ABAP Code Optimization Methods & Techniques

For all entries
Nested selects
Select using JOINS
Use the selection
criteria

Use the aggregated
functions

Select with view
Select with index support
Select … Into table
Select with selection
list

Key access to multiple
lines

Copying internal tables
Modifying a set of lines
Deleting a sequence of
lines

Linear search vs. binary
Comparison of internal
tables

Modify selected
components

Appending two internal
tables

Deleting a set of lines
Tools available in SAP to pin-point a performance problem
Optimizing the load of the database
Other General Tips & Tricks for Optimization


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

 

The Minus

Some steps that might
make FOR ALL ENTRIES more efficient:


Nested selects

The plus:

The minus:


Select using JOINS

The plus

The minus


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


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:

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.

——————————————————————————–

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

——————————————————————————–

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.

——————————————————————————–

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.

——————————————————————————–

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

——————————————————————————–

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.

——————————————————————————–

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

——————————————————————————–

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)

——————————————————————————–

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).

——————————————————————————–

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.

——————————————————————————–

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.

——————————————————————————–

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.

——————————————————————————–

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

——————————————————————————–

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

——————————————————————————–

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

——————————————————————————–

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

——————————————————————————–

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

More References