHERE CODE = (SELECT EMP.PJT_CODE FROM PRR_EMPLOYEES EMP WHERE EMP.INITIALS = USER)) L_PJT
WHERE PVN.PJT_CODE = L_PJT.CODE
AND KBA.PJT_CODE = PVN.PJT_CODE
AND KBA.PVN_CODE = PVN.CODE
AND KGW.PJT_CODE = PVN.PJT_CODE
AND KGW.PVN_CODE = PVN.CODE
AND KGW.BQI_CODE = KBA.BQI_CODE
ORDER BY PVN.PJT_CODE
, PVN.CODE
, KBA.BQI_CODE
, KGW.ACT_CODE;The explain plan is NOT OKAY for me looks like:
Plan Table
| Operation | Name | Rows | Bytes| Cost | Pstart| Pstop |
| SELECT STATEMENT | | 1 | 242 | 411715 | | |
| SORT ORDER BY | | 1 | 242 | 411715 | | |
| NESTED LOOPS | | 1 | 242 | 411714 | | |
| HASH JOIN | | 1 | 188 | 378640 | | |
| NESTED LOOPS | | 3 | 183 | 4 | | |
| TABLE ACCESS BY INDEX ROWID |PRR_PROJECTS | 1 | 26 | 2 | | |
| INDEX UNIQUE SCAN |PRR_PJT_PK | 1 | | 1 | | |
| TABLE ACCESS BY INDEX ROWID |PRR_EMPLOYEES | 1 | 7 | 1 | | |
| INDEX UNIQUE SCAN |PRR_EME_PK | 2 | | | | |
| TABLE ACCESS BY INDEX ROWID |KCS_PROJECT_VERSIONS | 10K| 345K| 2 | | |
| INDEX RANGE SCAN |KCS_PVN_PJT_FK | 10K| | 1 | | |
| VIEW |KCS_GAY_WCA_VW | 1M| 216M| 375247 | | |
| SORT UNIQUE | | 1M| 154M| 375247 | | |
| UNION-ALL | | | | | | |
| NESTED LOOPS | | 1M| 142M| 76854 | | |
| MERGE JOIN | | 1M| 135M| 76854 | | |
| MERGE JOIN | | 1M| 55M| 64136 | | |
| SORT JOIN | | 1M| 28M| | | |
| INDEX FAST FULL SCAN |KCS_ISC_GSN_FK | 1M| 28M| 13098 | | |
| SORT JOIN | | 1M| 21M| 49492 | | |
| INDEX FAST FULL SCAN |KCS_GSN_PK | 1M| 21M| 1546 | | |
| SORT JOIN | | 164K| 7M| 12718 | | |
| TABLE ACCESS FULL |KCS_GENERAL_ACTIVITIES | 164K| 7M| 558 | | |
| INDEX UNIQUE SCAN |KCS_SCG_PK | 20 | 80 | | | |
| NESTED LOOPS | | 22K| 1M| 12764 | | |
| HASH JOIN | | 22K| 1M| 12764 | | |
| TABLE ACCESS FULL |KCS_INTS_GAY_SCT | 22K| 504K| 36 | | |
| TABLE ACCESS FULL |KCS_GENERAL_ACTIVITIES | 164K| 7M| 558 | | |
| INDEX UNIQUE SCAN |KCS_SCG_PK | 20 | 80 | | | |
| HASH JOIN | | 105K| 10M| 10662 | | |
| TABLE ACCESS FULL |KCS_SYS_COST_GROUP | 20 | 120 | 1 | | |
| MERGE JOIN | | 105K| 9M| 10503 | | |
| SORT JOIN | | 71K| 4M| 6372 | | |
| TABLE ACCESS FULL |KCS_WEEKLY_COST_ACTIVITI | 71K| 4M| 490 | | |
| SORT JOIN | | 105K| 2M| 4131 | | |
| TABLE ACCESS FULL |KCS_INTS_WCA_PVN | 105K| 2M| 169 | | |
| VIEW |KCS_BOQ_ACT_VW | 269K| 13M| 33075 | | |
| SORT UNIQUE | | 269K| 15M| 33075 | | |
| UNION-ALL | | | | | | |
| MERGE JOIN | | 164K| 9M| 7193 | | |
| SORT JOIN | | 51K| 2M| 2461 | | |
| TABLE ACCESS FULL |KCS_BOQ_ITEMS | 51K| 2M| 107 | | |
| SORT JOIN | | 164K| 2M| 4733 | | |
| TABLE ACCESS FULL |KCS_GENERAL_ACTIVITIES | 164K| 2M| 558 | | |
| MERGE JOIN | | 105K| 5M| 4841 | | |
| SORT JOIN | | 51K| 2M| 2461 | | |
| TABLE ACCESS FULL |KCS_BOQ_ITEMS | 51K| 2M| 107 | | |
| SORT JOIN | | 105K| 1M| 2380 | | |
| TABLE ACCESS FULL |KCS_INTS_WCA_PVN | 105K| 1M| 169 | | |
52 rows selected.It's a bit hard to understand for me, because:
(SELECT * FROM PRR_PROJECTS WHERE CODE = (SELECT EMP.PJT_CODE FROM PRR_EMPLOYEES EMP WHERE EMP.INITIALS = USER)) L_PJTretrieves the only project '04.748', the one I hardcoded in the first query.
But as you can guess we do not want to work with hardcode projects, but with a project that is assisgned to the user via PRR_EMPLOYEES.PJT_CODE attribute.
I hope someone can steer me in the right direction to solve this issue.
Thanks in advance
Auke Quist
Edited by: aukequist on May 2, 2010 4:38 PM -
I have iphone 5; my battery life decreased dramatically after updating to ios 6.1.2. How do I delete and go back to previous iso?
Downgrading the iOS isn't supported and wouldn't help even if you could. There have been reports of decreased battery life after every update since iOS 1.0.1.
There are lots of things that can be done including reinstalling push email accounts. basic phone reset (pressing both home and power buttons for at least 10 seconds until the Apple logo appears), and restoring the phone with and without a backup. -
SQL Query Performance downgrade rapidly after migrated to SQL2012 from SQL2000
Problem:
SQL statement
SQL 2000 (cost) SQL2012
1 customer select SQL Statement ( little long) 22 seconds
5 mins (after rebuild index)
Migration method:
1. Backup SQL2000 DB and restore to SQL2008;
2. Backup SQL2008 DB and restore to SQL2012.
Anybody can help on this case? Thanks!
