Time_out Dump on this query take too long time

hi experts,
in my report a query taking too long time
pl. provide performance tips or suggestions
select mkpf~mblnr mkpf~mjahr mkpf~usnam mkpf~vgart
       mkpf~xabln mkpf~xblnr mkpf~zshift mkpf~frbnr
       mkpf~bktxt mkpf~bldat mkpf~budat mkpf~cpudt
       mkpf~cputm mseg~anln1 mseg~anln2 mseg~aplzl
       mseg~aufnr mseg~aufpl mseg~bpmng mseg~bprme
       mseg~bstme mseg~bstmg mseg~bukrs mseg~bwart
       mseg~bwtar mseg~charg mseg~dmbtr mseg~ebeln
       mseg~ebelp mseg~erfme mseg~erfmg mseg~exbwr
       mseg~exvkw mseg~grund mseg~kdauf mseg~kdein
       mseg~kdpos mseg~kostl mseg~kunnr mseg~kzbew
       mseg~kzvbr mseg~kzzug mseg~lgort mseg~lifnr
       mseg~matnr mseg~meins mseg~menge mseg~lsmng
       mseg~nplnr mseg~ps_psp_pnr mseg~rsnum mseg~rspos
       mseg~shkzg mseg~sobkz mseg~vkwrt mseg~waers
       mseg~werks mseg~xauto mseg~zeile mseg~SGTXT
    into table itab
       from mkpf as mkpf
        inner join mseg as mseg
                on mkpf~MBLNR = mseg~mblnr
               and mkpf~mjahr = mseg~mjahr

no the original query is, i use where clouse with conditions.
select mkpf~mblnr mkpf~mjahr mkpf~usnam mkpf~vgart
       mkpf~xabln mkpf~xblnr mkpf~zshift mkpf~frbnr
       mkpf~bktxt mkpf~bldat mkpf~budat mkpf~cpudt
       mkpf~cputm mseg~anln1 mseg~anln2 mseg~aplzl
       mseg~aufnr mseg~aufpl mseg~bpmng mseg~bprme
       mseg~bstme mseg~bstmg mseg~bukrs mseg~bwart
       mseg~bwtar mseg~charg mseg~dmbtr mseg~ebeln
       mseg~ebelp mseg~erfme mseg~erfmg mseg~exbwr
       mseg~exvkw mseg~grund mseg~kdauf mseg~kdein
       mseg~kdpos mseg~kostl mseg~kunnr mseg~kzbew
       mseg~kzvbr mseg~kzzug mseg~lgort mseg~lifnr
       mseg~matnr mseg~meins mseg~menge mseg~lsmng
       mseg~nplnr mseg~ps_psp_pnr mseg~rsnum mseg~rspos
       mseg~shkzg mseg~sobkz mseg~vkwrt mseg~waers
       mseg~werks mseg~xauto mseg~zeile mseg~SGTXT
    into table itab
       from mkpf as mkpf
        inner join mseg as mseg
                on mkpf~MBLNR = mseg~mblnr
               and mkpf~mjahr = mseg~mjahr
    WHERE mkpf~budat IN budat
      AND mkpf~usnam IN usnam
      AND mkpf~vgart IN vgart
      AND mkpf~xblnr IN xblnr
      AND mkpf~zshift IN p_shift
      AND mseg~bwart IN bwart
      AND mseg~matnr IN matnr
      AND mseg~werks IN werks
      AND mseg~lgort IN lgort
      AND mseg~charg IN charg
      AND mseg~sobkz IN sobkz
      AND mseg~lifnr IN lifnr
      AND mseg~kunnr IN kunnr.

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Hi Richa,
Maybe you are executing the query with S_BANFN empty. Still based on the note 191492 you should change your query on like the following
1st Suggestion:
if gt_ekko_ekpo[] is not initial.
SELECT banfn banfpo       INTO TABLE gt_eket
      FROM eket FOR ALL ENTRIES IN gt_ekko_ekpo
      WHERE
     ebeln = gt_ekko_ekpo-ebeln AND
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if sy-subrc = 0.
