SCOM SQL query killing instance performance

Hi!
Since a few day, a new query running against our SCOM datawarehouse db is killing the performance of the SQL instance. The query run 1'000'000 times per hour for a total of 100'000'000 logical read per hour, and this continuously. The query is part of the
following Procedure: OperationsManagerDW.dbo.fn_BuildInstancePropertyDelta
Any idea what's wrong ?
What could trigger this new behavior ? 
Rgds
/Chris
Waiting on statement:
RETURN
   SELECT 1 AS Tag ,
      NULL AS Parent ,
      ISNULL(S1.PropertyGuid, S2.PropertyGuid) AS [Property!1!Guid] ,
      S1.PropertyValue AS [Property!1!NewValue!ELEMENT] ,
      S2.PropertyValue AS [Property!1!OldValue!ELEMENT]
   FROM
      SELECT PropertyGuid = Set1.PropertyXml.value('@Guid' ,'nvarchar(256)') ,
         PropertyValue = Set1.PropertyXml.value('.' ,'nvarchar(max)')
      FROM @PropertyXml1.nodes('Root/Property') AS Set1(PropertyXml)
      ) AS S1
   FULL JOIN
      SELECT PropertyGuid = Set1.PropertyXml.value('@Guid' ,'nvarchar(256)') ,
         PropertyValue = Set1.PropertyXml.value('.' ,'nvarchar(max)')
      FROM @PropertyXml2.nodes('Root/Property') AS Set1(PropertyXml)
      ) AS S2
   ON (S1.PropertyGuid = S2.PropertyGuid)
   WHERE (S1.PropertyValue <> S2.PropertyValue)
   OR ( (ISNULL(S1.PropertyValue, S2.PropertyValue) IS NOT NULL)
  AND ((S1.PropertyValue IS NULL)
   OR (S2.PropertyValue IS NULL)) ) FOR XML EXPLICIT

Hallo,
We open a ticket to Microsoft Support.
In the SCOM application logs, this huge SQL cpu activity correlates with an error 31553, Violation of unique key constraint.
We get the information that if the following query return some rows, it means you are hitting the same issue and you should better open a ticket to get information how to fix the problem.
select
* from ManagedEntityStage mes
inner
join ManagedEntity me on mes.ManagedEntityGuid
= me.ManagedEntityGuid
inner
join ManagedEntityProperty mep
on me.ManagedEntityRowId
= mep.ManagedEntityRowId
where mep.FromDateTime
= mes.ChangeDateTime
order
by mep.ManagedEntityRowId
Rgds
/Chris

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    Arnab

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    UPDATE 2 - i think this will do it
    Our OPS guy just told me that we sample every 10min. So immediately im thinking, perhaps i can run the query for the last 11 minutes - IF more than
    1 sample is above 90%, the server is above 90% for more than 10min.
    But, when i run this query 
    select TOP 100 Percent Path, AVG(SampleValue) AS Value, DateTime  from Perf.vPerfRaw pvpr  inner join vManagedEntity vme on pvpr.ManagedEntityRowId
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    = 'PercentMemoryUSed' AND Datetime > DATEADD(minute, -1, GETUTCDATE()) AND SampleValue >= 90 GROUP BY Path, SampleValue, DateTime ORDER BY DateTime DESC
    I get a few servers, but some have more than 1 entry in the last 1 minute.  Which means that i cant compare 2 samples.
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    then add 1 to MemoryAbove90% 

  • How to measure the performance of sql query?

    Hi Experts,
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    What are all the measures available for an sql query?
    How to identify i am writing optimal query?
    I am using Oracle 9i...
    It ll be useful for me to write efficient query....
    Thanks & Regards

    psram wrote:
    Hi Experts,
    How to measure the performance, efficiency and cpu cost of a sql query?
    What are all the measures available for an sql query?
    How to identify i am writing optimal query?
    I am using Oracle 9i... You might want to start with a feature of SQL*Plus: The AUTOTRACE (TRACEONLY) option which executes your statement, fetches all records (if there is something to fetch) and shows you some basic statistics information, which include the number of logical I/Os performed, number of sorts etc.
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    alter session set timed_statistics = true;
    select /* findme */ ... <your query here>
    SELECT
             SUBSTR(LPAD(' ',DEPTH - 1)||OPERATION||' '||OBJECT_NAME,1,40) OPERATION,
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             CARDINALITY,
             LAST_OUTPUT_ROWS,
             LAST_CR_BUFFER_GETS,
             LAST_DISK_READS,
             LAST_DISK_WRITES,
    FROM     V$SQL_PLAN_STATISTICS_ALL P,
             (SELECT *
              FROM   (SELECT   *
                      FROM     V$SQL
                      WHERE    SQL_TEXT LIKE '%findme%'
                               AND SQL_TEXT NOT LIKE '%V$SQL%'
                               AND PARSING_USER_ID = SYS_CONTEXT('USERENV','CURRENT_USERID')
                      ORDER BY LAST_LOAD_TIME DESC)
              WHERE  ROWNUM < 2) S
    WHERE    S.HASH_VALUE = P.HASH_VALUE
             AND S.CHILD_NUMBER = P.CHILD_NUMBER
    ORDER BY ID
    /Check the V$SQL_PLAN_STATISTICS_ALL view for more statistics available. In 10g there is a convenient function DBMS_XPLAN.DISPLAY_CURSOR which can show this information with a single call, but in 9i you need to do it yourself.
    Note that "statistics_level=all" adds a significant overhead to the processing, so use with care and only when required:
    http://jonathanlewis.wordpress.com/2007/11/25/gather_plan_statistics/
    http://jonathanlewis.wordpress.com/2007/04/26/heisenberg/
    Regards,
    Randolf
    Oracle related stuff blog:
    http://oracle-randolf.blogspot.com/
    SQLTools++ for Oracle (Open source Oracle GUI for Windows):
    http://www.sqltools-plusplus.org:7676/
    http://sourceforge.net/projects/sqlt-pp/

  • SQL Query Performance needed.

