Performance tuning in DW system

Hi All,
Now I am working for DW system. Some days ago, I was told if I want to get employee id and departmment name with some filter conditions in this dw system , I need to get employee ids and department ids first from this single table to create a new table first and then join this new one to department to get department name.
Because after filtering ,the data set will be small and makes the join faster.
I don't think this makes sense based on the rules in Oracle. But the execution time really got shorten dramatically.
So I want to ask why this happened and is it a general rule in DW system? Is the table join in DW really a high-cost operation?
best regards,
Leon

user12064076 wrote:
Hi William,
I wish the indexes would be there.
However, this is not allowed.Well, whoever is not allowing it, is preventing your database from working. A database without indexes is like a library where all the books are mixed up.
Since regular queries can be told by pre-computed tables, I only have to write a limited number of ad hoc queries.
So it's assumed that maintanance of such kind of indexes is not necessary. Always bad to assume things. Assumptions often come from people who don't know the facts.

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    Pages out/s                            211 Kb paged out/s                        1688
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    Free in swap-space  Kb            21631032 Actual swap-space   Kb            26869896
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    Utilization                              2     Queue                                    0
    Avg wait time       ms              0    Avg service time    ms                  51
    Kb transfered/s                       2   Operations/s                             0
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    rsdb/obj/large_object_size    8192       Bytes Estimation for the size of the largest object
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    |
    OTR buffer                     OTR
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    rsdb/otr/max_objects          2000             Max. number of objects in the buffer
    rsdb/otr/mutex_n              0                Number of mutexes in OTR buffer
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    rsdb/esm/large_object_size    8192       Bytes Estimation for the size of the largest object
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    Table definition buffer        TTAB
    rsdb/ntab/entrycount          20000            Max. number of table definitions buffered
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    Field description buffer       FTAB
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    Initial record buffer          IRBD
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    rsdb/ntab/entrycount          20000            Max. number / 2 of initial records buffered
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    Short nametab (NTAB)           SNTAB
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    rsdb/ntab/entrycount          20000            Max. number / 2 of entries buffered
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    Calendar buffer                CALE
    zcsa/calendar_area            500000     Byte  Size of calendar buffer
    zcsa/calendar_ids             200              Max. number of directory entries
    |
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    ztta/roll_area                3000000    Byte  Roll area per workprocess (total)
    ztta/roll_first               1          Byte  First amount of roll area used in a dialog WP
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    rdisp/PG_SHM                  8192       8 kB  Part of paging file in shared memory
    rdisp/PG_LOCAL                150        8 kB  Paging buffer per workprocess
    em/initial_size_MB            4092       MB    Initial size of extended memory
    em/blocksize_KB               4096       kB    Size of one extended memory block
    em/address_space_MB           4092       MB    Address space reserved for ext. mem. (NT only)
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    abap/heap_area_dia            2000000000 Byte  Max. heap memory for dialog workprocesses
    abap/heap_area_nondia         2000000000 Byte  Max. heap memory for non-dialog workprocesses
    abap/heap_area_total          2000000000 Byte  Max. usable heap memory
    abap/heaplimit                40000000   Byte  Workprocess restart limit of heap memory
    abap/use_paging               0                Paging for flat tables used (1) or not (0)
    |
    Statistic parameters
    rsdb/staton                   1                Statistic turned on (1) or off (0)
    rsdb/stattime                 0                Times for statistic turned on (1) or off (0)
    Regards,
    Jitender