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if gt_eket[] is not initial
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if sy-subrc = 0.
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2nd Suggestion:
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if gt_eket[] is not initial
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      FROM eban FOR ALL ENTRIES IN gt_eket
      WHERE
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Hope this helps.
Regards,
R

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Plz find my SELECT query below:
select w~mandt
wvbeln wposnr wmeins wmatnr wwerks wnetwr
wkwmeng wvrkme wmatwa wcharg w~pstyv
wposar wprodh wgrkor wantlf wkztlf wlprio
wvstel wroute wumvkz wumvkn wabgru wuntto
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wvpwrk wmvgr1 wmvgr2 wmvgr3 wmvgr4 wmvgr5
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xetenr xwmeng xbmeng xettyp xwepos xabart
x~edatu
xtddat xmbdat xlddat xwadat xabruf xetart
x~ezeit
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from vbap as w
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xposnr = wposnr and
xmandt = wmandt
where
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( ( ( erdat > pre_dat and erdat < p_syndt ) or
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x~plart in s_pln_tp and
x~etart in s_etart and
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1.     Selection Criteria
2.     Select Statements
     Select Queries
     SQL Interface
     Aggregate Functions
     For all Entries
Select Over more than one internal table
Selection Criteria
1.     Restrict the data to the selection criteria itself, rather than filtering it out using the ABAP code using CHECK statement.
2.     Select with selection list.
SELECT * FROM SBOOK INTO SBOOK_WA.
CHECK: SBOOK_WA-CARRID = 'LH' AND
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ENDSELECT.
The above code can be much more optimized by the code written below which avoids CHECK, selects with selection list
SELECT CARRID CONNID FLDATE BOOKID FROM SBOOK INTO TABLE T_SBOOK
WHERE SBOOK_WA-CARRID = 'LH' AND
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Select Statements   Select Queries
1.     Avoid nested selects
SELECT * FROM EKKO INTO EKKO_WA.
SELECT * FROM EKAN INTO EKAN_WA
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ENDSELECT.
ENDSELECT.
The above code can be much more optimized by the code written below.
SELECT PF1 PF2 FF3 FF4 INTO TABLE ITAB
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2.     Select all the records in a single shot using into table clause of select statement rather than to use Append statements.
SELECT * FROM SBOOK INTO SBOOK_WA.
CHECK: SBOOK_WA-CARRID = 'LH' AND
         SBOOK_WA-CONNID = '0400'.
ENDSELECT.
The above code can be much more optimized by the code written below which avoids CHECK, selects with selection list and puts the data in one shot using into table
SELECT CARRID CONNID FLDATE BOOKID FROM SBOOK INTO TABLE T_SBOOK
WHERE SBOOK_WA-CARRID = 'LH' AND
              SBOOK_WA-CONNID = '0400'.
3.     When a base table has multiple indices, the where clause should be in the order of the index, either a primary or a secondary index.
To choose an index, the optimizer checks the field names specified in the where clause and then uses an index that has the same order of the fields. In certain scenarios, it is advisable to check whether a new index can speed up the performance of a program. This will come handy in programs that access data from the finance tables.
4.     For testing existence, use Select.. Up to 1 rows statement instead of a Select-Endselect-loop with an Exit.
SELECT * FROM SBOOK INTO SBOOK_WA
UP TO 1 ROWS
WHERE CARRID = 'LH'.
ENDSELECT.
The above code is more optimized as compared to the code mentioned below for testing existence of a record.
SELECT * FROM SBOOK INTO SBOOK_WA
    WHERE CARRID = 'LH'.
EXIT.
ENDSELECT.
5.     Use Select Single if all primary key fields are supplied in the Where condition .
If all primary key fields are supplied in the Where conditions you can even use Select Single.
Select Single requires one communication with the database system, whereas Select-Endselect needs two.
Select Statements SQL Interface
1.     Use column updates instead of single-row updates
to update your database tables.
SELECT * FROM SFLIGHT INTO SFLIGHT_WA.
SFLIGHT_WA-SEATSOCC =
    SFLIGHT_WA-SEATSOCC - 1.