    Hi All,
       I am getting performance issue with my below sql query. When I fired it, It is taking 823.438 seconds, but when I ran query in, it is taking 8.578 seconds, and query after in   is taking 7.579 seconds.
    SELECT BAL.L_ID, BAL.L_TYPE, BAL.L_NAME, BAL.NATURAL_ACCOUNT,
     BAL.LOCATION, BAL.PRODUCT, BAL.INTERCOMPANY, BAL.FUTURE1, BAL.FUTURE2, BAL.CURRENCY, BAL.AMOUNT_PTD, BAL.AMOUNT_YTD, BAL.CREATION_DATE,
     BAL.CREATED_BY, BAL.LAST_UPDATE_DATE, BAL.LAST_UPDATED_BY, BAL.STATUS, BAL.ANET_STATUS, BAL.COG_STATUS, BAL.comb_id, BAL.MESSAGE,
     SEG.SEGMENT_DESCRIPTION  FROM ACC_SEGMENTS_V_TST SEG , ACC_BALANCE_STG BAL where BAL.NATURAL_ACCOUNT = SEG.SEGMENT_VALUE AND SEG.SEGMENT_COLUMN = 'SEGMENT99' AND BAL.ACCOUNTING_PERIOD = 'MAY-10' and BAL.comb_id
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    (select comb_id from
     (select comb_id, rownum r from
      (select distinct(comb_id),LAST_UPDATE_DATE from ACC_BALANCE_STG where accounting_period='MAY-10' order by LAST_UPDATE_DATE )    
         where rownum <=100)  where r >0)
    Please help me in fine tuning above. I am using Oracle 10g database. There are total of 8000 records. Let me know if any other info required.
    Thanks in advance.

    In recent versions of Oracle an EXISTS predicate should produce the same execution plan as the corresponding IN clause.
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    It looks to me like you could avoid the double pass on ACC_BALANCE_STG by using an analytical function like ROW_NUMBER() and then joining to ACC_SEGMENTS_V_TST SEG, maybe using subquery refactoring to make it look nicer.
    e.g. something like (untested)
    WITH subq_bal as
        ((SELECT *
          FROM (SELECT BAL.L_ID, BAL.L_TYPE, BAL.L_NAME, BAL.NATURAL_ACCOUNT,
                 BAL.LOCATION, BAL.PRODUCT, BAL.INTERCOMPANY, BAL.FUTURE1, BAL.FUTURE2,
                 BAL.CURRENCY, BAL.AMOUNT_PTD, BAL.AMOUNT_YTD, BAL.CREATION_DATE,
                 BAL.CREATED_BY, BAL.LAST_UPDATE_DATE, BAL.LAST_UPDATED_BY, BAL.STATUS, BAL.ANET_STATUS,
                 BAL.COG_STATUS, BAL.comb_id, BAL.MESSAGE,
                 ROW_NUMBER() OVER (ORDER BY LAST_UPDATE_DATE) rn
                 FROM   acc_balance_stg
                 WHERE  accounting_period='MAY-10')
          WHERE rn <= 100)
    SELECT *
    FROM   subq_bal bal
    ,      acc_Segments_v_tst seg
    where  BAL.NATURAL_ACCOUNT = SEG.SEGMENT_VALUE
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  • In  a SQL query whihc has join, How to reduce Multiple instance of a table

    in a SQL query which has join, How to reduce Multiple instance of a table
    Here is an example: I am using Oracle 9i
    is there a way to reduce no.of Person instances from the following query? or can I optimize this query further?
    TABLES:
    mail_table
    mail_id, from_person_id, to_person_id, cc_person_id, subject, body
    person_table
    person_id, name, email
    QUERY:
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    FROM mail, person p_from, person p_to, person p_cc
    WHERE from_person_id = p_from.person_id
    AND to_person_id = p_to.person_id
    AND cc_person_id = p_cc.person_id
    Thnanks in advance,
    Babu.

