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Former Member

performance

Hi friends

I am writing below code

loop at tab1.

select single * from tablename

where objnr = tab1-field.

if sy-subrc = 0.

delete tab1.

continue.

else.

perform sleset.

endif.

endloop.

select inside the loop statement, This will raise performance issue. pls let me know how to rewrite the code without effecting the performance

thanks

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9 Answers

  • author's profile photo Former Member
    Former Member
    Posted on Jan 24, 2008 at 02:46 PM

    Press F1 on SELECT and look at the section on FOR ALL ENTRIES.

    Rob

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  • Posted on Jan 25, 2008 at 04:26 AM

    Hi karthik,

    Put the select statement before the loop for all entries in tab1.

    Now inside the loop use Read statement for objnr = tab1-field.

    This will solve your problem.

    Reward Points if Helpful.

    Regards,

    Sachin M M

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  • Posted on Jan 25, 2008 at 04:39 AM

    Hi,

    sort the internal table tab1 by field.

    change the existing query to this :

    if not tab1[] is initial.

    select * from tablename into tab2

    for all entries in tab1

    where objnr = tab1-field.

    if sy-subrc ne 0.

    • do the action which you want to take

    endif.

    endif.

    Now your tab2 will contain only those entries which are present in tablename.

    If you want to delete the entries from tab1 which are not present in tab2 then

    sort tb_tab2 by field.

    loop at tab1.

    read table tab with key field = tab1-field binary search transporting no fields.

    sy-subrc ne 0.

    delete tab1.

    endif.

    endloop.

    Hope this helps you!!

    Thanks and Regards,

    Sriranjani Chimakurthy.

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  • Posted on Jan 25, 2008 at 09:18 AM

    Sorry, there is not automatically a performance issue if there is SELECT SINGLE inside a LOOP.

    Usually it is o.k.

    You should only change the coding, if the internal table tab1 and the database table for the SELECT are very large and the whole this is really performance crictical.

    But if you change then you should really know what you doing.

    The FOR ALL ENTRIES does not require a sorted table tab1.

    Instead of the SELECT SINGLE there must be READ inside the LOOP the READ must at least be a READ BINARY SEARCH better a HASHED READ.

    For performance optimization of existing coding I would always recommend you to run trace

    (SE30 and ST05) and concentrate on the top contributions.

    I would wonder there are no other issues, with much more potential.

    Siegfried

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  • author's profile photo Former Member
    Former Member
    Posted on Jan 25, 2008 at 12:07 PM

    AVOID LOOP AND WRITE THE READ CONDITION IT WILL IMPROVE THE PERFORMANCE

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  • author's profile photo Former Member
    Former Member
    Posted on Jan 25, 2008 at 12:07 PM

    Ways of Performance Tuning

    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

    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

    SELECT CARRID CONNID FLDATE BOOKID FROM SBOOK INTO TABLE T_SBOOK

    WHERE SBOOK_WA-CARRID = 'LH' AND

    SBOOK_WA-CONNID = '0400'.

    Select Statements Select Queries

    1. Avoid nested selects

    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.

    Note: A simple SELECT loop is a single database access whose result is passed to the ABAP program line by line. Nested SELECT loops mean that the number of accesses in the inner loop is multiplied by the number of accesses in the outer loop. One should therefore use nested SELECT loops only if the selection in the outer loop contains very few lines or the outer loop is a SELECT SINGLE statement.

    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 don’t 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.

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  • author's profile photo Former Member
    Former Member
    Posted on Jan 25, 2008 at 03:02 PM

    Please look at the sample code below. You can select from the table outside the loop using for all entries and then use read statements in the loop. Again the delete statement within the loop will cause performance issues. In your code your delete statament is not doing anything so I have excluded it. If the deletion of the entries in table tab1 is necessary for later processing, create a field of type CHAR1 in table tab1, mark the records to be deleted by modifying the record with 'X' in this field and after the loop delete all the entries with one delete statement where this field in 'X'.

    types: begin of ty_tablename,

    objnr type tablename-objnr,

    end of ty_tablename.

    data: tab2 like table of tab1,

    t_tablename type hashed table of ty_tablename

    with unique key objnr.

    if not tab1[] is initial.

    tab2[] = tab1[].

    sort tab2 with field.

    delete adjacent duplicates from tab2 comparing field.

    select objnr

    from tablename

    into table of t_tablname

    for all entries in tab2

    where objnr eq tab2-field.

    endif.

    loop at tab1.

    read table t_tablname with key objnr = tab1-field

    transporting no fields.

    if sy-subrc ne 0.

    perform sleset.

    endif.

    endloop.

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  • author's profile photo Former Member
    Former Member
    Posted on Jan 29, 2008 at 06:14 AM

    Hi!

    Put the select statement before the loop for all entries in tab1.

    Now inside the loop use Read statement for objnr = tab1-field.

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  • author's profile photo Former Member
    Former Member
    Posted on Jan 29, 2008 at 06:21 AM

    HI

    points to improve performance in the report

    Ways of Performance Tuning

    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

    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

    SELECT CARRID CONNID FLDATE BOOKID FROM SBOOK INTO TABLE T_SBOOK

    WHERE SBOOK_WA-CARRID = 'LH' AND

    SBOOK_WA-CONNID = '0400'.

    Select Statements Select Queries

    1. Avoid nested selects

    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 P~F1 P~F2 F~F3 F~F4 INTO TABLE ITAB

    FROM EKKO AS P INNER JOIN EKAN AS F

    ON P~EBELN = F~EBELN.

    Note: A simple SELECT loop is a single database access whose result is passed to the ABAP program line by line. Nested SELECT loops mean that the number of accesses in the inner loop is multiplied by the number of accesses in the outer loop. One should therefore use nested SELECT loops only if the selection in the outer loop contains very few lines or the outer loop is a SELECT SINGLE statement.

    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 P~F1 P~F2 F~F3 F~F4 INTO TABLE ITAB

    FROM EKKO AS P INNER JOIN EKAN AS F

    ON P~EBELN = F~EBELN.

    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 don’t 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.

    Kindly Reward Points If Found Usefull,

    Cheers,

    Chaitanya.

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