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  • Performance Tuning Tips

    Dear All,
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    Hi
    <b>Ways of Performance Tuning</b>
    1.     Selection Criteria
    2.     Select Statements
    •     Select Queries
    •     SQL Interface
    •     Aggregate Functions
    •     For all Entries
    Select Over more than one Internal table
    <b>Selection Criteria</b>
    1.     Restrict the data to the selection criteria itself, rather than filtering it out using the ABAP code using CHECK statement. 
    2.     Select with selection list.
    <b>Points # 1/2</b>
    SELECT * FROM SBOOK INTO SBOOK_WA.
      CHECK: SBOOK_WA-CARRID = 'LH' AND
             SBOOK_WA-CONNID = '0400'.
    ENDSELECT.
    The above code can be much more optimized by the code written below which avoids CHECK, selects with selection list
    SELECT  CARRID CONNID FLDATE BOOKID FROM SBOOK INTO TABLE T_SBOOK
      WHERE SBOOK_WA-CARRID = 'LH' AND
                  SBOOK_WA-CONNID = '0400'.
    <b>Select Statements   Select Queries</b>
    1.     Avoid nested selects
    2.     Select all the records in a single shot using into table clause of select statement rather than to use Append statements.
    3.     When a base table has multiple indices, the where clause should be in the order of the index, either a primary or a secondary index.
    4.     For testing existence , use Select.. Up to 1 rows statement instead of a Select-Endselect-loop with an Exit. 
    5.     Use Select Single if all primary key fields are supplied in the Where condition .
    <b>Point # 1</b>
    SELECT * FROM EKKO INTO EKKO_WA.
      SELECT * FROM EKAN INTO EKAN_WA
          WHERE EBELN = EKKO_WA-EBELN.
      ENDSELECT.
    ENDSELECT.
    The above code can be much more optimized by the code written below.
    SELECT PF1 PF2 FF3 FF4 INTO TABLE ITAB
        FROM EKKO AS P INNER JOIN EKAN AS F
          ON PEBELN = FEBELN.
    Note: A simple SELECT loop is a single database access whose result is passed to the ABAP program line by line. Nested SELECT loops mean that the number of accesses in the inner loop is multiplied by the number of accesses in the outer loop. One should therefore use nested SELECT loops  only if the selection in the outer loop contains very few lines or the outer loop is a SELECT SINGLE statement.
    <b>Point # 2</b>
    SELECT * FROM SBOOK INTO SBOOK_WA.
      CHECK: SBOOK_WA-CARRID = 'LH' AND
             SBOOK_WA-CONNID = '0400'.
    ENDSELECT.
    The above code can be much more optimized by the code written below which avoids CHECK, selects with selection list and puts the data in one shot using into table
    SELECT  CARRID CONNID FLDATE BOOKID FROM SBOOK INTO TABLE T_SBOOK
      WHERE SBOOK_WA-CARRID = 'LH' AND
                  SBOOK_WA-CONNID = '0400'.
    <b>Point # 3</b>
    To choose an index, the optimizer checks the field names specified in the where clause and then uses an index that has the same order of the fields . In certain scenarios, it is advisable to check whether a new index can speed up the performance of a program. This will come handy in programs that access data from the finance tables.
    <b>Point # 4</b>
    SELECT * FROM SBOOK INTO SBOOK_WA
      UP TO 1 ROWS
      WHERE CARRID = 'LH'.
    ENDSELECT.
    The above code is more optimized as compared to the code mentioned below for testing existence of a record.
    SELECT * FROM SBOOK INTO SBOOK_WA
        WHERE CARRID = 'LH'.
      EXIT.
    ENDSELECT.
    <b>Point # 5</b>
    If all primary key fields are supplied in the Where condition you can even use Select Single.
    Select Single requires one communication with the database system, whereas Select-Endselect needs two.
    <b>Select Statements           contd..  SQL Interface</b>
    1.     Use column updates instead of single-row updates
    to update your database tables.
    2.     For all frequently used Select statements, try to use an index.
    3.     Using buffered tables improves the performance considerably.
    <b>Point # 1</b>
    SELECT * FROM SFLIGHT INTO SFLIGHT_WA.
      SFLIGHT_WA-SEATSOCC =
        SFLIGHT_WA-SEATSOCC - 1.
      UPDATE SFLIGHT FROM SFLIGHT_WA.
    ENDSELECT.
    The above mentioned code can be more optimized by using the following code
    UPDATE SFLIGHT
           SET SEATSOCC = SEATSOCC - 1.
    <b>Point # 2</b>
    SELECT * FROM SBOOK CLIENT SPECIFIED INTO SBOOK_WA
      WHERE CARRID = 'LH'
        AND CONNID = '0400'.
    ENDSELECT.
    The above mentioned code can be more optimized by using the following code
    SELECT * FROM SBOOK CLIENT SPECIFIED INTO SBOOK_WA
      WHERE MANDT IN ( SELECT MANDT FROM T000 )
        AND CARRID = 'LH'
        AND CONNID = '0400'.
    ENDSELECT.
    <b>Point # 3</b>
    Bypassing the buffer increases the network considerably
    SELECT SINGLE * FROM T100 INTO T100_WA
      BYPASSING BUFFER
      WHERE     SPRSL = 'D'
            AND ARBGB = '00'
            AND MSGNR = '999'.
    The above mentioned code can be more optimized by using the following code
    SELECT SINGLE * FROM T100  INTO T100_WA
      WHERE     SPRSL = 'D'
            AND ARBGB = '00'
            AND MSGNR = '999'.
    <b>Select Statements       contd…           Aggregate Functions</b>
    •     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 yourself.
    Some of the Aggregate functions allowed in SAP are  MAX, MIN, AVG, SUM, COUNT, COUNT( * )