    SQL> select * from mail;
            ID          F          T         CC
             1          1          2          3
    SQL> select * from person;
           PID NAME
             1 a
             2 b
             3 c
    --Query with only ne Instance of PERSON Table
    SQL> select m.id,max(decode(m.f,p.pid,p.name)) frm_name,
      2         max(decode(m.t,p.pid,p.name)) to_name,
      3         max(decode(m.cc,p.pid,p.name)) cc_name
      4  from mail m,person p
      5  where m.f = p.pid
      6  or m.t = p.pid
      7  or m.cc = p.pid
      8  group by m.id;
            ID FRM_NAME   TO_NAME    CC_NAME
             1 a          b          c
    --Expalin plan for "One instance" Query
    SQL> explain plan for
      2  select m.id,max(decode(m.f,p.pid,p.name)) frm_name,
      3         max(decode(m.t,p.pid,p.name)) to_name,
      4         max(decode(m.cc,p.pid,p.name)) cc_name
      5  from mail m,person p
      6  where m.f = p.pid
      7  or m.t = p.pid
      8  or m.cc = p.pid
      9  group by m.id;
    Explained.
    SQL> select * from table(dbms_xplan.display);
    PLAN_TABLE_OUTPUT
    Plan hash value: 902563036
    | Id  | Operation           | Name   | Rows  | Bytes | Cost (%CPU)| Time     |
    |   0 | SELECT STATEMENT    |        |     3 |   216 |     7  (15)| 00:00:01 |
    |   1 |  HASH GROUP BY      |        |     3 |   216 |     7  (15)| 00:00:01 |
    |   2 |   NESTED LOOPS      |        |     3 |   216 |     6   (0)| 00:00:01 |
    |   3 |    TABLE ACCESS FULL| MAIL   |     1 |    52 |     3   (0)| 00:00:01 |
    |*  4 |    TABLE ACCESS FULL| PERSON |     3 |    60 |     3   (0)| 00:00:01 |
    PLAN_TABLE_OUTPUT
    Predicate Information (identified by operation id):
       4 - filter("M"."F"="P"."PID" OR "M"."T"="P"."PID" OR
                  "M"."CC"="P"."PID")
    Note
       - dynamic sampling used for this statement
    --Explain plan for "Normal" query
    SQL> explain plan for
      2  select m.id,pf.name fname,pt.name tname,pcc.name ccname
      3  from mail m,person pf,person pt,person pcc
      4  where m.f = pf.pid
      5  and m.t = pt.pid
      6  and m.cc = pcc.pid;
    Explained.
    SQL> select * from table(dbms_xplan.display);
    PLAN_TABLE_OUTPUT
    Plan hash value: 4145845855
    | Id  | Operation            | Name   | Rows  | Bytes | Cost (%CPU)| Time     |
    |   0 | SELECT STATEMENT     |        |     1 |   112 |    14  (15)| 00:00:01 |
    |*  1 |  HASH JOIN           |        |     1 |   112 |    14  (15)| 00:00:01 |
    |*  2 |   HASH JOIN          |        |     1 |    92 |    10  (10)| 00:00:01 |
    |*  3 |    HASH JOIN         |        |     1 |    72 |     7  (15)| 00:00:01 |
    |   4 |     TABLE ACCESS FULL| MAIL   |     1 |    52 |     3   (0)| 00:00:01 |
    |   5 |     TABLE ACCESS FULL| PERSON |     3 |    60 |     3   (0)| 00:00:01 |
    PLAN_TABLE_OUTPUT
    |   6 |    TABLE ACCESS FULL | PERSON |     3 |    60 |     3   (0)| 00:00:01 |
    |   7 |   TABLE ACCESS FULL  | PERSON |     3 |    60 |     3   (0)| 00:00:01 |
    Predicate Information (identified by operation id):
       1 - access("M"."CC"="PCC"."PID")
       2 - access("M"."T"="PT"."PID")
       3 - access("M"."F"="PF"."PID")
    PLAN_TABLE_OUTPUT
    Note
       - dynamic sampling used for this statement
    25 rows selected.
    Message was edited by:
            jeneesh
    No indexes created...                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               