Environment
SQL2000 and SQL2005 instances: 4CPU, 4GB RAM, Windows Server 2000 SP4
SQL2012 R2: 4 vitual CPU cores, 8GB RAM, Windows Server 2012R21. execution plan
|--Compute Scalar(DEFINE:([Expr1013]=isnull([Expr1011],(0.000000000000000e+000)), [Expr1014]=(0), [Expr1021]=isnull([Expr1019],(0.000000000000000e+000)), [Expr1022]=(0), [Expr1023]=(0), [Expr1028]=isnull([Expr1026],(0.000000000000000e+000)),
[Expr1033]=isnull([Expr1031],(0.000000000000000e+000)), [Expr1040]=isnull([Expr1038],(0.000000000000000e+000)), [Expr1047]=isnull([Expr1045],(0.000000000000000e+000)), [Expr1054]=isnull([Expr1052],(0.000000000000000e+000)), [Expr1061]=isnull([Expr1059],(0.000000000000000e+000)),
[Expr1068]=isnull([Expr1066],(0.000000000000000e+000)), [Expr1075]=isnull([Expr1073],(0.000000000000000e+000)), [Expr1082]=isnull([Expr1080],(0.000000000000000e+000)), [Expr1089]=isnull([Expr1087],(0.000000000000000e+000)), [Expr1096]=isnull([Expr1094],(0.000000000000000e+000)),
[Expr1103]=isnull([Expr1101],(0.000000000000000e+000)), [Expr1110]=isnull([Expr1108],(0.000000000000000e+000)), [Expr1117]=isnull([Expr1115],(0.000000000000000e+000)), [Expr1124]=isnull([Expr1122],(0.000000000000000e+000)), [Expr1131]=isnull([Expr1129],(0.000000000000000e+000)),
[Expr1138]=isnull([Expr1136],(0.000000000000000e+000)), [Expr1145]=isnull([Expr1143],(0.000000000000000e+000)), [Expr1152]=isnull([Expr1150],(0.000000000000000e+000)))),1,2,1,Compute Scalar,Compute Scalar,DEFINE:([Expr1013]=isnull([Expr1011],(0.000000000000000e+000)),
[Expr1014]=(0), [Expr1021]=isnull([Expr1019],(0.000000000000000e+000)), [Expr1022]=(0), [Expr1023]=(0), [Expr1028]=isnull([Expr1026],(0.000000000000000e+000)), [Expr1033]=isnull([Expr1031],(0.000000000000000e+000)), [Expr1040]=isnull([Expr1038],(0.000000000000000e+000)),
[Expr1047]=isnull([Expr1045],(0.000000000000000e+000)), [Expr1054]=isnull([Expr1052],(0.000000000000000e+000)), [Expr1061]=isnull([Expr1059],(0.000000000000000e+000)), [Expr1068]=isnull([Expr1066],(0.000000000000000e+000)), [Expr1075]=isnull([Expr1073],(0.000000000000000e+000)),
[Expr1082]=isnull([Expr1080],(0.000000000000000e+000)), [Expr1089]=isnull([Expr1087],(0.000000000000000e+000)), [Expr1096]=isnull([Expr1094],(0.000000000000000e+000)), [Expr1103]=isnull([Expr1101],(0.000000000000000e+000)), [Expr1110]=isnull([Expr1108],(0.000000000000000e+000)),
[Expr1117]=isnull([Expr1115],(0.000000000000000e+000)), [Expr1124]=isnull([Expr1122],(0.000000000000000e+000)), [Expr1131]=isnull([Expr1129],(0.000000000000000e+000)), [Expr1138]=isnull([Expr1136],(0.000000000000000e+000)), [Expr1145]=isnull([Expr1143],(0.000000000000000e+000)),
[Expr1152]=isnull([Expr1150],(0.000000000000000e+000))),[Expr1013]=isnull([Expr1011],(0.000000000000000e+000)), [Expr1014]=(0), [Channel], [CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name],
[CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg], [CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target],
[CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo], [CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1013], [Expr1014],
[Expr1021], [Expr1022], [Expr1023], [Expr1028], [Expr1033], [Expr1040], [Expr1047], [Expr1054], [Expr1061], [Expr1068], [Expr1075], [Expr1082], [Expr1089], [Expr1096], [Expr1103], [Expr1110], [Expr1117], [Expr1124], [Expr1131], [Expr1138], [Expr1145], [Expr1152],NULL,PLAN_ROW,0,1
|--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,3,2,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1899,689.5999,[CRW].[Channel], [CRW].[Channel_Mapping],
[CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg], [CRW].[Last_1y_mth_avg],
[CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo], [CRW].[OE_Short_Name], [CRW].[Item_Type],
[AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031], [Expr1038], [Expr1045], [Expr1052], [Expr1059], [Expr1066], [Expr1073], [Expr1080], [Expr1087], [Expr1094], [Expr1101], [Expr1108], [Expr1115], [Expr1122],
[Expr1129], [Expr1136], [Expr1143], [Expr1150],NULL,PLAN_ROW,0,1
|--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,4,3,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1891,689.2623,[CRW].[Channel],
[CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg],
[CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo],
[CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031], [Expr1038], [Expr1045], [Expr1052], [Expr1059], [Expr1066], [Expr1073], [Expr1080], [Expr1087], [Expr1094],
[Expr1101], [Expr1108], [Expr1115], [Expr1122], [Expr1129], [Expr1136], [Expr1143],NULL,PLAN_ROW,0,1
| |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,5,4,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1883,688.9249,[CRW].[Channel],
[CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg],
[CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo],
[CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031], [Expr1038], [Expr1045], [Expr1052], [Expr1059], [Expr1066], [Expr1073], [Expr1080], [Expr1087], [Expr1094],
[Expr1101], [Expr1108], [Expr1115], [Expr1122], [Expr1129], [Expr1136],NULL,PLAN_ROW,0,1
| | |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,6,5,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1875,688.5874,[CRW].[Channel],
[CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg],
[CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo],
[CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031], [Expr1038], [Expr1045], [Expr1052], [Expr1059], [Expr1066], [Expr1073], [Expr1080], [Expr1087], [Expr1094],
[Expr1101], [Expr1108], [Expr1115], [Expr1122], [Expr1129],NULL,PLAN_ROW,0,1
| | | |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,7,6,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1866,688.2499,[CRW].[Channel],
[CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg],
[CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo],
[CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031], [Expr1038], [Expr1045], [Expr1052], [Expr1059], [Expr1066], [Expr1073], [Expr1080], [Expr1087], [Expr1094],
[Expr1101], [Expr1108], [Expr1115], [Expr1122],NULL,PLAN_ROW,0,1
| | | | |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,8,7,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1858,687.9124,[CRW].[Channel],
[CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg],
[CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo],
[CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031], [Expr1038], [Expr1045], [Expr1052], [Expr1059], [Expr1066], [Expr1073], [Expr1080], [Expr1087], [Expr1094],
[Expr1101], [Expr1108], [Expr1115],NULL,PLAN_ROW,0,1
| | | | | |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,9,8,Nested Loops,Inner
Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1850,687.575,[CRW].[Channel], [CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name],
[CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg], [CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast],
[CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo], [CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031],
[Expr1038], [Expr1045], [Expr1052], [Expr1059], [Expr1066], [Expr1073], [Expr1080], [Expr1087], [Expr1094], [Expr1101], [Expr1108],NULL,PLAN_ROW,0,1
| | | | | | |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,10,9,Nested
Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1842,687.2375,[CRW].[Channel], [CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code],
[CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg], [CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast],
[CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo], [CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031],
[Expr1038], [Expr1045], [Expr1052], [Expr1059], [Expr1066], [Expr1073], [Expr1080], [Expr1087], [Expr1094], [Expr1101],NULL,PLAN_ROW,0,1
| | | | | | | |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,11,10,Nested
Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1834,686.9,[CRW].[Channel], [CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code],
[CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg], [CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast],
[CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo], [CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031],
[Expr1038], [Expr1045], [Expr1052], [Expr1059], [Expr1066], [Expr1073], [Expr1080], [Expr1087], [Expr1094],NULL,PLAN_ROW,0,1
| | | | | | | | |--Nested Loops(Inner Join, OUTER
REFERENCES:([CRW].[Parent_Cust_Code])),1,12,11,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1826,670.2579,[CRW].[Channel], [CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code],
[CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg], [CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target],
[CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo], [CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005],
[Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031], [Expr1038], [Expr1045], [Expr1052], [Expr1059], [Expr1066], [Expr1073], [Expr1080], [Expr1087],NULL,PLAN_ROW,0,1
| | | | | | | | | |--Nested
Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,13,12,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1818,661.1638,[CRW].[Channel], [CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name],
[CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg], [CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target],
[CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo], [CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1],
[Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031], [Expr1038], [Expr1045], [Expr1052], [Expr1059], [Expr1066], [Expr1073], [Expr1080],NULL,PLAN_ROW,0,1
| | | | | | | | | |
|--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,14,13,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1810,648.2534,[CRW].[Channel], [CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code],
[CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg], [CRW].[Last_1y_mth_avg], [CRW].[Aug_Target],
[CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo], [CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel],
[AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031], [Expr1038], [Expr1045], [Expr1052], [Expr1059], [Expr1066], [Expr1073],NULL,PLAN_ROW,0,1
| | | | | | | | | |
| |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,15,14,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1801,638.7095,[CRW].[Channel], [CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code],
[CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg], [CRW].[Last_1y_mth_avg], [CRW].[Aug_Target],
[CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo], [CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel],
[AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031], [Expr1038], [Expr1045], [Expr1052], [Expr1059], [Expr1066],NULL,PLAN_ROW,0,1
| | | | | | | | | |
| | |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,16,15,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1793,638.372,[CRW].[Channel], [CRW].[Channel_Mapping],
[CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg], [CRW].[Last_1y_mth_avg],
[CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo], [CRW].[OE_Short_Name], [CRW].[Item_Type],
[AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031], [Expr1038], [Expr1045], [Expr1052], [Expr1059],NULL,PLAN_ROW,0,1
| | | | | | | | | |
| | | |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,17,16,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1785,638.0345,[CRW].[Channel],
[CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg],
[CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo],
[CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031], [Expr1038], [Expr1045], [Expr1052],NULL,PLAN_ROW,0,1
| | | | | | | | | |
| | | | |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,18,17,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1777,627.3322,[CRW].[Channel],
[CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg],
[CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo],
[CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031], [Expr1038], [Expr1045],NULL,PLAN_ROW,0,1
| | | | | | | | | |
| | | | | |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,19,18,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1769,616.6299,[CRW].[Channel],
[CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg],
[CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo],
[CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031], [Expr1038],NULL,PLAN_ROW,0,1
| | | | | | | | | |
| | | | | | |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,20,19,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1761,605.9097,[CRW].[Channel],
[CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg],
[CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo],
[CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026], [Expr1031],NULL,PLAN_ROW,0,1
| | | | | | | | | |
| | | | | | | |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,21,20,Nested Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1753,281.6566,[CRW].[Channel],
[CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg],
[CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo],
[CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019], [Expr1026],NULL,PLAN_ROW,0,1
| | | | | | | | | |
| | | | | | | | |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,22,21,Nested Loops,Inner
Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1745,18.4746,[CRW].[Channel], [CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name],
[CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg], [CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast],
[CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo], [CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011], [Expr1019],NULL,PLAN_ROW,0,1