UPDATE SFLIGHT FROM SFLIGHT_WA.
ENDSELECT.
The above mentioned code can be more optimized by using the following code
UPDATE SFLIGHT
       SET SEATSOCC = SEATSOCC - 1.
2.     For all frequently used Select statements, try to use an index.
SELECT * FROM SBOOK CLIENT SPECIFIED INTO SBOOK_WA
WHERE CARRID = 'LH'
    AND CONNID = '0400'.
ENDSELECT.
The above mentioned code can be more optimized by using the following code
SELECT * FROM SBOOK CLIENT SPECIFIED INTO SBOOK_WA
WHERE MANDT IN ( SELECT MANDT FROM T000 )
    AND CARRID = 'LH'
    AND CONNID = '0400'.
ENDSELECT.
3.     Using buffered tables improves the performance considerably.
Bypassing the buffer increases the network considerably
SELECT SINGLE * FROM T100 INTO T100_WA
BYPASSING BUFFER
WHERE     SPRSL = 'D'
        AND ARBGB = '00'
        AND MSGNR = '999'.
The above mentioned code can be more optimized by using the following code
SELECT SINGLE * FROM T100 INTO T100_WA
WHERE     SPRSL = 'D'
        AND ARBGB = '00'
        AND MSGNR = '999'.
Select Statements Aggregate Functions
     If you want to find the maximum, minimum, sum and average value or the count of a database column, use a select list with aggregate functions instead of computing the aggregates yourself.
Some of the Aggregate functions allowed in SAP are MAX, MIN, AVG, SUM, COUNT, COUNT( * )
Consider the following extract.
            Maxno = 0.
            Select * from zflight where airln = LF and cntry = IN.
             Check zflight-fligh > maxno.
             Maxno = zflight-fligh.
            Endselect.
The above mentioned code can be much more optimized by using the following code.
Select max( fligh ) from zflight into maxno where airln = LF and cntry = IN.
Select Statements For All Entries
     The for all entries creates a where clause, where all the entries in the driver table are combined with OR. If the number of entries in the driver table is larger than rsdb/max_blocking_factor, several similar SQL statements are executed to limit the length of the WHERE clause.
     The plus
     Large amount of data
     Mixing processing and reading of data
     Fast internal reprocessing of data
     Fast
     The Minus
     Difficult to program/understand
     Memory could be critical (use FREE or PACKAGE size)
Points to be must considered FOR ALL ENTRIES
     Check that data is present in the driver table
     Sorting the driver table
     Removing duplicates from the driver table
Consider the following piece of extract
          Loop at int_cntry.
Select single * from zfligh into int_fligh
where cntry = int_cntry-cntry.
Append int_fligh.
                      Endloop.
The above mentioned can be more optimized by using the following code.
Sort int_cntry by cntry.
Delete adjacent duplicates from int_cntry.
If NOT int_cntry[] is INITIAL.
            Select * from zfligh appending table int_fligh
            For all entries in int_cntry
            Where cntry = int_cntry-cntry.
Endif.
Select Statements Select Over more than one Internal table
1.     Its better to use a views instead of nested Select statements.
SELECT * FROM DD01L INTO DD01L_WA
WHERE DOMNAME LIKE 'CHAR%'
        AND AS4LOCAL = 'A'.
SELECT SINGLE * FROM DD01T INTO DD01T_WA
    WHERE   DOMNAME    = DD01L_WA-DOMNAME
        AND AS4LOCAL   = 'A'
        AND AS4VERS    = DD01L_WA-AS4VERS
        AND DDLANGUAGE = SY-LANGU.
ENDSELECT.
The above code can be more optimized by extracting all the data from view DD01V_WA
SELECT * FROM DD01V INTO DD01V_WA
WHERE DOMNAME LIKE 'CHAR%'
        AND DDLANGUAGE = SY-LANGU.
ENDSELECT
2.     To read data from several logically connected tables use a join instead of nested Select statements. Joins are preferred only if all the primary key are available in WHERE clause for the tables that are joined. If the primary keys are not provided in join the Joining of tables itself takes time.