  • SQL Query Performance

    Hi There,
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    --/*+ DRIVING_SITE(var) ALL_ROWS */
             ventity_id, ar_action_performed, action_date,
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        FROM (SELECT var.ventity_id, var.ar_action_performed, var.action_date,
                     var.familyname_id, var.status, var.isprotected,
                     var.dateofbirth, var.gender, var.sindigits,
                     LAG (var.familyname_id) OVER (PARTITION BY var.ventity_id ORDER BY action_date)
                                                                lag_familyname_id,
                     LAG (var.status) OVER (PARTITION BY var.ventity_id ORDER BY action_date)
                                                                       lag_status,
                     LAG (var.isprotected) OVER (PARTITION BY var.ventity_id ORDER BY action_date)
                                                                  lag_isprotected,
                     LAG (var.dateofbirth) OVER (PARTITION BY var.ventity_id ORDER BY action_date)
                                                                  lag_dateofbirth,
                     LAG (var.gender) OVER (PARTITION BY var.ventity_id ORDER BY action_date)
                                                                       lag_gender,
                     LAG (var.sindigits) OVER (PARTITION BY var.ventity_id ORDER BY action_date)
                                                                    lag_sindigits
                FROM cpp_schema.ventity_ar@CdpP var,
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                     (SELECT DISTINCT ventity_id
                                 FROM cpp_schema.ventity_ar@CdpP
                                WHERE action_date BETWEEN '01-MAR-10' AND '10-APR-10'
                                  AND ar_action_performed <> 'RTRV') m
               WHERE var.action_date <= '10-APR-10'
                 AND var.ventity_id = m.ventity_id
                 AND var.ar_action_performed <> 'RTRV') mm
       WHERE action_date BETWEEN '01-MAR-10' AND '10-APR-10'
         -- most of the columns from the data table allow nulls
         AND (   (NVL (familyname_id, 0) <> NVL (lag_familyname_id, 0))
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              OR (NVL (isprotected, 2) <> NVL (lag_isprotected, 2))
              OR (NVL (dateofbirth, TO_DATE ('15000101', 'yyyymmdd')) <>
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              OR (NVL (gender, 'x') <> NVL (lag_gender, 'x'))
              OR (NVL (sindigits, 'x') <> NVL (lag_sindigits, 'x'))
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    6401 rows selected.
    Elapsed: 00:01:47.03
    Execution Plan
    Plan hash value: 3953446945
    | Id  | Operation        | Name | Rows  | Bytes |TempSpc| Cost (%CPU)| Time     | Inst   |IN-OUT|
    |   0 | SELECT STATEMENT |      |    12M|  1575M|       |   661K  (1)| 02:12:22 |        |      |
    |   1 |  SORT ORDER BY   |      |    12M|  1575M|  2041M|   661K  (1)| 02:12:22 |        |      |
    |*  2 |   VIEW           |      |    12M|  1575M|       |   291K  (2)| 00:58:13 |        |      |
    |   3 |    REMOTE        |      |       |       |       |            |          | CCP01  | R->S |
       2 - filter("action_date">='01_MAR-10' AND "action_date"<='10-APR-10' AND
                  (NVL("FAMILYNAME_id",0)<>NVL("LAG_FAMILYNAME_id",0) OR
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                  ) OR NVL("DATEOFBIRTH",TO_DATE(' 1500-01-01 00:00:00', 'syyyy-mm-dd
                  hh24:mi:ss'))<>NVL("LAG_DATEOFBIRTH",TO_DATE(' 1500-01-01 00:00:00', 'syyyy-mm-dd
                  hh24:mi:ss')) OR NVL("GENDER",'x')<>NVL("LAG_GENDER",'x') OR
                  NVL("SINDIGITS",'x')<>NVL("LAG_SINDIGITS",'x')))
    Remote SQL Information (identified by operation id):
       3 - EXPLAIN PLAN SET STATEMENT_ID='PLUS4294967295' INTO PLAN_TABLE@! FOR SELECT
           "A2"."ventity_id","A2"."AR_ACTION_PERFORMED","A2"."action_date","A2"."FAMILYNAME_id","A2"
           ."STATUS","A2"."ISPROTECTED","A2"."DATEOFBIRTH","A2"."GENDER","A2"."SINDIGITS",DECODE(COU
           NT(*) OVER ( PARTITION BY "A2"."ventity_id" ORDER BY "A2"."action_date" ROWS  BETWEEN 1
           PRECEDING  AND 1 PRECEDING ),1,FIRST_VALUE("A2"."FAMILYNAME_id") OVER ( PARTITION BY
           "A2"."ventity_id" ORDER BY "A2"."action_date" ROWS  BETWEEN 1 PRECEDING  AND 1 PRECEDING
           ),NULL),DECODE(COUNT(*) OVER ( PARTITION BY "A2"."ventity_id" ORDER BY
           "A2"."action_date" ROWS  BETWEEN 1 PRECEDING  AND 1 PRECEDING ),1,FIRST_VALUE("A2"."STATUS")
           OVER ( PARTITION BY "A2"."ventity_id" ORDER BY "A2"."action_date" ROWS  BETWEEN 1
           PRECEDING  AND 1 PRECEDING ),NULL),DECODE(COUNT(*) OVER ( PARTITION BY
           "A2"."ventity_id" ORDER BY "A2"."action_date" ROWS  BETWEEN 1 PRECEDING  AND 1 PRECEDING
           ),1,FIRST_VALUE("A2"."ISPROTECTED") OVER ( PARTITION BY "A2"."ventity_id" ORDER BY
           "A2"."action_date" ROWS  BETWEEN 1 PRECEDING  AND 1 PRECEDING ),NULL),DECODE(COUNT(*) OVER (
           PARTITION BY "A2"."ventity_id" ORDER BY "A2"."action_date" ROWS  BETWEEN 1 PRECEDING
           AND 1 PRECEDING ),1,FIRST_VALUE("A2"."DATEOFBIRTH") OVER ( PARTITION BY
           "A2"."ventity_id" ORDER BY "A2"."action_date" ROWS  BETWEEN 1 PRECEDING  AND 1 PRECEDING
           ),NULL),DECODE(COUNT(*) OVER ( PARTITION BY "A2"."ventity_id" ORDER BY
           "A2"."action_date" ROWS  BETWEEN 1 PRECEDING  AND 1 PRECEDING ),1,FIRST_VALUE("A2"."GENDER")
           OVER ( PARTITION BY "A2"."ventity_id" ORDER BY "A2"."action_date" ROWS  BETWEEN 1
           PRECEDING  AND 1 PRECEDING ),NULL),DECODE(COUNT(*) OVER ( PARTITION BY
           "A2"."ventity_id" ORDER BY "A2"."action_date" ROWS  BETWEEN 1 PRECEDING  AND 1 PRECEDING
           ),1,FIRST_VALUE("A2"."SINDIGITS") OVER ( PARTITION BY "A2"."ventity_id" ORDER BY
           "A2"."action_date" ROWS  BETWEEN 1 PRECEDING  AND 1 PRECEDING ),NULL) FROM
           "CPP_SCHEMA"."ventity_AR" "A2", (SELECT DISTINCT "A3"."ventity_id"
           "ventity_id" FROM "CPP_SCHEMA"."ventity_AR" "A3" WHERE
           "A3"."action_date">='01_MAR-10' AND "A3"."action_date"<='10-APR-10' AND
           "A3"."AR_ACTION_PERFORMED"<>'RETRIEVE' AND TO_DATE('01_MAR-10')<=TO_DATE('10-APR-10'))
           "A1" WHERE "A2"."action_date"<='10-APR-10' AND "A2"."ventity_id"="A1"."ventity_id"
           AND "A2"."AR_ACTION_PERFORMED"<>'RETRIEVE' (accessing 'EBCP01.EBC.GOV.BC.CA' )Your advise and/or help is highly appreciated.
    THanks
    Edited by: rsar001 on Apr 20, 2010 6:57 AM