| | | | | | | | | |
| | | | | | | | | |--Nested Loops(Inner Join, OUTER REFERENCES:([CRW].[Parent_Cust_Code])),1,23,22,Nested
Loops,Inner Join,OUTER REFERENCES:([CRW].[Parent_Cust_Code]),NULL,497.7165,0,0.002080455,1736,14.40793,[CRW].[Channel], [CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code],
[CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg], [CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast],
[CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo], [CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006], [Expr1011],NULL,PLAN_ROW,0,1
| | | | | | | | | |
| | | | | | | | | | |--Compute Scalar(DEFINE:([Expr1005]=isnull([JDE_TEST].[dbo].[JDE_addressbook].[Area_1]
as [AB].[Area_1],N''), [Expr1006]=isnull([JDE_TEST].[dbo].[JDE_addressbook].[Local_Channel] as [AB].[Local_Channel],N''))),1,24,23,Compute Scalar,Compute Scalar,DEFINE:([Expr1005]=isnull([JDE_TEST].[dbo].[JDE_addressbook].[Area_1] as [AB].[Area_1],N''), [Expr1006]=isnull([JDE_TEST].[dbo].[JDE_addressbook].[Local_Channel]
as [AB].[Local_Channel],N'')),[Expr1005]=isnull([JDE_TEST].[dbo].[JDE_addressbook].[Area_1] as [AB].[Area_1],N''), [Expr1006]=isnull([JDE_TEST].[dbo].[JDE_addressbook].[Local_Channel] as [AB].[Local_Channel],N''),497.7165,0,4.977165E-05,1728,0.453685,[CRW].[Channel],
[CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code], [CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg],
[CRW].[Last_1y_mth_avg], [CRW].[Aug_Target], [CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo],
[CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel], [AB].[Area_1], [Expr1005], [Expr1006],NULL,PLAN_ROW,0,1
| | | | | | | | | |
| | | | | | | | | | | |--Sort(ORDER BY:([AB].[Area_1] ASC,
[AB].[Local_Channel] ASC, [CRW].[Parent_Cust_Code] ASC)),1,25,24,Sort,Sort,ORDER BY:([AB].[Area_1] ASC, [AB].[Local_Channel] ASC, [CRW].[Parent_Cust_Code] ASC),NULL,497.7165,0.01126126,0.00705794,1694,0.4536353,[CRW].[Channel], [CRW].[Channel_Mapping], [CRW].[Parent_Cust_Code],
[CRW].[Parent_Cust_Name], [CRW].[Customer_Code], [CRW].[Customer_Name], [CRW].[Rebate_Code], [CRW].[Rebate_Name], [CRW].[Ship_To_Code], [CRW].[Ship_To_Name], [CRW].[Qtr_Target], [CRW].[New_Cust], [CRW].[Last_2y_mth_avg], [CRW].[Last_1y_mth_avg], [CRW].[Aug_Target],
[CRW].[Sep_Target], [CRW].[Oct_Target], [CRW].[Nov_Target], [CRW].[Dec_Target], [CRW].[Sales_Forecast], [CRW].[RetreadFlag], [CRW].[Last_2y_mth_avg_RD], [CRW].[Last_1y_mth_avg_RD], [CRW].[報表歸屬客編], [CRW].[Memo], [CRW].[OE_Short_Name], [CRW].[Item_Type], [AB].[Local_Channel],
[AB].[Area_1],NULL,PLAN_ROW,0,1 -
Physical partitioning query performance wore than without
Hello experts,
I have copied InfoCube 0COPC_C04 to ZCPOC_C06 with a test-query and took over data from 0COPC_C04 to test the functionality of Repartitioning (~ 4 million records)
I did Repartitioning following instructions from note 1008833 for 0FISCPER (I used se38 RSDU_SET_FV_TO_FIX_VALUE to set 0FISCVARNT to constant) - starting-point is 001.2000 - end-point is 016.2010
Indexes and Statistcs are re-created.
We have Oracle 10.2.0.2.0 and SAPKW70022 on BW 700
So - from my point of view everything is fine - BUT: Queryperformance is worst than before - shown in rsrv.
Variable in Query is over 0FISCYEAR and 0FISCPER3 and NOT over 0FISCPER (a querytest with 0FISCPER brought the same bad performance result).
Even I read, that with physical partitioning the query reads PARALLEL --- I can not see any parallel things in sm50 / sm66 - I have excpected to see parallel readings due to my query - I asked for results from 001.2006 - 12.2010 - and 13 partions were created (related to se14 ).
What might be the problem?
Thanks for your answer,
Thomas
Edited by: Thomas Liebschner on Jan 4, 2011 3:28 PM#1171650 is already implemented (since 14.12.2010) --- I asked my collegaue from Basis-Team to send me the report.
> I read parallel-queryexcution in the SAP Press Galileo Press Book "SAP BW Peformanceoptimierung" written by Thomas Schröder (ISBN: 3-89842-718-8), Page 376. If you like, I can send this page as pdf to your mail stored in your business card.
Would be interesting to see that excerpt, yes.
> What I missed was to compress the F-Table.
>
> I'm wondering, that:
> 1. After Compressing 0COPC_C04 with 8 million records gave a dramatically improvement of query-performance. No partitioning.
Sure, usually a lot less data needs to be read now.
> 2. After a new Full-load from 0COPC_C04 to ZCOPC_C06 with rebuilding indices and statistics I got similar query-performance compared to 1
Also easy to understand.
The F-Facttable contains data per load. So data concerning the same business items will be in that table multiple times and need to be aggregated on-the-fly during query execution.
The E-Facttable in contrast just contains one entry per business item. Which is the same situation you'll find when you just have one single data load request.
> 3. If I compress ZCOPC_C06, then query-performance drops dramatically down (needs double time, if I use 0FISCPER, needs 8 times more in query with 0FISCYEAR and 0FISCPER3)
>
> additional information: I have merged partitions from ZCOPC_C06 to one partition --> checked by se14 /BIC/FZCOPC_C06 -- storage parameters
Hmm... ok, here we would really need to see what Oracle does with your Query and the partitioning scheme then.
What seems obvious is that as soon as you have just one partition, then there is no way for Oracle to split up work and leave uninteresting data aside (partition-pruning),
> Conclusion: it seems for me, that compression is enough - partitioning has no advantage in that dedicated scenario.
> Do I think right?
I think that compression is a must-do in 99% of all cases for SAP BI and that the partitioning of the E-Facttable should be reviewed on your system.
Up to here there is too little information available to tell whether or not it could benefit your query execution time.
Another aspect you might consider with partitioning the E-facttable is your data retention policy.
If you're about to throw away your data on, say, a yearly basis, then having the table partitioned that way can provide huge benefits.
My personal view to this is: you already payed for the most expensive and feature-rich database engine available for SAP BI - so why not go and exploit these features where possible?
best regards
Lars -
How to improve Query Performance
Hi Friends...
I Want to improve query performance.I need following things.
1.What is the process to findout the performance?. Any transaction code's and how to use?.
2.How can I know whether the query is running good or bad ,ie. in performance praspect.
3.I want to see the values i.e. how much time it is taking to run?. and where the defect is?.
4.How to improve the query performance?. After I did the needfull things to improve performance, I want to see the query execution time. i.e. it is running fast or not?.