SELECT * FROM EKKO INTO EKKO_WA.
SELECT * FROM EKAN INTO EKAN_WA
      WHERE EBELN = EKKO_WA-EBELN.
ENDSELECT.
ENDSELECT.
The above code can be much more optimized by the code written below.
SELECT PF1 PF2 FF3 FF4 INTO TABLE ITAB
    FROM EKKO AS P INNER JOIN EKAN AS F
      ON PEBELN = FEBELN.
3.     Instead of using nested Select loops it is often better to use subqueries.
SELECT * FROM SPFLI
INTO TABLE T_SPFLI
WHERE CITYFROM = 'FRANKFURT'
    AND CITYTO = 'NEW YORK'.
SELECT * FROM SFLIGHT AS F
    INTO SFLIGHT_WA
    FOR ALL ENTRIES IN T_SPFLI
    WHERE SEATSOCC < F~SEATSMAX
      AND CARRID = T_SPFLI-CARRID
      AND CONNID = T_SPFLI-CONNID
      AND FLDATE BETWEEN '19990101' AND '19990331'.
ENDSELECT.
The above mentioned code can be even more optimized by using subqueries instead of for all entries.
SELECT * FROM SFLIGHT AS F INTO SFLIGHT_WA
    WHERE SEATSOCC < F~SEATSMAX
      AND EXISTS ( SELECT * FROM SPFLI
                     WHERE CARRID = F~CARRID
                       AND CONNID = F~CONNID
                       AND CITYFROM = 'FRANKFURT'
                       AND CITYTO = 'NEW YORK' )
      AND FLDATE BETWEEN '19990101' AND '19990331'.
ENDSELECT.
1.     Table operations should be done using explicit work areas rather than via header lines.
READ TABLE ITAB INTO WA WITH KEY K = 'X BINARY SEARCH.
IS MUCH FASTER THAN USING
READ TABLE ITAB INTO WA WITH KEY K = 'X'.
If TAB has n entries, linear search runs in O( n ) time, whereas binary search takes only O( log2( n ) ).
2.     Always try to use binary search instead of linear search. But dont forget to sort your internal table before that.
READ TABLE ITAB INTO WA WITH KEY K = 'X'. IS FASTER THAN USING
READ TABLE ITAB INTO WA WITH KEY (NAME) = 'X'.
3.     A dynamic key access is slower than a static one, since the key specification must be evaluated at runtime.
4.     A binary search using secondary index takes considerably less time.
5.     LOOP ... WHERE is faster than LOOP/CHECK because LOOP ... WHERE evaluates the specified condition internally.
LOOP AT ITAB INTO WA WHERE K = 'X'.
ENDLOOP.
The above code is much faster than using
LOOP AT ITAB INTO WA.
CHECK WA-K = 'X'.
ENDLOOP.
6.     Modifying selected components using MODIFY itab TRANSPORTING f1 f2.. accelerates the task of updating a line of an internal table.
WA-DATE = SY-DATUM.
MODIFY ITAB FROM WA INDEX 1 TRANSPORTING DATE.
The above code is more optimized as compared to
WA-DATE = SY-DATUM.
MODIFY ITAB FROM WA INDEX 1.
7.     Accessing the table entries directly in a "LOOP ... ASSIGNING ..." accelerates the task of updating a set of lines of an internal table considerably
Modifying selected components only makes the program faster as compared to Modifying all lines completely.
e.g,
LOOP AT ITAB ASSIGNING <WA>.
I = SY-TABIX MOD 2.
IF I = 0.
    <WA>-FLAG = 'X'.
ENDIF.
ENDLOOP.
The above code works faster as compared to
LOOP AT ITAB INTO WA.
I = SY-TABIX MOD 2.
IF I = 0.
    WA-FLAG = 'X'.
    MODIFY ITAB FROM WA.
ENDIF.
ENDLOOP.
8.    If collect semantics is required, it is always better to use to COLLECT rather than READ BINARY and then ADD.
LOOP AT ITAB1 INTO WA1.
