Performance tuning

[Former Member]

Hi experts

pls could u tell me what are the performance issues other than Select statement.

other than data base related.....

Thax heaps

kondal

[Former Member]

hi kondal,

Mainly performance issues are associated with select stmt and various types of Loops we use in our program.

[Former Member]

Or doing a SELECT ... FOR ALL ENTRIES, when the internal table is empty.

Loop in a loop in a loop etc.

You can see a lot of examples when you are in the ABAP editor.

Then go to Environment-->Performance examples.

[Former Member]

Hi,

Definitely ‘Select*’ statement makes the performance issue if not use properly, so that you can choose the following ways which it better for performance issues.

- Write the select statement with required field names instead of all fields (*) which avoids the performance issue.

- Along with selected field names you may also take care in where condition: you should use only key fields in the where conditions and also maintain the sequence of key fields which they occurred in table if possible.

- Suppose if you use the non-key fields in where condition it makes lot of performance issues and there is no options to use key-fields then you have to create the secondary index for those non-key fields.

-use binary search concept.

-make proper cleare statement after no long use of internal tables

-avoid the joins concept and use the for all entries syntax etc....

• Select Statements within Loop processing is not recommended. Preferred approach is to select data into an itab and then read the itab to access specific records

• Do not use Nested Selects, Selects within Loops. or SELECT...ENDSELECT

• Do not use Select * unless at least 70% of fields are needed

• Select only the fields you require.

• Do not use INTO CORRESPONDING

• Do not do Order By on non key fields

• Force optimizer to use the index where possible

• If primary index can not be used, look for alternate indexes or alternate index tables

• Avoid Use of LIKE in the Where clause on index fields. It will force a non index read.

• Avoid Use of NOT conditions in the Where clause on index fields. It will force a non index read.

• Select Single MUST have the primary key fully specified in the WHERE clause. Otherwise use Select.. Up to 1 Rows.

• Avoid DISTINCT see performance standards for usage

• Consider filtering on the appserver rather than in a WHERE statement

• SAP Recommendation on Joins - try not to exceed a 3 Table Join

• <b>When using "Select.. For all Entries". The following 4 rules MUST be followed:</b>

o Check to make sure driver itab is not empty

o Always SORT the itab (driver table) by keys. Specify all keys used in the Where clause

o DELETE Adjacent Duplicates Comparing the keys that were sorted.

o All Primary Key Fields must be in the Select List

<b>Internal Tables :</b>

Internal tables are considered to be the true work horse of ABAP. They can have a big impact on processing and performance when programmed incorrectly. Use the quick checklist below to help guide you when coding internal table(itab) processing.

Internal Table Quick Checklist

• Loop at itab must always use a work area or assign to a field symbol

• Use parallel cursor technique for nested loops.

• Use the TRANSPORTING clause with READ and MODIFY wherever possible to tranport only the fields necessary

• Use TRANSPORTING No FIELDS clause when checking only for existence of a record

• Read by INDEX is the fastest access option for a single READ. Use standard table if you are accessing mainly by index. Consider this where possible but use caution as it does not apply to all programming situations.

• Specify full key on a table read whenever possible. Use ‘WITH TABLE KEY’ clause when full key is specified

• Internal Tables should be passed to FORMS with the "USING" clause. The "TABLES" clause is considered obsolete.

• Internal tables should be passed to FORMS by Reference for performance reasons

i.e. do not use USING Value(..)

• Do not use Occurs 0 or With Header Line unless it is a SAP function that requires it.

• Hashed tables are a good performance approach over standard tables whenever random record accesses are required for a large internal table using the fully qualified key.

• When sorting internal tables, always use "SORT BY Key1...n", never just "SORT" on it's own

• Standard Tables require a Sort by, Delete adjacent Duplicates, and READ itab with KEY...Binary Search

• Keep "SORT itab BY" statement as close as possible to the READ itab with KEY...Binary Search.

• Delete Adjacent Duplicates should always be explicit by using the COMPARING clause, even if there is only one field in the itab

• Standard Tables should be sorted by sorting keys to take advantage of Binary Search. However, if you sort by one key and Read with a different set, you could miss data

Hope these points will be useful to you avoid the performance issues.

<b>Reward with points if helpful.</b>

<b>Regards,</b>

Vijay

[Former Member]

hI

SEE THIS

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.

Note: It is suggestible to make at least on field mandatory in Selection-Screen as mandatory fields restrict the data selection and hence increasing the performance.

Points # 1/2

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

2. Select all the records in a single shot using into table clause of select statement rather than to use Append statements.

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.

4. For testing existence , use Select.. Up to 1 rows statement instead of a Select-Endselect-loop with an Exit.

5. Use Select Single if all primary key fields are supplied in the Where condition .

Point # 1

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.

Point # 2

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'.