Eg..
Eg 1. Need to create aggregates.
Solution: where can I create aggregates?. Now I'm in production system. So where I need to create? .i.e. indevelopment or in Quality or in Production system?.
Any chenges I need to do in Development?.Because I'm in Production system.
So please tell me solution for my questions.
Thanks
Ganga
Message was edited by: Ganga Nhi ganga
please refer oss note :557870 : Frequently asked questions on query performance
also refer to
Prakash's weblog
/people/prakash.darji/blog/2006/01/27/query-creation-checklist
/people/prakash.darji/blog/2006/01/26/query-optimization
performance docs on query
https://www.sdn.sap.com/irj/servlet/prt/portal/prtroot/docs/library/uuid/3f66ba90-0201-0010-ac8d-b61d8fd9abe9
https://www.sdn.sap.com/irj/servlet/prt/portal/prtroot/docs/library/uuid/cccad390-0201-0010-5093-fd9ec8157802
https://www.sdn.sap.com/irj/servlet/prt/portal/prtroot/docs/library/uuid/ce7fb368-0601-0010-64ba-fadc985a1f94
https://www.sdn.sap.com/irj/servlet/prt/portal/prtroot/docs/library/uuid/c8c4d794-0501-0010-a693-918a17e663cc
https://www.sdn.sap.com/irj/servlet/prt/portal/prtroot/docs/library/uuid/064fed90-0201-0010-13ae-b16fa4dab695
This is the oss notes of FAQ on query performance
1. What kind of tools are available to monitor the overall Query Performance?
1. BW Statistics
2. BW Workload Analysis in ST03N (Use Export Mode!)
3. Content of Table RSDDSTAT
2. Do I have to do something to enable such tools?
Yes, you need to turn on the BW Statistics:
RSA1, choose Tools -> BW statistics for InfoCubes
(Choose OLAP and WHM for your relevant Cubes)
3. What kind of tools is available to analyze a specific query in detail?
1. Transaction RSRT
2. Transaction RSRTRACE
4. Do I have an overall query performance problem?
i. Use ST03N -> BW System load values to recognize the problem. Use the number given in table 'Reporting - InfoCubes:Share of total time (s)' to check if one of the columns %OLAP, %DB, %Frontend shows a high number in all Info Cubes.
ii. You need to run ST03N in expert mode to get these values
5. What can I do if the database proportion is high for all queries?
Check:
1. If the database statistic strategy is set up properly for your DB platform (above all for the BW specific tables)
2. If database parameter set up accords with SAP Notes and SAP Services (EarlyWatch)
3. If Buffers, I/O, CPU, memory on the database server are exhausted?
4. If Cube compression is used regularly
5. If Database partitioning is used (not available on all DB platforms)
6. What can I do if the OLAP proportion is high for all queries?
Check:
1. If the CPUs on the application server are exhausted
2. If the SAP R/3 memory set up is done properly (use TX ST02 to find bottlenecks)
3. If the read mode of the queries is unfavourable (RSRREPDIR, RSDDSTAT, Customizing default)
7. What can I do if the client proportion is high for all queries?
Check whether most of your clients are connected via a WAN connection and the amount of data which is transferred is rather high.
8. Where can I get specific runtime information for one query?
1. Again you can use ST03N -> BW System Load
2. Depending on the time frame you select, you get historical data or current data.
3. To get to a specific query you need to drill down using the InfoCube name
4. Use Aggregation Query to get more runtime information about a single query. Use tab All data to get to the details. (DB, OLAP, and Frontend time, plus Select/ Transferred records, plus number of cells and formats)
9. What kind of query performance problems can I recognize using ST03N
values for a specific query?
(Use Details to get the runtime segments)
1. High Database Runtime
2. High OLAP Runtime
3. High Frontend Runtime
10. What can I do if a query has a high database runtime?
1. Check if an aggregate is suitable (use All data to get values "selected records to transferred records", a high number here would be an indicator for query performance improvement using an aggregate)
2. o Check if database statistics are update to data for the Cube/Aggregate, use TX RSRV output (use database check for statistics and indexes)
3. Check if the read mode of the query is unfavourable - Recommended (H)
11. What can I do if a query has a high OLAP runtime?
1. Check if a high number of Cells transferred to the OLAP (use "All data" to get value "No. of Cells")
2. Use RSRT technical Information to check if any extra OLAP-processing is necessary (Stock Query, Exception Aggregation, Calc. before Aggregation, Virtual Char. Key Figures, Attributes in Calculated Key Figs, Time-dependent Currency Translation) together with a high number of records transferred.
3. Check if a user exit Usage is involved in the OLAP runtime?
4. Check if large hierarchies are used and the entry hierarchy level is as deep as possible. This limits the levels of the hierarchy that must be processed. Use SE16 on the inclusion tables and use the List of Value feature on the column successor and predecessor to see which entry level of the hierarchy is used.
5. Check if a proper index on the inclusion table exist
12. What can I do if a query has a high frontend runtime?
1. Check if a very high number of cells and formatting are transferred to the Frontend (use "All data" to get value "No. of Cells") which cause high network and frontend (processing) runtime.
2. Check if frontend PC are within the recommendation (RAM, CPU MHz)
3. Check if the bandwidth for WAN connection is sufficient
REWARDING POINTS IS THE WAY OF SAYING THANKS IN SDN
CHEERS
RAVI -
"Error determining attribute" after adding navigational attribute to query
Hello all,
We are getting a "Error Error determining attribute, Abort System error in program SAPLRRK0 and form RSRDR;SRRK0f30-01-" error message when running a query after adding a navigational attribute. We tried adding the attribute of the characteristic directly in the query and this works ok. But when we try using the navigational attribute we get the error. We would like to use the navigational attribute so we can filter based on this attribute.
We've searched for notes regarding this problem and haven't found any. Any suggestions?
Thanks, Ronhi,
Please check if number of the fields after adding the Navigationl attribute the should not cross 50.
Check the RSRV test for the master data whose navigational attribute u r trying to add.
Thanks
Mukesh -
Problems with Full loads/Decreased query performance in Prod
We have a table which serves as a base for a complex view. The table has roughly around 10 Million records and its a daily full load(I know, that delta loads are much better for handling large sets of data, but this information is very dynamic and with the business time constraints and project deliverables, the best decision was to do a Full load).
