Performance tuning

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)

Some steps that might make FOR ALL ENTRIES more efficient:

• Removing duplicates from the the driver table

• Sorting the driver table

• If possible, convert the data in the driver table to ranges so a BETWEEN statement is used instead of and OR statement:
  FOR ALL ENTRIES IN i_tab
    WHERE mykey >= i_tab-low and
          mykey <= i_tab-high.

Nested selects

The plus:

• Small amount of data

• Mixing processing and reading of data

• Easy to code - and understand

The minus:

• Large amount of data

• when mixed processing isn’t needed

• Performance killer no. 1
  

Select using JOINS

The plus

• Very large amount of data

• Similar to Nested selects - when the accesses are planned by the programmer

• In some cases the fastest

• Not so memory critical

The minus

• Very difficult to program/understand

• Mixing processing and reading of data not possible

Use the selection criteria

SELECT * FROM SBOOK.                    
  CHECK: SBOOK-CARRID = 'LH' AND        
                  SBOOK-CONNID = '0400'.         
ENDSELECT.                              

SELECT * FROM SBOOK                      
  WHERE CARRID = 'LH' AND                
        CONNID = '0400'.                 
ENDSELECT.                               

Use the aggregated functions

C4A = '000'.               
SELECT * FROM T100         
  WHERE SPRSL = 'D' AND    
        ARBGB = '00'.      
  CHECK: T100-MSGNR > C4A. 
  C4A = T100-MSGNR.        
ENDSELECT.                 

SELECT MAX( MSGNR ) FROM T100 INTO C4A  
 WHERE SPRSL = 'D' AND                 
       ARBGB = '00'.                   

Select with view

SELECT * FROM DD01L                     
  WHERE DOMNAME LIKE 'CHAR%'            
        AND AS4LOCAL = 'A'.             
  SELECT SINGLE * FROM DD01T            
    WHERE   DOMNAME    = DD01L-DOMNAME  
        AND AS4LOCAL   = 'A'            
        AND AS4VERS    = DD01L-AS4VERS  
        AND DDLANGUAGE = SY-LANGU.      
ENDSELECT.                              

SELECT * FROM DD01V                     
 WHERE DOMNAME LIKE 'CHAR%'            
       AND DDLANGUAGE = SY-LANGU.      
ENDSELECT.                              

Select with index support

SELECT * FROM T100             
 WHERE     ARBGB = '00'       
       AND MSGNR = '999'.     
ENDSELECT.                     

SELECT * FROM T002.              
  SELECT * FROM T100             
    WHERE     SPRSL = T002-SPRAS 
          AND ARBGB = '00'       
          AND MSGNR = '999'.     
  ENDSELECT.                     
ENDSELECT.                       

Select … Into table

REFRESH X006.                  
SELECT * FROM T006 INTO X006.  
  APPEND X006.                 
ENDSELECT

SELECT * FROM T006 INTO TABLE X006.

Select with selection list

SELECT * FROM DD01L               
  WHERE DOMNAME LIKE 'CHAR%'      
        AND AS4LOCAL = 'A'.       
ENDSELECT

SELECT DOMNAME FROM DD01L     
 INTO DD01L-DOMNAME          
 WHERE DOMNAME LIKE 'CHAR%'  
       AND AS4LOCAL = 'A'.   
ENDSELECT

Key access to multiple lines

LOOP AT TAB.           
 CHECK TAB-K = KVAL.  
 " ...                
ENDLOOP.               

LOOP AT TAB WHERE K = KVAL.      
  " ...                          
ENDLOOP.                         

Copying internal tables

REFRESH TAB_DEST.               
LOOP AT TAB_SRC INTO TAB_DEST.  
  APPEND TAB_DEST.              
ENDLOOP.                        

TAB_DEST[] = TAB_SRC[].

Modifying a set of lines

LOOP AT TAB.              
  IF TAB-FLAG IS INITIAL. 
    TAB-FLAG = 'X'.       
  ENDIF.                  
  MODIFY TAB.             
ENDLOOP.                  

