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Former Member
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1.How would u go about improving the performance of a Program, which selects data from MSEG & MKPF?

2. How does System work in case of an Interactive Report?

3. What is LUW?

4. What is First event triggered in program?

5. What are various Joins? What is right outer join?

6. What is Performance tuning?

7. Define Documentation.

8. Brief about Testing of programs

1 REPLY 1

Former Member
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Hi

<b>1.How would u go about improving the performance of a Program, which selects data from MSEG & MKPF?</b>

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.

<b>2. How does System work in case of an Interactive Report?</b>

IT WILL WAIT FOR THE USER ACTION , DEPENDING UP ON THE ACTION THAT WILL TRIGGER SOME EVENTS

<b>3. What is LUW?</b>

A Logical Unit of Work (LUW or database transaction) is an inseparable sequence of database operations which must be executed either in its entirety or not at all. For the database system, it thus constitutes a unit.

LUWs help to guarantee database integrity. When an LUW has been successfully concluded, the database is once again in a correct state. If, however, an error occurs within an LUW, all database changes made since the beginning of the LUW are canceled and the database is then in the same state as before the LUW started.

An LUW begins

o each time you start a transaction

o when the database changes of the previous LUW have been confirmed (database commit) or

o when the database changes of the previous LUW have been cancelled (database rollback)

An LUW ends

o when the database changes have been confirmed (database commit) or

o when the database changes have been canceled (database rollback)

SAP memory and ABAP memoryUsing SAP memory. User-specific memory retained for the duration of the session. Can only be used for simple field values.

Using ABAP memory. Can be used to transfer data between internal modi. Can be used to transfer any ABAP/4 variables ( Fields, strings, internal tables, complex objects)

SAP memoryYou use the SPA/GPA parameters to pass data. These paramters are saved globally in memory. The paramters are indetified by a three-character code.

In dialog programs you can SET and GET these parameters in the attribute window of the screen field, by marking the SET and GET fields and put the name of the parameter in the ParameterId field.

In a program ( Dialog or Report ) you can use the GET PARAMETER and SET PARAMETER statements:

set parameter id 'RV1' field <fieldname>

get parameter id 'RV1' field <fieldname>

<b>4. What is First event triggered in program?</b>

INITIALIZATION it will trigger when ever you execute the program

<b>5. What are various Joins? What is right outer join?</b>

go through these links

http://help.sap.com/saphelp_46c/helpdata/EN/50/a71ec8f65911d296390000e82de14a/content.htm

http://help.sap.com/saphelp_nw04/helpdata/en/fc/eb39c4358411d1829f0000e829fbfe/content.htm

<b>6. What is Performance tuning?</b>

Tools for Performance Analysis

Run time analysis transaction SE30

SQL Trace transaction ST05

Extended Program Check (SLIN)

Code Inspector ( SCI)

Run time analysis transaction SE30 :This transaction gives all the analysis of an ABAP program with respect to the database and the non-database processing.

SQL Trace transaction ST05: The trace list has many lines that are not related to the SELECT statement in the ABAP program. This is because the execution of any ABAP program requires additional administrative SQL calls. To restrict the list output, use the filter introducing the trace list.

The trace list contains different SQL statements simultaneously related to the one SELECT statement in the ABAP program. This is because the R/3 Database Interface - a sophisticated component of the R/3 Application Server - maps every Open SQL statement to one or a series of physical database calls and brings it to execution. This mapping, crucial to R/3s performance, depends on the particular call and database system. For example, the SELECT-ENDSELECT loop on a particular database table of the ABAP program would be mapped to a sequence PREPARE-OPEN-FETCH of physical calls in an Oracle environment.

The WHERE clause in the trace list's SQL statement is different from the WHERE clause in the ABAP statement. This is because in an R/3 system, a client is a self-contained unit with separate master records and its own set of table data (in commercial, organizational, and technical terms). With ABAP, every Open SQL statement automatically executes within the correct client environment. For this reason, a condition with the actual client code is added to every WHERE clause if a client field is a component of the searched table.

To see a statement's execution plan, just position the cursor on the PREPARE statement and choose Explain SQL. A detailed explanation of the execution plan depends on the database system in use.

Extended Program Check

This can be called in through transaction SE38 or through transaction SLIN. This indicates possible problems that may cause performance problems.

Code Inspector (SCI)

You can call the Code Inspector from the ABAP Editor (SE38), the Function Builder (SE37), the Class Builder (SE24), or as a separate transaction (SCI).

The Code Inspector indicates possible problems. However, note that, especially with performance issues: There is no rule without exception. If a program passes an inspection, it does not necessarily mean that this program will have no performance problems.

Run time analysis transaction SE30

In Transaction SE30, fill in the transaction name or the program name which needs to be analyzed for performance tuning.

For our case, let this be “ZABAP_PERF_TUNING”

After giving the required inputs to the program, execute it. After the final output list has been displayed, PRESS the “BACK” button.

On the original SE30 screen, now click on “ANALYZE” button.

The percentage across each of the areas ABAP/ Database/System shows the percentage of total time used for those areas and load on these areas while running the program . The lesser the database load faster the program runs.

SQL Trace – ST05

Starting the Trace:

To analyze a trace file, do the following:

...

Choose the menu path Test &#61614; Performance Trace in the ABAP Workbench or go to Transaction ST05. The initial screen of the test tool appears. In the lower part of the screen, the status of the Performance Trace is displayed. This provides you with information as to whether any of the Performance Traces are switched on and the users for which they are enabled. It also tells you which user has switched the trace on.

Using the selection buttons provided, set which trace functions you wish to have switched on (SWL trace, enqueue trace, RFC trace, table buffer trace).

If you want to switch on the trace under your user name, choose Trace on. If you want to pass on values for one or several filter criteria, choose Trace with Filter. Typical filter criteria are: the name of the user, transaction name, process name, and program name.

Now run the program to be analyzed.

Stopping the Trace:

To deactivate the trace:

...

Choose Test &#61614;Performance Trace in the ABAP Workbench. The initial screen of the test tool appears. It contains a status line displaying the traces that are active, the users for whom they are active, and the user who activated them.

Select the trace functions that you want to switch off.

Choose Deactivate Trace. If you started the trace yourself, you can now switch it off immediately. If the performance trace was started by a different user, a confirmation prompt appears before deactivation-

Analyzing a Sample trace data:

PREPARE: Prepares the OPEN statement for use and determines the access method.

OPEN: Opens the cursor and specifies the selection result by filling the selection fields with concrete values.

FETCH: Moves the cursor through the dataset created by the OPEN operation. The array size displayed beside the fetch data means that the system can transfer a maximum package size of 392 records at one time into the buffered area.

7. Define Documentation.

8. Brief about Testing of programs