This is the process we follow:
> Drop Indexes (All columns individual indexes which are used inside the complex view as joins)
> Truncate table
> Load data
> Recreate indexes.
All the above steps are performed from SAP Dataservices Thru scripts and sql() function to execute the command, no manual intervention what so ever.
After the job is successfully completed, the view doesn't refresh at all(It sits there forever). The same job when run across same volume of production data in Test environment performs much faster.
Then, how do I refresh the view is manually log into SQL Developer, drop all the indexes on the parent table, and re-create all the indexes in the same order as Dataservices script. It performs very well after till the next load (the next morning).
Any suggestions would be very helpful.
My main question is why does it run faster, when I drop and recreate the indexes? and doesnt complete when the indexes are created by the SQL() from data services tool.
Tried:
Explain Plan(in dev, Test, Prod): Query cost vaired accross environments but returned results with same return times (In Production after manual Index creation)
Tuning advisor (Only in Test) DBA evaluated it to be good.
Thanks
Nash
DB Version Oracle 11.0.7
Dataservices 3.2BluShadow and Harman
Thank You!
Im using a regular view, not a materialized view. and yes the query plan is completely different from Test and Production. In test the query was completely running on Hash based joins whereas in Production its using Nested Joins in the execution plan.
Will try to gather statistics after the load and as per BluShadow, will look on the way of writing a function that makes a call to Database.
Thank you all for taking sometime. I will try to test this out starting today and will extend tests over a couple of days.
Regards
Nash -
Severe Samba performance decrease after u6 - u7 upgrade
I just upgraded my Solaris 10 x86 system from u6 (kernel 138889-08) to u7 using LiveUpgrade. I have samba sharing some ZFS filesystems, and the first thing I noticed after the upgrade was a severe performance decrease in reading files via smb.
For example, using smbget from a MacOS client to retrieve a particular test file, pre-upgrade I was getting about 30Mb/sec, but after the upgrade to u7 I'm only getting 100Kb/sec. If I boot back to my alternate boot environment that still has u6, performance returns to normal. This happened when u7 was first released, so I just ignored it and went back to u6, and now I tried u7 again yesterday and applied all of the current security and most recommended patches (including the latest samba patch) and am still experiencing the same behavior.
I don't currently have any socket options or other performance tuning in my smb.conf, it is about as simple as possible with just a couple share definitions.
Any ideas why the upgrade would cause such problems for samba? The only troubleshooting I can think to check is that the network card (e1000g) isn't getting errors all of a sudden after the upgrade, but netstat -i shows everything is working as expected; 0 errors/collisions/etc.
Any suggestions would be appreciated!
Thanks,
MatthewHi Experts,
After i tried a few times, i can successfully start prepare with upgrade asistant monitor - Administrator >> Start Prepare,
Thanks -
Adding indexes to a table is slowing down query performance.
I am running a query against a table which contains approx. 4 million records in it. So I created 4 indexes on the table and noticed that the performance on my query drastically decreased. I went back and began remove and creating the indexes in different combinations. It turns out that whenever two of four indexes are created the performance worsens. The strange thing about this problem is when I do an explain plan on the query the cost is greater when the performance is better and the cost is less when the performance is worse. Also Oracle only uses one out of the four indexes on the table for this query.
I'd like to try to understand what is going on with the Oracle optimizer to try to fix this problem.Mark,
Below is the information you requested.
DATABASE: 10.2.0.3.0
QUERY:
select distinct object, object_access from betweb_objects
where instr(object_access,'RES\') = 0
and object_access_type = 'ADM'
and object in (select distinct object
from betweb_objects
where instr(object_access,'RES\') = 0
and object_access_type = 'NTK'
and object not like '%.%'
and substr(object_access,instr(object_access,'\')+1) in (select distinct substr(object_access,instr(object_access,'\')+1)
from betweb_objects
where object_access_type = 'NTK'
and instr(object_access,'RES\') = 0
minus
select distinct upper(id)
from uamp.ad_users
where status = 'A'))
TABLE:
BETWEB_OBJECTS
OBJECT VARCHAR2
OBJECT_ACCESS VARCHAR2
OBJECT_ACCESS_TYPE VARCHAR2
INDEXES ON BETWEB_OBJECTS:
BETWEB_OBJECTS_IDX1
OBJECT
BETWEB_OBJECTS_IDX2
OBJECT_ACCESS
BETWEB_OBJECTS_IDX3
OBJECT_ACCESS_TYPE
BETWEB_OBJECTS_IDX4
OBJECT_ACCESS
OBJECT_ACCESS_TYPE
TABLE:
AD_USERS
ID VARCHAR2
DOMAIN VARCHAR2
FNAME VARCHAR2
LNAME VARCHAR2
INITIALS VARCHAR2
TITLE VARCHAR2
DN VARCHAR2
COMPANY VARCHAR2
DEPARTMENT VARCHAR2
PHONE VARCHAR2
MANAGER VARCHAR2
STATUS VARCHAR2
DISPLAY_NAME VARCHAR2
EXPLAIN PLAN when performance is better:
SELECT STATEMENT Rows=13,414 Time=643,641 Cost=53,636,676 Bytes=6,948,452
HASH UNIQUE Rows=13,414 Time=643,641 Cost=53,636,676 Bytes=6,948,452
HASH JOIN Rows=694,646,835 Time=428 Cost=35,620 Bytes=359,827,060,530
VIEW VW_NSO_1 Rows=542 Time=42 Cost=3,491 Bytes=163,684
MINUS
SORT UNIQUE Rows=542 Bytes=9,756
INDEX FAST FULL SCAN BETWEB_OBJECTS_IDX4 Rows=26,427 Time=40 Cost=3,302 Bytes=475,686
SORT UNIQUE Rows=16,228 Bytes=178,508
TABLE ACCESS FULL AD_USERS Rows=16,360 Time=2 Cost=113 Bytes=179,960
HASH JOIN Rows=128,163,623 Time=322 Cost=26,805 Bytes=27,683,342,568
TABLE ACCESS FULL BETWEB_OBJECTS Rows=9,161 Time=154 Cost=12,805 Bytes=989,388
TABLE ACCESS FULL BETWEB_OBJECTS Rows=25,106 Time=154 Cost=12,822 Bytes=2,711,448
EXPLAIN PLAN when performance is worse:
SELECT STATEMENT Rows=13,414 Time=22,614 Cost=1,884,484 Bytes=2,897,424
HASH UNIQUE Rows=13,414 Time=22,614 Cost=1,884,484 Bytes=2,897,424
HASH JOIN Rows=128,163,623 Time=322 Cost=26,805 Bytes=27,683,342,568
TABLE ACCESS FULL BETWEB_OBJECTS Rows=9,161 Time=154 Cost=12,805 Bytes=989,388
TABLE ACCESS FULL BETWEB_OBJECTS Rows=25,106 Time=154 Cost=12,822 Bytes=2,711,448
MINUS
SORT UNIQUE NOSORT Rows=209 Time=40 Cost=3,305 Bytes=3,762
INDEX FAST FULL SCAN BETWEB_OBJECTS_IDX4 Rows=264 Time=40 Cost=3,304 Bytes=4,752
SORT UNIQUE NOSORT Rows=164 Time=2 Cost=115 Bytes=1,804
TABLE ACCESS FULL AD_USERS Rows=164 Time=2 Cost=114 Bytes=1,804 -
Poor Performance of OBIEE url after adding BI Publisher link in a page
Hi Gurus,
I've added a BI Publisher report link in my existing OBIEE dashboard page.