TAB-FLAG = 'X'.                   
MODIFY TAB TRANSPORTING FLAG      
           WHERE FLAG IS INITIAL. 

Deleting a sequence of lines

DO 101 TIMES.                
  DELETE TAB_DEST INDEX 450. 
ENDDO.                       

DELETE TAB_DEST FROM 450 TO 550.

Linear search vs. binary

READ TABLE TAB WITH KEY K = 'X'.

READ TABLE TAB WITH KEY K = 'X' BINARY SEARCH.

Comparison of internal tables

DESCRIBE TABLE: TAB1 LINES L1,       
                TAB2 LINES L2.       
                                     
IF L1 <> L2.                         
  TAB_DIFFERENT = 'X'.               
ELSE.                                
  TAB_DIFFERENT = SPACE.             
  LOOP AT TAB1.                      
    READ TABLE TAB2 INDEX SY-TABIX.  
    IF TAB1 <> TAB2.                 
      TAB_DIFFERENT = 'X'. EXIT.     
    ENDIF.                           
  ENDLOOP.                           
ENDIF.                               
                                     
IF TAB_DIFFERENT = SPACE.            
  " ...                              
ENDIF.                               

IF TAB1[] = TAB2[].   
 " ...               
ENDIF.                

Modify selected components

LOOP AT TAB.            
 TAB-DATE = SY-DATUM.  
 MODIFY TAB.           
ENDLOOP.                

WA-DATE = SY-DATUM.                     
LOOP AT TAB.                            
 MODIFY TAB FROM WA TRANSPORTING DATE. 
ENDLOOP.                                

Appending two internal tables

LOOP AT TAB_SRC.               
  APPEND TAB_SRC TO TAB_DEST.  
ENDLOOP

APPEND LINES OF TAB_SRC TO TAB_DEST.

Deleting a set of lines

LOOP AT TAB_DEST WHERE K = KVAL.  
  DELETE TAB_DEST.                
ENDLOOP

DELETE TAB_DEST WHERE K = KVAL.

Tools available in SAP to pin-point a performance problem

• The runtime analysis (SE30)

• SQL Trace (ST05)

• Tips and Tricks tool 

• The performance database

Optimizing the load of the database

Using table buffering

Using buffered tables improves the performance considerably. Note that in some cases a stament can not be used with a buffered table, so when using these staments the buffer will be bypassed. These staments are:

• Select DISTINCT

• ORDER BY / GROUP BY / HAVING clause

• Any WHERE clasuse that contains a subquery or IS NULL expression

• JOIN s

• A SELECT... FOR UPDATE

If you wnat to explicitly bypass the bufer, use the BYPASS BUFFER addition to the SELECR clause.

Use the ABAP SORT Clause Instead of ORDER BY

The ORDER BY clause is executed on the database server while the ABAP SORT statement is executed on the application server. The datbase server will usually be the bottleneck, so sometimes it is better to move thje sort from the datsbase server to the application server.

If you are not sorting by the primary key ( E.g. using the ORDER BY PRIMARY key statement) but are sorting by another key, it could be better to use the ABAP SORT stament to sort the data in an internal table. Note however that for very large result sets it might not be a feasible solution and you would want to let the datbase server sort it.

Avoid ther SELECT DISTINCT Statement

As with the ORDER BY clause it could be better to avoid using SELECT DISTINCT, if some of the fields are not part of an index. Instead use ABAP SORT + DELETE ADJACENT DUPLICATES on an internal table, to delete duplciate rows.

TIPS & TRICKS FOR OPTIMIZATION

ABAP/4 Development Code Efficiency Guidelines

ABAP/4 (Advanced Business Application Programming 4GL) language is an "event-driven", "top-down", well-structured and powerful programming language.  The ABAP/4 processor controls the execution of an event.  Because the ABAP/4 language incorporates many "event" keywords and these keywords need not be in any specific order in the code, it is wise to implement in-house ABAP/4 coding standards.

SAP-recommended customer-specific ABAP/4 development guidelines can be found in the SAP-documentation.

