Need help in Performance tuning for function...
Hi all,
I am using the below algorithm for calculating the Luhn Alogorithm to calculate the 15th luhn digit for an IMEI (Phone Sim Card).
But the below function is taking about 6 min for 5 million records. I had 170 million records in a table want to calculate the luhn digit for all of them which might take up to 4-5 hours.Please help me performance tuning (better way or better logic for luhn calculation) to the below function.
A wikipedia link is provided for the luhn algorithm below
Create or Replace FUNCTION AddLuhnToIMEI (LuhnPrimitive VARCHAR2)
RETURN VARCHAR2
AS
Index_no NUMBER (2) := LENGTH (LuhnPrimitive);
Multiplier NUMBER (1) := 2;
Total_Sum NUMBER (4) := 0;
Plus NUMBER (2);
ReturnLuhn VARCHAR2 (25);
BEGIN
WHILE Index_no >= 1
LOOP
Plus := Multiplier * (TO_NUMBER (SUBSTR (LuhnPrimitive, Index_no, 1)));
Multiplier := (3 - Multiplier);
Total_Sum := Total_Sum + TO_NUMBER (TRUNC ( (Plus / 10))) + MOD (Plus, 10);
Index_no := Index_no - 1;
END LOOP;
ReturnLuhn := LuhnPrimitive || CASE
WHEN MOD (Total_Sum, 10) = 0 THEN '0'
ELSE TO_CHAR (10 - MOD (Total_Sum, 10))
END;
RETURN ReturnLuhn;
EXCEPTION
WHEN OTHERS
THEN
RETURN (LuhnPrimitive);
END AddLuhnToIMEI;
http://en.wikipedia.org/wiki/Luhn_algorithmAny sort of help is much appreciated....
Thanks
Rede
There is a not needed to_number function in it. TRUNC will already return a number.
Also the MOD function can be avoided at some steps. Since multiplying by 2 will never be higher then 18 you can speed up the calculation with this.
create or replace
FUNCTION AddLuhnToIMEI_fast (LuhnPrimitive VARCHAR2)
RETURN VARCHAR2
AS
Index_no pls_Integer;
Multiplier pls_Integer := 2;
Total_Sum pls_Integer := 0;
Plus pls_Integer;
rest pls_integer;
ReturnLuhn VARCHAR2 (25);
BEGIN
for Index_no in reverse 1..LENGTH (LuhnPrimitive) LOOP
Plus := Multiplier * TO_NUMBER (SUBSTR (LuhnPrimitive, Index_no, 1));
Multiplier := 3 - Multiplier;
if Plus < 10 then
Total_Sum := Total_Sum + Plus ;
else
Total_Sum := Total_Sum + Plus - 9;
end if;
END LOOP;
rest := MOD (Total_Sum, 10);
ReturnLuhn := LuhnPrimitive || CASE WHEN rest = 0 THEN '0' ELSE TO_CHAR (10 - rest) END;
RETURN ReturnLuhn;
END AddLuhnToIMEI_fast;
/My tests gave an improvement for about 40%.
The next step to try could be to use native complilation on this function. This can give an additional big boost.
Edited by: Sven W. on Mar 9, 2011 8:11 PM
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Select Statements SQL Interface
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Select Statements Aggregate Functions
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Select Statements For All Entries
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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
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Select Statements Select Over more than one Internal table
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AND DDLANGUAGE = SY-LANGU.
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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 dont 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.
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