    Maybe I'm missing something but this subquery seems inefficient:
    SELECT var.ventity_id, var.ar_action_performed, var.action_date,
                     var.familyname_id, var.status, var.isprotected,
                     var.dateofbirth, var.gender, var.sindigits,
                     LAG (var.familyname_id) OVER (PARTITION BY var.ventity_id ORDER BY action_date)
                                                                lag_familyname_id,
                     LAG (var.status) OVER (PARTITION BY var.ventity_id ORDER BY action_date)
                                                                       lag_status,
                     LAG (var.isprotected) OVER (PARTITION BY var.ventity_id ORDER BY action_date)
                                                                  lag_isprotected,
                     LAG (var.dateofbirth) OVER (PARTITION BY var.ventity_id ORDER BY action_date)
                                                                  lag_dateofbirth,
                     LAG (var.gender) OVER (PARTITION BY var.ventity_id ORDER BY action_date)
                                                                       lag_gender,
                     LAG (var.sindigits) OVER (PARTITION BY var.ventity_id ORDER BY action_date)
                                                                    lag_sindigits
                FROM cpp_schema.ventity_ar@CdpP var,
                     -- reduce the set to ventity_id that had a change within the time frame,
                     -- and filter out RETRIEVEs as they do not signal change
                     (SELECT DISTINCT ventity_id
                                 FROM cpp_schema.ventity_ar@CdpP
                                WHERE action_date BETWEEN '01-MAR-10' AND '10-APR-10'
                                  AND ar_action_performed <> 'RTRV') m
               WHERE var.action_date <= '10-APR-10'
                 AND var.ventity_id = m.ventity_id
                 AND var.ar_action_performed != 'RTRV'I don't think accessing the VENTITY_AR table twice is helping you here. The comments looks like you want to restrict the set of VENTITY_IDs but if you look at the plan it is not happening. The plan is reading them from the index and joining against the full VENTITY_AR table anyways. I recommend you consolidate it into something like this:
    SELECT  var.ventity_id
    ,       var.ar_action_performed
    ,       var.action_date
    ,       var.familyname_id
    ,       var.status
    ,       var.isprotected
    ,       var.dateofbirth
    ,       var.gender
    ,       var.sindigits
    ,       LAG (var.familyname_id) OVER (PARTITION BY var.ventity_id ORDER BY action_date)         AS lag_familyname_id
    ,       LAG (var.status) OVER (PARTITION BY var.ventity_id ORDER BY action_date)                AS lag_status
    ,       LAG (var.isprotected) OVER (PARTITION BY var.ventity_id ORDER BY action_date)           AS lag_isprotected
    ,       LAG (var.dateofbirth) OVER (PARTITION BY var.ventity_id ORDER BY action_date)           AS lag_dateofbirth
    ,       LAG (var.gender) OVER (PARTITION BY var.ventity_id ORDER BY action_date)                AS lag_gender
    ,       LAG (var.sindigits) OVER (PARTITION BY var.ventity_id ORDER BY action_date)             AS lag_sindigits
    FROM    cpp_schema.ventity_ar@CdpP var
    WHERE   var.action_date BETWEEN TO_DATE('01-MAR-10','DD-MON-YY') AND TO_DATE('10-APR-10','DD-MON-YY')
    AND     var.ar_action_performed != 'RTRV'It may then be useful to put an index on (ACTION_DATE,AR_ACTION_PERFORMED) if one doesn't already exist.
    *::EDIT::*
    I noticed the large amount of NVL calls in your outer query. These NVLs could possibly be eliminated if you use the optional second and third arguments of the LAG analytical function. I'm not sure if this would improve performance but it may make the query more readable and maintainable.
    HTH!
    Edited by: Centinul on Apr 20, 2010 10:50 AM

  • Performance of OBIEE report whereas SQL query behind it executed in 1-2 min

    Facing lot of performance issues in OBIEE reports, whereas SQL query behind the report fetch data in 2-3 minutes. Reprot take around 1-2 hrs. Can anyone help to resolve this please?

    (my 2c worth)... if the physical query runs for a reasonably short time but the report takes much longer to return it suggests the rendering process (ie. pivot view) is lagging.
    To test this theory, go into Answers and remove all views from the request and leave a simple table view on the compound view. Run the report and the report should return around the same time the physical request takes to run because the table view is a very raw, un aggregated rendering process. Table views are nice and fast. If that works then you can focus on tuning your other views, ie. Pivot view. I've seen a simple pivot view take minutes to render what looks like a simple report because the underlying recordset is quite large.
    I hope this helped. another quick trick you could try is applying aggregation in the formulas to aggregate things at the physical sql level so the returning result set isn't 5,000. depends what you're up to with the end report.
    Edited by: user8300108 on 25-Feb-2010 04:40

  • Need help in improving the performance for the sql query

    Thanks in advance for helping me.
    I was trying to improve the performance of the below query. I tried the following methods used merge instead of update, used bulk collect / Forall update, used ordered hint, created a temp table and upadated the target table using the same. The methods which I used did not improve any performance. The data count which is updated in the target table is 2 million records and the target table has 15 million records.
    Any suggestions or solutions for improving performance are appreciated
    SQL query:
    update targettable tt
    set mnop = 'G',
    where ( x,y,z ) in
    select a.x, a.y,a.z
    from table1 a
    where (a.x, a.y,a.z) not in (
    select b.x,b.y,b.z
    from table2 b
    where 'O' = b.defg
    and mnop = 'P'
    and hijkl = 'UVW';