    Consider the following extract.
                Maxno = 0.
                Select * from zflight where airln = ‘LF’ and cntry = ‘IN’.
                 Check zflight-fligh > maxno.
                 Maxno = zflight-fligh.
                Endselect.
    The  above mentioned code can be much more optimized by using the following code.
    Select max( fligh ) from zflight into maxno where airln = ‘LF’ and cntry = ‘IN’.
    <b>Select Statements    contd…For All Entries</b>
    •     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)
    <u>Points to be must considered FOR ALL ENTRIES</u> •     Check that data is present in the driver table
    •     Sorting the driver table
    •     Removing duplicates from the driver table
    Consider the following piece of extract
    Loop at int_cntry.
           Select single * from zfligh into int_fligh
    where cntry = int_cntry-cntry.
    Append int_fligh.
    Endloop.
    The above mentioned can be more optimized by using the following code.
    Sort int_cntry by cntry.
    Delete adjacent duplicates from int_cntry.
    If NOT int_cntry[] is INITIAL.
                Select * from zfligh appending table int_fligh
                For all entries in int_cntry
                Where cntry = int_cntry-cntry.
    Endif.
    <b>Select Statements    contd…  Select Over more than one Internal table</b>
    1.     Its better to use a views instead of nested Select statements.
    2.     To read data from several logically connected tables use a join instead of nested Select statements. Joins are preferred only if all the primary key are available in WHERE clause for the tables that are joined. If the primary keys are not provided in join the Joining of tables itself takes time.
    3.     Instead of using nested Select loops it is often better to use subqueries.
    <b>Point # 1</b>
    SELECT * FROM DD01L INTO DD01L_WA
      WHERE DOMNAME LIKE 'CHAR%'
            AND AS4LOCAL = 'A'.
      SELECT SINGLE * FROM DD01T INTO DD01T_WA
        WHERE   DOMNAME    = DD01L_WA-DOMNAME
            AND AS4LOCAL   = 'A'
            AND AS4VERS    = DD01L_WA-AS4VERS
            AND DDLANGUAGE = SY-LANGU.
    ENDSELECT.
    The above code can be more optimized by extracting all the data from view DD01V_WA
    SELECT * FROM DD01V INTO  DD01V_WA
      WHERE DOMNAME LIKE 'CHAR%'
            AND DDLANGUAGE = SY-LANGU.
    ENDSELECT
    <b>Point # 2</b>
    SELECT * FROM EKKO INTO EKKO_WA.
      SELECT * FROM EKAN INTO EKAN_WA
          WHERE EBELN = EKKO_WA-EBELN.
      ENDSELECT.
    ENDSELECT.
    The above code can be much more optimized by the code written below.
    SELECT PF1 PF2 FF3 FF4 INTO TABLE ITAB
        FROM EKKO AS P INNER JOIN EKAN AS F
          ON PEBELN = FEBELN.
    <b>Point # 3</b>
    SELECT * FROM SPFLI
      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.
    <b>Internal Tables</b>
    1.     Table operations should be done using explicit work areas rather than via header lines.
    2.     Always try to use binary search instead of linear search. But don’t forget to sort your internal table before that.
    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.
    6.     Modifying selected components using “ MODIFY itab …TRANSPORTING f1 f2.. “ accelerates the task of updating  a line of an internal table.
    <b>Point # 2</b>
    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 ) ).
    <b>Point # 3</b>
    READ TABLE ITAB INTO WA WITH KEY K = 'X'. IS FASTER THAN USING
    READ TABLE ITAB INTO WA WITH KEY (NAME) = 'X'.
    <b>Point # 5</b>
    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.
    <b>Point # 6</b>
    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
    8.    If collect semantics is required, it is always better to use to COLLECT rather than READ BINARY and then ADD.
    9.    "APPEND LINES OF itab1 TO itab2" accelerates the task of appending a table to another table considerably as compared to “ LOOP-APPEND-ENDLOOP.”
    10.   “DELETE ADJACENT DUPLICATES“ accelerates the task of deleting duplicate entries considerably as compared to “ READ-LOOP-DELETE-ENDLOOP”.
    11.   "DELETE itab FROM ... TO ..." accelerates the task of deleting a sequence of lines considerably as compared to “  DO -DELETE-ENDDO”.
    <b>Point # 7</b>
    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.
    <b>Point # 8</b>
    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)) .
    <b>Point # 9</b>
    APPEND LINES OF ITAB1 TO ITAB2.
    This is more optimized as compared to
    LOOP AT ITAB1 INTO WA.
      APPEND WA TO ITAB2.
    ENDLOOP.
    <b>Point # 10</b>
    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.
    <b>Point # 11</b>
    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”.
    13.   Specify the sort key as restrictively as possible to run the program faster.
    <b>Point # 12</b>
    ITAB2[] = ITAB1[].
    This is much more optimized as compared to
    REFRESH ITAB2.
    LOOP AT ITAB1 INTO WA.
      APPEND WA TO ITAB2.
    ENDLOOP.
    <b>Point # 13</b>“SORT ITAB BY K.” makes the program runs faster as compared to “SORT ITAB.”
    <b>Internal Tables         contd…
    Hashed and Sorted tables</b>
    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
    <b>Point # 1</b>
    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.
    <b>Point # 2</b>
    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.
    <b>Reward if usefull</b>

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