After adding this BIP link,the performance of the obiee url becomes very poor.....and it's taking around 10-15 to open the page.
Earlier it use to open with in 5-10 secs.
Is there any resolution for this.
Any help will be more appreciated.
Thanks,
Pramod.I have been able to improve processing speed up to
6-8 times with these two techniques:
1. A separate trickle thread was created that would
periodically call DbEnv::memp_trickle. This works
especially good on multicore machines, but also
speeds things up a bit on single CPU boxes. This
alone improved speed from 2K rec/sec to about 4K
rec/sec.Hello Stone,
I am facing a similar problem, and I too hope to resolve the same with memp_trickle. I had these queries.
1. what was the % of clean pages that you specified?
2. What duration were you clling this thread to call memp_trickle?
This would give me a rough idea about which to tune my app. Would really appreciate if you can answer these queries.
Regards,
Nishith.
>
2. Maintaining multiple secondary databases in real
time proved to be the bottleneck. The code was
changed to create secondary databases at the end of
the run (calling Db::associate with the DB_CREATE
flag), right before the reports are generated, which
use these secondary databases. This improved speed
from 4K rec/sec to 14K rec/sec. -
Poor performance on admin console after adding 1k+ teams and member profile
We run v7sp3p2 (MS) now but even back on v5.1 see degraded performance in form of response times over 60 seconds when browsing security hierarchy in admin console after adding over 1000 teams and member access profiles. We need the granularity in access for our many users. Does anyone know any tricks to prevent the glacial and disappointing response times while maintaining the necessary security? This behavior reflects poorly on the product's scalability.
Thanks,
ErikSorin, I want to make sure I understand your recommendation.
First, we do have more than 1000 users. Each location has a unique team to which their users belong, and each of these teams has a member access profile with corresponding read/write access to the dimension member representing their location. The users at each location only view data for their own location.
Is your recommendation to use another interface besides the admin console for accomplishing security updates?
We have a custom package that uses an API to upload data files with mass updates to security assignments and definitions, but hesitate to use this method for mundane changes for add/remove/change just a few users as this method bypasses the domain validation we get on the front end wherein we can only add users to the domain they correctly belong to.
To dodge the risk of a bad user/domain matchup we'd like to use front end but it appears to not support our scale well.
Thoughts on a setting or configuration we could manipulate to resolve the poor performance would be great - what levers can we pull? If this is all the tool can support we just live with it and pay the cost in wasted man hours over the life of the product... -
Crystal report running total explodes after adding a low-level characterist
I've profit center hierarchy, suppressed to show only level 5 of the hierarchy in crystal report and the report has Group1:Division, Group2:Company Code and Group3:Profit Center hierarchy and I have summary at each group level.
and now when I click on a profit center, I want to drill-down to show all customers for that profit center, sales document and few other characteristics.... that I want to add to the details.
After adding these characteristics to the details, the Summary at group division is not right for the AR Balance and I've other key figures and Iam sure they are also not correct. Any help with fixing this issue will be appreciated. Thanks.I've profit center hierarchy, suppressed to show only level 5 of the hierarchy in crystal report and the report has Group1:Division, Group2:Company Code and Group3:Profit Center hierarchy and I have summary at each group level.
and now when I click on a profit center, I want to drill-down to show all customers for that profit center, sales document and few other characteristics.... that I want to add to the details.
After adding these characteristics to the details, the Summary at group division is not right for the AR Balance and I've other key figures and Iam sure they are also not correct. Any help with fixing this issue will be appreciated. Thanks. -
How to improve query performance using infoset
I create one infoset that including 4 char.and 3 DSO which all are time-dependent.When query run, system show very poor perfomance, sometimes no data show in BEX anayzer. In this case I have to close BEX analyzer at first and then open it again, after that it show real results. It seems very strange. Does anybody has experience on infoset performance improvement. pls info, thanks!
Hi
As info set itself doesn't have any data so it improves Performance
also go through the below tips.
Find the query Run-time
where to find the query Run-time ?
557870 'FAQ BW Query Performance'
130696 - Performance trace in BW
This info may be helpful.
General tips
Using aggregates and compression.
Using less and complex cell definitions if possible.
1. Avoid using too many nav. attr
2. Avoid RKF and CKF
3. Many chars in row.
By using T-codes ST03 or ST03N
Go to transaction ST03 > switch to expert mode > from left side menu > and there in system load history and distribution for a particular day > check query execution time.
Statistical Records Part 4: How to read ST03N datasets from DB in NW2004
How to read ST03N datasets from DB
Try table rsddstats to get the statistics
Using cache memory will decrease the loading time of the report.
Run reporting agent at night and sending results to email. This will ensure use of OLAP cache. So later report execution will retrieve the result faster from the OLAP cache.
Also try
1. Use different parameters in ST03 to see the two important parameters aggregation ratio and records transferred to F/E to DB selected.
2. Use the program SAP_INFOCUBE_DESIGNS (Performance of BW infocubes) to see the aggregation ratio for the cube. If the cube does not appear in the list of this report, try to run RSRV checks on the cube and aggregates.