READ TABLE ITAB2 INTO WA2 WITH KEY K = WA1-K BINARY SEARCH.
IF SY-SUBRC = 0.
    ADD: WA1-VAL1 TO WA2-VAL1,
         WA1-VAL2 TO WA2-VAL2.
    MODIFY ITAB2 FROM WA2 INDEX SY-TABIX TRANSPORTING VAL1 VAL2.
ELSE.
    INSERT WA1 INTO ITAB2 INDEX SY-TABIX.
ENDIF.
ENDLOOP.
The above code uses BINARY SEARCH for collect semantics. READ BINARY runs in O( log2(n) ) time. The above piece of code can be more optimized by
LOOP AT ITAB1 INTO WA.
COLLECT WA INTO ITAB2.
ENDLOOP.
SORT ITAB2 BY K.
COLLECT, however, uses a hash algorithm and is therefore independent
of the number of entries (i.e. O(1)) .
9.    "APPEND LINES OF itab1 TO itab2" accelerates the task of appending a table to another table considerably as compared to LOOP-APPEND-ENDLOOP.
APPEND LINES OF ITAB1 TO ITAB2.
This is more optimized as compared to
LOOP AT ITAB1 INTO WA.
APPEND WA TO ITAB2.
ENDLOOP.
10.   DELETE ADJACENT DUPLICATES accelerates the task of deleting duplicate entries considerably as compared to READ-LOOP-DELETE-ENDLOOP.
DELETE ADJACENT DUPLICATES FROM ITAB COMPARING K.
This is much more optimized as compared to
READ TABLE ITAB INDEX 1 INTO PREV_LINE.
LOOP AT ITAB FROM 2 INTO WA.
IF WA = PREV_LINE.
    DELETE ITAB.
ELSE.
    PREV_LINE = WA.
ENDIF.
ENDLOOP.
11.   "DELETE itab FROM ... TO ..." accelerates the task of deleting a sequence of lines considerably as compared to DO -DELETE-ENDDO.
DELETE ITAB FROM 450 TO 550.
This is much more optimized as compared to
DO 101 TIMES.
DELETE ITAB INDEX 450.
ENDDO.
12.   Copying internal tables by using ITAB2[ ] = ITAB1[ ] as compared to LOOP-APPEND-ENDLOOP.
ITAB2[] = ITAB1[].
This is much more optimized as compared to
REFRESH ITAB2.
LOOP AT ITAB1 INTO WA.
APPEND WA TO ITAB2.
ENDLOOP.
13.   Specify the sort key as restrictively as possible to run the program faster.
SORT ITAB BY K. makes the program runs faster as compared to SORT ITAB.
Internal Tables         contd
Hashed and Sorted tables
1.     For single read access hashed tables are more optimized as compared to sorted tables.
2.      For partial sequential access sorted tables are more optimized as compared to hashed tables
Hashed And Sorted Tables
Point # 1
Consider the following example where HTAB is a hashed table and STAB is a sorted table
DO 250 TIMES.
N = 4 * SY-INDEX.
READ TABLE HTAB INTO WA WITH TABLE KEY K = N.
IF SY-SUBRC = 0.
ENDIF.
ENDDO.
This runs faster for single read access as compared to the following same code for sorted table
DO 250 TIMES.
N = 4 * SY-INDEX.
READ TABLE STAB INTO WA WITH TABLE KEY K = N.
IF SY-SUBRC = 0.
ENDIF.
ENDDO.
Point # 2
Similarly for Partial Sequential access the STAB runs faster as compared to HTAB
LOOP AT STAB INTO WA WHERE K = SUBKEY.
ENDLOOP.
This runs faster as compared to
LOOP AT HTAB INTO WA WHERE K = SUBKEY.
ENDLOOP.

This report takes a long time

Hello:
I have this report and to run it takes a long time, how can I optimize it?
thank you very much.