This page contains some general guidelines for efficient ABAP/4 Program Development that should be considered to improve the systems performance on the following areas:-

Physical I/O - data must be read from and written into I/O devices. This can be a potential bottle neck. A well configured system always runs 'I/O-bound' - the performance of the I/O dictates the overall performance.

Memory consumption of the database resources eg. buffers, etc.

CPU consumption on the database and application servers

Network communication - not critical for little data volumes, becomes a bottle neck when large volumes are transferred.

Policies and procedures can also be put into place so that every SAP-customer development object is thoroughly reviewed (quality – program correctness as well as code-efficiency) prior to promoting the object to the SAP-production system.   Information on the SAP R/3 ABAP/4 Development Workbench programming tools and its features can be found on the SAP Public Web-Server.

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CLASSIC GOOD 4GL PROGRAMMING CODE-PRACTICES GUIDELINES

Avoid dead-code

Remove unnecessary code and redundant processing

Spend time documenting and adopt good change control practices

Spend adequate time anayzing business requirements, process flows, data-structures and data-model

Quality assurance is key: plan and execute a good test plan and testing methodology

Experience counts

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SELECT * FROM <TABLE>
 CHECK:  <CONDITION>
ENDSELECT

  vs.

SELECT * FROM <TABLE>
 WHERE <CONDITION>
ENDSELECT
 

In order to keep the amount of data which is relevant to the query the hit set small, avoid using SELECT+CHECK statements wherever possible. As a general rule of thumb, always specify all known conditions in the WHERE clause (if possible). If there is no WHERE clause the DBMS has no chance to make optimizations.  Always specify your conditions in the Where-clause instead of checking them yourself with check-statements.  The database system can also potentially make use a database index (if possible) for greater efficiency resulting in less load on the database server and considerably less load on the network traffic as well.

Also, it is important to use EQ (=) in the WHERE clause wherever possible, and analyze the SQL-statement for the optimum path the database optimizer will utilize via SQL-trace when necessary.

Also, ensure careful usage of  "OR", "NOT"  and value range tables (INTTAB) that are used inappropriately in Open SQL statements.

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SELECT *

 vs.

SELECT SINGLE *

If you are interested in exactly one row of a database table or view, use the SELECT SINGLE statement instead of a SELECT * statement.  SELECT SINGLE requires one communication with the database system whereas SELECT * requires two.

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SELECT * FROM <TABLE>  INTO <INT-TAB>
 APPEND <INT-TAB>
ENDSELECT

 vs.

SELECT * FROM <TABLE> INTO TABLE <INT-TAB>
 

It is usually faster to use the INTO TABLE version of a SELECT statement than to use APPEND statements

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SELECT ... WHERE + CHECK

 vs.

SELECT using aggregate function

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 within the program.   The RDBMS is responsible for aggregated computations instead of transferring large amount of data to the application. Overall Network, Application-server and Database load is also considerably less.

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SELECT INTO TABLE <INT-TAB> + LOOP AT T
  …………
SELECT * FROM <TABLE> INTO TABLE <INT-TAB>.
LOOP AT <INT-TAB>.
ENDLOOP.

 vs.

SELECT * FROM <TABLE>
    ……….
ENDSELECT

If you process your data only once, use a SELECT-ENDSELECT loop instead of collecting data in an internal table with SELECT ... INTO TABLE.  Internal table handling takes up much more space

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Nested SELECT statements:
SELECT * FROM <TABLE-A>
     SELECT * FROM <TABLE-B>
     ……..
     ENDSELECT.
ENDSELECT

 vs.

Select with view
 SELECT * FROM <VIEW>
 ENDSELECT

To process a join, use a view wherever possible instead of nested SELECT statements.
Using nested selects is a technique with low performance. The inner select statement is executed several times which might be an overhead. In addition, fewer data must be transferred if another technique would be used eg. join implemented as a view in ABAP/4 Repository.