    987981 wrote:
    I was trying to improve the performance of the below query. I tried the following methods used merge instead of update, used bulk collect / Forall update, used ordered hint, created a temp table and upadated the target table using the same. The methods which I used did not improve any performance. And that meant what? Surely if you spend all that time and effort to try various approaches, it should mean something? Failures are as important teachers as successes. You need to learn from failures too. :-)
    The data count which is updated in the target table is 2 million records and the target table has 15 million records.Tables have rows btw, not records. Database people tend to get upset when rows are called records, as records exist in files and a database is not a mere collection of records and files.
    The failure to find a single faster method with the approaches you tried, points to that you do not know what the actual performance problem is. And without knowing the problem, you still went ahead, guns blazing.
    The very first step in dealing with any software engineering problem, is to identify the problem. Seeing the symptoms (slow performance) is still a long way from problem identification.
    Part of identifying the performance problem, is understanding the workload. Just what does the code task the database to do?
    From your comments, it needs to find 2 million rows from 15 million rows. Change these rows. And then write 2 million rows back to disk.
    That is not a small workload. Simple example. Let's say that the 2 million row find is 1ms/row and the 2 million row write is also 1ms/row. This means a 66 minute workload. Due to the number of rows, an increase in time/row either way, will potentially have 2 million fold impact.
    So where is the performance problem? Time spend finding the 2 million rows (where other tables need to be read, indexes used, etc)? Time spend writing the 2 million rows (where triggers and indexes need to be fired and maintained)? Both?

  • How to compare same SQL query performance in different DB servers.

    We have Production and Validation Environment of Oracle11g DB on two Solaris OSs.
    H/W and DB,etc configurations of two Oracle DBs are almost same in PROD and VAL.
    But we detected large SQL query performace difference in PROD DB and VAL DB in same SQL query.
    I would like to find and solve the cause of this situation.
    How could I do that ?
    I plan to compare SQL execution plan in PROD and VAL DB and index fragmentations.
    Before that I thought I need to keep same condition of DB statistics information in PROD and VAL DB.
    So, I plan to execute alter system FLUSH BUFFER_CACHE;
    But I am worring about bad effects of alter system FLUSH BUFFER_CACHE; to end users
    If we did alter system FLUSH BUFFER_CACHE; and got execution plan of that SQL query in the time end users do not use that system ,
    there is not large bad effect to end users after those operations?
    Could you please let me know the recomendation to compare SQL query performace ?