======= THIS IS MY REPORTS =======
{ NAMEWIDTH 15 }
{ WIDTH 15 }
{ SUPFEED }
<SUPSHARE
{DECIMAL 2}
{ NOINDENTGEN }
{ SUPHEADING }
{ROWREPEAT}
<SPARSE
{ SUPBRACKETS }
<COLUMN (Accounts,Scenarios)
"Mov_Ppto"
Real
&Esc_Rep
<PAGE("Time Periods", Years, Moneda, Periodicidad, Producto, Versions)
Producto
&Mes_Rep
&Year_Rep
Moneda
Mensual
Final
<RESTRICT(@DATACOL(1) = #Missing OR @DATACOL(2) = #Missing)
<ROW (Cliente, Ejecutivos,"Jefe de Grupo",Entities)
<LINK (<LEV("Cliente",0) AND <DESCENDANTS("CLIENTES BE"))
<LINK (<GEN("Ejecutivos",3))
<LINK (<GEN("Jefe de Grupo",3))
<LINK (<GEN("Entities",5) AND NOT <DESCENDANTS(U4728))
====== THIS IS THE INFORMATION OF DATABASE ========
Name : Plan1
Application Name : BEMP_DES
Database Type : NORMAL
Status : Loaded
Elapsed Db Time : 00:01:07:41
Users Connected : 2
Blocks Locked : 0
Dimensions : 12
Data Status : Data has not been modified
since last calculation.
Data File Cache Size Setting : 0
Current Data File Cache Size : 0
Data Cache Size Setting : 268393440
Current Data Cache Size : 2086560
Index Cache Size Setting : 307200000
Current Index Cache Size : 307200000
Index Page Size Setting : 8192
Current Index Page Size : 8192
Cache Memory Locking : Disabled
Database State : Read-write
Data Compression on Disk : Yes
Data Compression Type : BitMap Compression
Retrieval Buffer Size (in K) : 90
Retrieval Sort Buffer Size (in K) : 90
Isolation Level : Uncommitted Access
Pre Image Access : No
Time Out : Never
Number of blocks modified before internal commit : 3000
Number of rows to data load before internal commit : 0
Number of disk volume definitions : 1
1) Vol: f, Size: Unlimited, File Type: 3, Size: 2097152K
Currency Country Dimension Member : Entities
Currency Time Dimension Member : Time Periods
Currency Category Dimension Member : Accounts
Currency Type Dimension Member :
Currency Partition Member :
Request Info
Request Type : Data Load
User Name : admin
Start Time : Fri Apr 18 17:45:05 2008
End Time : Fri Apr 18 17:46:05 2008
Request Type : Customized Calculation
User Name : admin
Start Time : Tue Apr 29 18:32:05 2008
End Time : Wed Apr 30 04:14:37 2008
Request Type : Outline Update
User Name : admin
Start Time : Sun Apr 06 16:24:58 2008
End Time : Sun Apr 06 17:50:46 2008
Description:
Allow Database to Start : Yes
Start Database when Application Starts : Yes
Access Level : None
Data File Cache Size : 33554432
Data Cache Size : 268435456
Aggregate Missing Values : No
Perform two pass calc when [CALC ALL;] : Yes
Create blocks on equation : Yes
Currency DB Name : N/A
Currency Conversion Type Member : N/A
Currency Conversion Type : N/A
Index Cache Size : 307200000
Index Page Size : 8192
Cache Memory Locking : Disabled
Data Compression on Disk : Yes
Data Compression Type : BitMap Compression
Retrieval Buffer Size (in K) : 90
Retrieval Sort Buffer Size (in K) : 90
Isolation Level : Uncommitted Access
Pre Image Access : Yes
Time Out after : 20 sec.
Number of blocks modified before internal commit : 3000
Number of rows to data load before internal commit : 0
Number of disk volume definitions : 1
1) Vol: f, Size: Unlimited, File Type: 3, Size: 2097152K
I/O Access Mode (pending) : Buffered
I/O Access Mode (in use) : Buffered
Direct I/O Type (in use) : N/A

Hi
Hope you have resolved this already, otherwise, generating cost collectors would mean you are allowing cots to be posted into RE-FX using Settlement units. If there are no costs to be posted with an SU, then you do not need to run RECSSS.
Regards
MK

Time_out Dump on this query take too long time

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