· SELECT ... FORM ALL ENTRIES
· Explicit cursor handling (for more information, goto Transaction SE30 – Tips & Tricks)

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Nested select:
SELECT * FROM pers WHERE condition.
         SELECT * FROM persproj WHERE person = pers-persnr.
               ... process ...
         ENDSELECT.
ENDSELECT.

 vs.

SELECT persnr FROM pers INTO TABLE ipers WHERE cond.  ……….
SELECT * FROM persproj FOR ALL ENTRIES IN ipers
      WHERE person = ipers-persnr
………... process .……………
ENDSELECT.

In the lower version the new Open SQL statement FOR ALL ENTRIES is used. Prior to the call, all interesting records from 'pers' are read into an internal table. The second SELECT statement results in a call looking like this (ipers containing: P01, P02, P03):
(SELECT * FROM persproj WHERE person = 'P01')
UNION
(SELECT * FROM persproj WHERE person = 'P02')
UNION
(SELECT * FROM persproj WHERE person = 'P03')

In case of large statements, the R/3's database interface divides the statement into several parts and recombines the resulting set to one.  The advantage here is that the number of transfers is minimized and there is minimal restrictions due to the statement size (compare with range tables).

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SELECT * FROM <TABLE>

vs.

SELECT <column(s)> FROM <TABLE>
 

Use a select list or a view instead of SELECT *, if you are only interested in specific columns of the table. If only certain fields are needed then only those fields should be read from the database.  Similarly, the number of columns can also be restricted by using a view defined in ABAP/4 Dictionary. Overall database and network load is considerably less.

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SELECT without table buffering support

 vs.

SELECT with table buffering support

For all frequently used, read-only(few updates) tables, do attempt to use SAP-buffering for eimproved performance response times. This would reduce the overall Database activity and Network traffic.

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Single-line inserts
LOOP AT <INT-TAB>
 INSERT INTO <TABLE> VALUES <INT-TAB>
ENDLOOP

 vs.

Array inserts

Whenever possible, use array operations instead of single-row operations to modify the database tables.

Frequent communication between the application program and database system produces considerable overhead.

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Single-line updates
 SELECT * FROM <TABLE>
  <COLUMN-UPDATE STATEMENT>
  UPDATE <TABLE>
 ENDSELECT

 vs.
 

Column updates
 UPDATE <TABLE> SET <COLUMN-UPDATE STATEMENT>

Wherever possible, use column updates instead of single row updates to update your database tables

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DO....ENDDO loop with Field-Symbol

 vs.

Using CA operator

Use the special operators CO, CA, CS instead of programming the operations yourself
If ABAP/4 statements are executed per character on long strings, CPU consumprion can rise substantially

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Use of a CONCATENATE function module

 vs.

Use of a CONCATENATE statement

Some function modules for string manipulation have become obsolete, and should be replaced by ABAP statements or functions

STRING_CONCATENATE...   ---> CONCATENATE
STRING_SPLIT...  ---> SPLIT
STRING_LENGTH...  ---> strlen()
STRING_CENTER...  ---> WRITE..TO. ..CENTERED
STRING_MOVE_RIGHT  ---> WRITE...TO...RIGHT-JUSTIFIED

--------------------------------------------------------------------------------

Moving with offset

 vs.

Use of the CONCATENATE statement

Use the CONCATENATE statement instead of programming a string concatenation of your own

--------------------------------------------------------------------------------

Use of SEARCH and MOVE with offset

 vs.
 

Use of SPLIT statement
 

Use the SPLIT statement instead of programming a string split yourself

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Shifting by SY-FDPOS places

 vs

Using SHIFT...LEFT DELETING LEADING...

If you want ot delete the leading spaces in a string use the ABAP/4 statements SHIFT...LEFT DELETING LEADING...  Other constructions (with CN and SHIFT... BY SY-FDPOS PLACES, with CONDENSE if possible, with CN and ASSIGN CLA+SY-FDPOS(LEN) ...) are not as fast

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Get a check-sum with field length

 vs

Get a check-sum with strlen ()
 

Use the strlen () function to restrict the DO loop to the relevant part of the field, eg. when determinating a check-sum