Point # 3

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.

Point # 4

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.

Point # 5

If all primary key fields are supplied in the Where condition you can even use Select Single.

Select Single requires one communication with the database system, whereas Select-Endselect needs two.

Select Statements contd.. SQL Interface

1. Use column updates instead of single-row updates

to update your database tables.

2. For all frequently used Select statements, try to use an index.

3. Using buffered tables improves the performance considerably.

Point # 1

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.

Point # 2

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.

Point # 3

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 contd… 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 contd…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 contd… Select Over more than one Internal table

1. Its better to use a views instead of nested Select statements.

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.

3. Instead of using nested Select loops it is often better to use subqueries.

Point # 1

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

Point # 2

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.

Point # 3

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.

<b>REWARD IF USEFULL</b>

[Former Member]

I have started a series of blogs on performance topics.

The most dramatic performance problems are of course selects if there are not indexes supporting the select,

especially with joins the runtime can increase dramatically. Run the SQL Trace, and check the column ‘minimal time

per record’, if this is larger than 10000 mircoseconds, then you check the statement carefully.

Read on SQL trace:

/people/siegfried.boes/blog/2007/09/05/the-sql-trace-st05-150-quick-and-easy

The other dramatic problem are nested loops on internal tables, where the access to the inner table is slow, this

can lead to programs which be become over-proportionally the larger the processed objects are:

More details on nonlinearity can be found here

/people/siegfried.boes/blog/2007/02/12/performance-problems-caused-by-nonlinear-coding

Measurements on internal tables which explain which reads should be taken can be found here:

/people/siegfried.boes/blog/2007/09/12/runtimes-of-reads-and-loops-on-internal-tables

I will add more topics as soon as I find the time.

Siegfried

[Former Member]

Hi

these are the performance cases where data base is not involved

reward if usefull

<b>Internal Tables</b>

1)Table operations should be done using explicit work areas rather than via header lines.

2)Always try to use binary search instead of linear search. But don’t forget to sort your internal table before that.

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.

6)Modifying selected components using “ MODIFY itab …TRANSPORTING f1 f2.. “ accelerates the task of updating a line of an internal table.

7. Accessing the table entries directly in a "LOOP ... ASSIGNING ..." accelerates the task of updating a set of lines of an internal table considerably

8. If collect semantics is required, it is always better to use to COLLECT rather than READ BINARY and then ADD.

9. "APPEND LINES OF itab1 TO itab2" accelerates the task of appending a table to another table considerably as compared to “ LOOP-APPEND-ENDLOOP.”

10. “DELETE ADJACENT DUPLICATES“ accelerates the task of deleting duplicate entries considerably as compared to “ READ-LOOP-DELETE-ENDLOOP”.

11. "DELETE itab FROM ... TO ..." accelerates the task of deleting a sequence of lines considerably as compared to “ DO -DELETE-ENDDO”.

12. Copying internal tables by using “ITAB2[ ] = ITAB1[ ]” as compared to “LOOP-APPEND-ENDLOOP”.

13. Specify the sort key as restrictively as possible to run the program faster.

<b>Point # 2</b>

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 ) ).

<b>Point # 3</b>

READ TABLE ITAB INTO WA WITH KEY K = 'X'. IS FASTER THAN USING

READ TABLE ITAB INTO WA WITH KEY (NAME) = 'X'.

<b>Point # 5</b>

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.

<b>Point # 6</b>

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.

<b>Point # 7</b>

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.

<b>Point # 8</b>

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)) .

<b>Point # 9</b>

APPEND LINES OF ITAB1 TO ITAB2.

This is more optimized as compared to

LOOP AT ITAB1 INTO WA.

APPEND WA TO ITAB2.

ENDLOOP.

<b>Point # 10</b>

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.

<b>Point # 11</b>

DELETE ITAB FROM 450 TO 550.

This is much more optimized as compared to

DO 101 TIMES.

DELETE ITAB INDEX 450.

ENDDO.

<b>Point # 12</b>

ITAB2[] = ITAB1[].

This is much more optimized as compared to

REFRESH ITAB2.

LOOP AT ITAB1 INTO WA.

APPEND WA TO ITAB2.

ENDLOOP.

<b>Point # 13</b>“SORT ITAB BY K.” makes the program runs faster as compared to “SORT ITAB.”

<b>Internal Tables contd… Hashed and Sorted tables</b>

For single read access hashed tables are more optimized as compared to sorted tables.

For partial sequential access sorted tables are more optimized as compared to hashed tables

Hashed And Sorted Tables

<b>Point # 1</b>

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.

<b>Point # 2</b>

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.