Go to SE38 > Run the program SAP_INFOCUBE_DESIGNS
It will shown dimension Vs Fact tables Size in percent.If you mean speed of queries on a cube as performance metric of cube,measure query runtime.
3. To check the performance of the aggregates,see the columns valuation and usage in aggregates.
Open the Aggregates...and observe VALUATION and USAGE columns.
"---" sign is the valuation of the aggregate. You can say -3 is the valuation of the aggregate design and usage. ++ means that its compression is good and access is also more (in effect, performance is good). If you check its compression ratio, it must be good. -- means the compression ratio is not so good and access is also not so good (performance is not so good).The more is the positives...more is useful the aggregate and more it satisfies the number of queries. The greater the number of minus signs, the worse the evaluation of the aggregate. The larger the number of plus signs, the better the evaluation of the aggregate.
if "-----" then it means it just an overhead. Aggregate can potentially be deleted and "+++++" means Aggregate is potentially very useful.
In valuation column,if there are more positive sign it means that the aggregate performance is good and it is useful to have this aggregate.But if it has more negative sign it means we need not better use that aggregate.
In usage column,we will come to know how far the aggregate has been used in query.
Thus we can check the performance of the aggregate.
Refer.
http://help.sap.com/saphelp_nw70/helpdata/en/b8/23813b310c4a0ee10000000a114084/content.htm
http://help.sap.com/saphelp_nw70/helpdata/en/60/f0fb411e255f24e10000000a1550b0/frameset.htm
performance ISSUE related to AGGREGATE
Note 356732 - Performance Tuning for Queries with Aggregates
Note 166433 - Options for finding aggregates (find optimal aggregates for an InfoCube)
4. Run your query in RSRT and run the query in the debug mode. Select "Display Aggregates Found" and "Do not use cache" in the debug mode. This will tell you if it hit any aggregates while running. If it does not show any aggregates, you might want to redesign your aggregates for the query.
Also your query performance can depend upon criteria and since you have given selection only on one infoprovider...just check if you are selecting huge amount of data in the report
Check for the query read mode in RSRT.(whether its A,X or H)..advisable read mode is X.
5. In BI 7 statistics need to be activated for ST03 and BI admin cockpit to work.
By implementing BW Statistics Business Content - you need to install, feed data and through ready made reports which for analysis.
http://help.sap.com/saphelp_nw70/helpdata/en/26/4bc0417951d117e10000000a155106/frameset.htm
/people/vikash.agrawal/blog/2006/04/17/query-performance-150-is-aggregates-the-way-out-for-me
https://www.sdn.sap.com/irj/servlet/prt/portal/prtroot/docs/library/uuid/1955ba90-0201-0010-d3aa-8b2a4ef6bbb2
https://www.sdn.sap.com/irj/servlet/prt/portal/prtroot/docs/library/uuid/ce7fb368-0601-0010-64ba-fadc985a1f94
http://help.sap.com/saphelp_nw04/helpdata/en/c1/0dbf65e04311d286d6006008b32e84/frameset.htm
You can go to T-Code DB20 which gives you all the performance related information like
Partitions
Databases
Schemas
Buffer Pools
Tablespaces etc
use tool RSDDK_CHECK_AGGREGATE in se38 to check for the corrupt aggregates
If aggregates contain incorrect data, you must regenerate them.
202469 - Using aggregate check tool
Note 646402 - Programs for checking aggregates (as of BW 3.0B SP15)
You can find out whether an aggregate is usefull or useless you can find out through a proccess of checking the tables RSDDSTATAGGRDEF*
Run the query in RSRT with statistics execute and come back you will get STATUID... copy this and check in the table...
This gives you exactly which infoobjects it's hitting, if any one of the object is missing it's useless aggregate.
6
Check SE11 > table RSDDAGGRDIR . You can find the last callup in the table.
Generate Report in RSRT
https://www.sdn.sap.com/irj/sdn/go/portal/prtroot/docs/library/uuid/cccad390-0201-0010-5093-fd9ec8157802
https://www.sdn.sap.com/irj/sdn/go/portal/prtroot/docs/library/uuid/4c0ab590-0201-0010-bd9a-8332d8b4f09c
Business Intelligence Journal Improving Query Performance in Data Warehouses
http://www.tdwi.org/Publications/BIJournal/display.aspx?ID=7891
Achieving BI Query Performance Building Business Intelligence
http://www.dmreview.com/issues/20051001/1038109-1.html
Assign points if useful
Cheers
SM -
Performance Decrease with ComboBoxes
Memory consumption and bad performance decrease when closing and reopening panels containing ComboBoxes.
Context:
- Running localMode
- Jdev 9.0.3.1 DE
- Business Component Version 9.0.3.10.62
- jdk 1.3.1_02
Panel (within an JInternal frame) with some JUComboBoxes with LOV-Binding to ViewObjects, only with a few entries (2-20)
We observed, that the count of JUIteratorBindings encreases with every new Panel (re)open.
After closing the Internal Frame (including the Panel) the IteratorBindings of all ComboBoxes keep alive and a set of new ones are added to the PanelBinding when opening the (same) Panel once more.
Is it a bug?
Have one to remove the IteratorBindings explicitly?
Is there any configuration possibility, that the IteratorBindings die with the Panel?
Has anyone the same problem?
Roswitha StepputtisYes, we experience similar problems. My suggestion would be to simply hide (setVisible(false)) your internal frames and reuse them when you open them again.
So, instead of dynamically re-creating your JInternalFrame instances, you keep a reference to them once they are created and reuse them each time they should be made visible. I think this will make your application more efficient as a whole.
Maybe you are looking for
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i create one form based on emp. then i create beanarea and set its "Implementation Class Property" to oracle.forms.demos.Calendar. i copied calendar.jar from D:\oracle\ds9i\forms90\demos\jars to this lacation D:\oracle\ds9i\forms90\java after i write
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hi, I have a procedure which took 15-20 minutes in the past to execute.Suddently it is taking 2 hours.When i examined i came to know that the sql statement is not using one of the index.I dropped the index and created it.The explain plan is generated
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Can you have a song that another person bought on iTunes
My sister has bought some songs on iTunes that I want to have. Is there a way she can share it to me on the same computer without me having to pay for it?
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I have downloaded the adobe cc desktop but when it asks me to sign in, it logs me right back out. How can I fix it?
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I Can redeem my iTunes card.pls help me