    Thank you.
    I got AWR report for only VAL DB server but it looks strange.
    Is there any thing wrong in DB or how to get AWR report ?
    Host Name
    Platform
    CPUs
    Cores
    Sockets
    Memory (GB)
    xxxx
    Solaris[tm] OE (64-bit)
    .00
    Snap Id
    Snap Time
    Sessions
    Cursors/Session
    Begin Snap:
    xxxx
    13-Apr-15 04:00:04
    End Snap:
    xxxx
    14-Apr-15 04:00:22
    Elapsed:
    1,440.30 (mins)
    DB Time:
    0.00 (mins)
    Report Summary
    Cache Sizes
    Begin
    End
    Buffer Cache:
    M
    M
    Std Block Size:
    K
    Shared Pool Size:
    0M
    0M
    Log Buffer:
    K
    Load Profile
    Per Second
    Per Transaction
    Per Exec
    Per Call
    DB Time(s):
    0.0
    0.0
    0.00
    0.00
    DB CPU(s):
    0.0
    0.0
    0.00
    0.00
    Redo size:
    Logical reads:
    0.0
    1.0
    Block changes:
    0.0
    1.0
    Physical reads:
    0.0
    1.0
    Physical writes:
    0.0
    1.0
    User calls:
    0.0
    1.0
    Parses:
    0.0
    1.0
    Hard parses:
    W/A MB processed:
    16.7
    1,442,472.0
    Logons:
    Executes:
    0.0
    1.0
    Rollbacks:
    Transactions:
    0.0
    Instance Efficiency Percentages (Target 100%)
    Buffer Nowait %:
    Redo NoWait %:
    Buffer Hit %:
    In-memory Sort %:
    Library Hit %:
    96.69
    Soft Parse %:
    Execute to Parse %:
    0.00
    Latch Hit %:
    Parse CPU to Parse Elapsd %:
    % Non-Parse CPU:
    Shared Pool Statistics
    Begin
    End
    Memory Usage %:
    % SQL with executions>1:
    34.82
    48.31
    % Memory for SQL w/exec>1:
    63.66
    73.05
    Top 5 Timed Foreground Events
    Event
    Waits
    Time(s)
    Avg wait (ms)
    % DB time
    Wait Class
    DB CPU
    0
    100.00
    Host CPU (CPUs: Cores: Sockets: )
    Load Average Begin
    Load Average End
    %User
    %System
    %WIO
    %Idle
    Instance CPU
    %Total CPU
    %Busy CPU
    %DB time waiting for CPU (Resource Manager)
    Memory Statistics
    Begin
    End
    Host Mem (MB):
    SGA use (MB):
    46,336.0
    46,336.0
    PGA use (MB):
    713.6
    662.6
    % Host Mem used for SGA+PGA:
    Time Model Statistics
    No data exists for this section of the report.
    Back to Wait Events Statistics
    Back to Top
    Operating System Statistics
    No data exists for this section of the report.
    Back to Wait Events Statistics
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    Operating System Statistics - Detail
    No data exists for this section of the report.
    Back to Wait Events Statistics
    Back to Top
    Foreground Wait Class
    s - second, ms - millisecond - 1000th of a second
    ordered by wait time desc, waits desc
    %Timeouts: value of 0 indicates value was < .5%. Value of null is truly 0
    Captured Time accounts for % of Total DB time .00 (s)
    Total FG Wait Time: (s) DB CPU time: .00 (s)
    Wait Class
    Waits
    %Time -outs
    Total Wait Time (s)
    Avg wait (ms)
    %DB time
    DB CPU
    0
    100.00
    Back to Wait Events Statistics
    Back to Top
    Foreground Wait Events
    No data exists for this section of the report.
    Back to Wait Events Statistics
    Back to Top
    Background Wait Events
    ordered by wait time desc, waits desc (idle events last)
    Only events with Total Wait Time (s) >= .001 are shown
    %Timeouts: value of 0 indicates value was < .5%. Value of null is truly 0
    Event
    Waits
    %Time -outs
    Total Wait Time (s)
    Avg wait (ms)
    Waits /txn
    % bg time
    log file parallel write
    527,034
    0
    2,209
    4
    527,034.00
    db file parallel write
    381,966
    0
    249
    1
    381,966.00
    os thread startup
    2,650
    0
    151
    57
    2,650.00
    latch: messages
    125,526
    0
    89
    1
    125,526.00
    control file sequential read
    148,662
    0
    54
    0
    148,662.00
    control file parallel write
    41,935
    0
    28
    1
    41,935.00
    Log archive I/O
    5,070
    0
    14
    3
    5,070.00
    Disk file operations I/O
    8,091
    0
    10
    1
    8,091.00
    log file sequential read
    3,024
    0
    6
    2
    3,024.00
    db file sequential read
    1,299
    0
    2
    2
    1,299.00
    latch: shared pool
    722
    0
    1
    1
    722.00
    enq: CF - contention
    4
    0
    1
    208
    4.00
    reliable message
    1,316
    0
    1
    1
    1,316.00
    log file sync
    71
    0
    1
    9
    71.00
    enq: CR - block range reuse ckpt
    36
    0
    0
    13
    36.00
    enq: JS - queue lock
    459
    0
    0
    1
    459.00
    log file single write
    414
    0
    0
    1
    414.00
    enq: PR - contention
    5
    0
    0
    57
    5.00
    asynch descriptor resize
    67,076
    100
    0
    0
    67,076.00
    LGWR wait for redo copy
    5,184
    0
    0
    0
    5,184.00
    rdbms ipc reply
    1,234
    0
    0
    0
    1,234.00
    ADR block file read
    384
    0
    0
    0
    384.00
    SQL*Net message to client
    189,490
    0
    0
    0
    189,490.00
    latch free
    559
    0
    0
    0
    559.00
    db file scattered read
    17
    0
    0
    6
    17.00
    resmgr:internal state change
    1
    100
    0
    100
    1.00
    direct path read
    301
    0
    0
    0
    301.00
    enq: RO - fast object reuse
    35
    0
    0
    2
    35.00
    direct path write
    122
    0
    0
    1
    122.00
    latch: cache buffers chains
    260
    0
    0
    0
    260.00
    db file parallel read
    1
    0
    0
    41
    1.00
    ADR file lock
    144
    0
    0
    0
    144.00
    latch: redo writing
    55
    0
    0
    1
    55.00
    ADR block file write
    120
    0
    0
    0
    120.00
    wait list latch free
    2
    0
    0
    10
    2.00
    latch: cache buffers lru chain
    44
    0
    0
    0
    44.00
    buffer busy waits
    3
    0
    0
    2
    3.00
    latch: call allocation
    57
    0
    0
    0
    57.00
    SQL*Net more data to client
    55
    0
    0
    0
    55.00
    ARCH wait for archivelog lock
    78
    0
    0
    0
    78.00
    rdbms ipc message
    3,157,653
    40
    4,058,370
    1285
    3,157,653.00
    Streams AQ: qmn slave idle wait
    11,826
    0
    172,828
    14614
    11,826.00
    DIAG idle wait
    170,978
    100
    172,681
    1010
    170,978.00
    dispatcher timer
    1,440
    100
    86,417
    60012
    1,440.00
