Performance tuning for Data Selection Statement
2010-11-30 23:06
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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 ofentries 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 plusVery 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 SELECT 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.相关文章推荐
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