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 e.g. 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 analyzing 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
CHECK: ENDSELECT
vs.
SELECT * FROM WHERE 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 fewer loads 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 INTO APPEND ENDSELECT
vs.
SELECT * FROM INTO TABLE
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 + LOOP AT T ………… SELECT * FROM INTO TABLE . LOOP AT . ENDLOOP.
vs.
SELECT * FROM ………. 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 SELECT * FROM …….. ENDSELECT. ENDSELECT
vs.
Select with view SELECT * FROM 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 e.g. 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
vs.
SELECT FROM
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 improved performance response times. This would reduce the overall Database activity and Network traffic.
Single-line inserts LOOP AT INSERT INTO VALUES 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 UPDATE ENDSELECT
vs.
!Column updates UPDATE SET
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 consumption 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 to 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
Quick Note on Design of secondary database indexes
First it must be stated that table design is a more logical work while index design is rather technical. In table design it might make sense to place certain fields (client, company code, ...) in the beginning. In index design, this is not advisable. Very important for an index is that it contains very selective fields in the beginning. Those are fields like object numbers. Not selective are client, company code, ...
Indexes should be small (few fields). The Database optimizer can combine two or more indexes to execute a query.
Indexes of one table should be disjoint (have few common fields), in order not to confuse the optimizer which index to use.
Note that each index slows the inserts into the table down. Updates are only slowed down if indexed fields are updated. In general, heavy inserted tables should have only few indexes while heavy selected tables might have more.
Quick Note on Design of logical databases
Using logical databases is a good method to write reports. Logical databases can be optimized centrally. But ensure that the structure of the logical database fits well to your report. Otherwise the effect can be the opposite.
For more information about more SAP ABAP/4 Development code-efficiency standards, esp. on non-database related tips and tricks, please goto transaction SE30 and click on Tips & Tricks section, which served as the main source of reference for this section of this document.