<b>Typing</b>

Typed Parameters: Specifying the type for formal parameters in the source code, optimizes the code more thoroughly

Typed Field-Symbols: Specifying the type for formal parameters in the source code, optimizes the code more thoroughly

<b>Typing</b>

<b>Point # 1</b>

Consider the following case

PERFORM UP1 USING 10 M6-DIMID M6-ZAEHL M6-ISOCODE.

FORM UP1 USING

REPEAT TYPE I

DIMID LIKE T006-DIMID

ZAEHL LIKE T006-ZAEHL

ISOCODE LIKE T006-ISOCODE

…………………..

…………………..

ENDFORM.

This works faster as compared to

FORM UP1 USING

REPEAT

DIMID

ZAEHL

ISOCODE

……………………..

……………………..

ENDFORM

If, Case, While..

<b>Point # 1</b>

DATA C TYPE C.

CASE C.

WHEN 'A'. WRITE '1'.

WHEN 'B'. WRITE '2'.

ENDCASE.

This is faster as compared to

DATA C TYPE C.

IF C = 'A'. WRITE '1'.

ELSEIF C = 'B'. WRITE '2'.

ENDIF.

<b>Point # 2</b>

DATA C TYPE C. DATA I TYPE I.

I = 0.

WHILE C = SPACE.

ADD 1 TO I.

IF I GT 10. C = 'X'. ENDIF.

ENDWHILE.

The above code is much faster as compared to

DATA C TYPE C. DATA I TYPE I.

I = 0.

DO.

IF C NE SPACE. EXIT. ENDIF.

ADD 1 TO I.

IF I GT 10. C = 'X'. ENDIF.

ENDDO.

<b>Control Statements If, Case, While..</b>

CASE statements are clearer and a little faster than IF-constructions

Use of WHILE instead of a DO+EXIT-construction, is faster to execute.

<b>Field Conversion</b>

Use fields of type I instead of P for typical integral variables like indices.

Use numeric literals or named constants with a number type instead of character strings if you are dealing with type-I or integral type-P fields.

Use properly typed constants instead of literals.

Use number types for arithmetic. Use type-N fields only for pure digit strings that are not intended for calculations e.g, Telephone nos etc.

Don't mix types unless absolutely necessary.

String operations can be made faster by specifying length of character field rather than defining as string.

<b>Point # 1</b>

DATA I TYPE I VALUE 1.

READ TABLE TAB INTO TAB_WA INDEX I.

This is faster as compared to

DATA P TYPE P VALUE 1.

READ TABLE TAB INTO TAB_WA INDEX P.

<b>Point # 2</b>

SY-SUBRC = 0.

CASE SY-SUBRC.

WHEN 1.

WHEN 2.

WHEN 3.

WHEN 4.

ENDCASE.

This is much faster as compared to

MOVE SPACE TO SY-SUBRC.

CASE SY-SUBRC.

WHEN ‘1’.

WHEN ‘2’.

WHEN ‘3’.

WHEN ‘4’.

ENDCASE.

<b>Point # 3</b>

CONSTANTS:

PI TYPE F VALUE '3.1415926535897932'.

DATA:

FLOAT TYPE F.

FLOAT = PI.

The above code is faster as compared to below mentioned code

DATA:

FLOAT TYPE F.

FLOAT = '3.1415926535897932'.

<b>Point # 4</b>

DATA:

P1 TYPE P VALUE '123456789012345',

P2 TYPE P VALUE '543210987654321',

P3 TYPE P.

P3 = P1 + P2.

The above code is faster as compared to below mentioned code

DATA:

N1(15) TYPE N VALUE '123456789012345',

N2(15) TYPE N VALUE '543210987654321',

N3(15) TYPE N.

N3 = N1 + N2.

<b>Point # 5</b>

DATA: F1 TYPE F VALUE 2,

F2 TYPE F VALUE '3.14',

F3 TYPE F.

F3 = F1 * F2.

The above code is faster as compared to below mentioned code

DATA: F1 TYPE I VALUE 2,

F2 TYPE P DECIMALS 2 VALUE '3.14',

F3 TYPE F.

F3 = F1 * F2.

<b>Point # 6</b>

*data c1(200) type c.

*data c2(200) type c.

*data c3(400) type c.

c1 = 'mysap'.

c2 = '.com'.

concatenate c1 c2 into c3.

The above code is faster as compared to below mentioned code

*data string1 type string.

*data string2 type string.

*data string3 type string.

string1 = 'mysap'.

string2 = '.com'.

concatenate string1 string2 into string3.

<b>Reward if usefull</b>

[Former Member]

Hi Kondal,

All said and done it is not always related to the select query that the performance comes into play.

<b>The best part to tune the performance is to relate the dB table to the secondary index.</b>

The primary index is available and the fetching depends on this. We can go ahead to create the secondary index to fetch more relatively and use this as a powerful tool in tuning the perfomance of Select queries.

This should be a valuable suggestion.

Reward points if useful.

Thanks,

Tej..