    Streams AQ: qmn coordinator idle wait
    6,479
    48
    86,413
    13337
    6,479.00
    shared server idle wait
    2,879
    100
    86,401
    30011
    2,879.00
    Space Manager: slave idle wait
    17,258
    100
    86,324
    5002
    17,258.00
    pmon timer
    46,489
    62
    86,252
    1855
    46,489.00
    smon timer
    361
    66
    86,145
    238628
    361.00
    VKRM Idle
    1
    0
    14,401
    14400820
    1.00
    SQL*Net message from client
    253,909
    0
    419
    2
    253,909.00
    class slave wait
    379
    0
    0
    0
    379.00
    Back to Wait Events Statistics
    Back to Top
    Wait Event Histogram
    No data exists for this section of the report.
    Back to Wait Events Statistics
    Back to Top
    Wait Event Histogram Detail (64 msec to 2 sec)
    No data exists for this section of the report.
    Back to Wait Events Statistics
    Back to Top
    Wait Event Histogram Detail (4 sec to 2 min)
    No data exists for this section of the report.
    Back to Wait Events Statistics
    Back to Top
    Wait Event Histogram Detail (4 min to 1 hr)
    No data exists for this section of the report.
    Back to Wait Events Statistics
    Back to Top
    Service Statistics
    No data exists for this section of the report.
    Back to Wait Events Statistics
    Back to Top
    Service Wait Class Stats
    No data exists for this section of the report.
    Back to Wait Events Statistics
    Back to Top
    SQL Statistics
    SQL ordered by Elapsed Time
    SQL ordered by CPU Time
    SQL ordered by User I/O Wait Time
    SQL ordered by Gets
    SQL ordered by Reads
    SQL ordered by Physical Reads (UnOptimized)
    SQL ordered by Executions
    SQL ordered by Parse Calls
    SQL ordered by Sharable Memory
    SQL ordered by Version Count
    Complete List of SQL Text
    Back to Top
    SQL ordered by Elapsed Time
    No data exists for this section of the report.
    Back to SQL Statistics
    Back to Top
    SQL ordered by CPU Time
    No data exists for this section of the report.
    Back to SQL Statistics
    Back to Top
    SQL ordered by User I/O Wait Time
    No data exists for this section of the report.
    Back to SQL Statistics
    Back to Top
    SQL ordered by Gets
    No data exists for this section of the report.
    Back to SQL Statistics
    Back to Top
    SQL ordered by Reads
    No data exists for this section of the report.
    Back to SQL Statistics
    Back to Top
    SQL ordered by Physical Reads (UnOptimized)
    No data exists for this section of the report.
    Back to SQL Statistics
    Back to Top
    SQL ordered by Executions
    No data exists for this section of the report.
    Back to SQL Statistics
    Back to Top
    SQL ordered by Parse Calls
    No data exists for this section of the report.
    Back to SQL Statistics
    Back to Top
    SQL ordered by Sharable Memory
    No data exists for this section of the report.
    Back to SQL Statistics
    Back to Top
    SQL ordered by Version Count
    No data exists for this section of the report.
    Back to SQL Statistics
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    Complete List of SQL Text
    No data exists for this section of the report.
    Back to SQL Statistics
    Back to Top
    Instance Activity Statistics
    Instance Activity Stats
    Instance Activity Stats - Absolute Values
    Instance Activity Stats - Thread Activity
    Back to Top
    Instance Activity Stats
    No data exists for this section of the report.
    Back to Instance Activity Statistics
    Back to Top
    Instance Activity Stats - Absolute Values
    No data exists for this section of the report.
    Back to Instance Activity Statistics
    Back to Top
    Instance Activity Stats - Thread Activity
    Statistics identified by '(derived)' come from sources other than SYSSTAT
    Statistic
    Total
    per Hour
    log switches (derived)
    69
    2.87
    Back to Instance Activity Statistics
    Back to Top
    IO Stats
    IOStat by Function summary
    IOStat by Filetype summary
    IOStat by Function/Filetype summary
    Tablespace IO Stats
    File IO Stats
    Back to Top
    IOStat by Function summary
    'Data' columns suffixed with M,G,T,P are in multiples of 1024 other columns suffixed with K,M,G,T,P are in multiples of 1000
    ordered by (Data Read + Write) desc
    Function Name
    Reads: Data
    Reqs per sec
    Data per sec
    Writes: Data
    Reqs per sec
    Data per sec
    Waits: Count
    Avg Tm(ms)
    Others
    28.8G
    20.55
    .340727
    16.7G
    2.65
    .198442
    1803K
    0.01
    Direct Reads
    43.6G
    57.09
    .517021
    411M
    0.59
    .004755
    0
    LGWR
    19M
    0.02
    .000219
    41.9G
    21.87
    .496493
    2760
    0.08
    Direct Writes
    16M
    0.00
    .000185
    8.9G
    1.77
    .105927
    0
    DBWR
    0M
    0.00
    0M
    6.7G
    4.42
    .079670
    0
    Buffer Cache Reads
    3.1G
    3.67
    .037318
    0M
    0.00
    0M
    260.1K
    3.96
    TOTAL:
    75.6G
    81.33
    .895473
    74.7G
    31.31
    .885290
    2065.8K
    0.51
    Back to IO Stats
    Back to Top
    IOStat by Filetype summary
    'Data' columns suffixed with M,G,T,P are in multiples of 1024 other columns suffixed with K,M,G,T,P are in multiples of 1000
    Small Read and Large Read are average service times, in milliseconds
    Ordered by (Data Read + Write) desc
    Filetype Name
    Reads: Data
    Reqs per sec
    Data per sec
    Writes: Data
    Reqs per sec
    Data per sec
    Small Read
    Large Read
    Data File
    53.2G
    78.33
    .630701
    8.9G
    7.04
    .105197
    0.37
    21.51
    Log File
    13.9G
    0.18
    .164213
    41.9G
    21.85
    .496123
    0.02
    2.93
    Archive Log
    0M
    0.00
    0M
    13.9G
    0.16
    .164213
    Temp File
    5.6G
    0.67
    .066213
    8.1G
    0.80
    .096496
    5.33
    3713.27
    Control File
    2.9G
    2.16
    .034333
    2G
    1.46
    .023247
    0.05
    19.98

  • SQL query performance issues.

    Hi All,
    I worked on the query a month ago and the fix worked for me in test intance but failed in production. Following is the URL for the previous thread.
    SQL query performance issues.
    Following is the tkprof file.
    CURSOR_ID:76  LENGTH:2383  ADDRESS:f6b40ab0  HASH_VALUE:2459471753  OPTIMIZER_GOAL:ALL_ROWS  USER_ID:443 (APPS)
    insert into cos_temp(
    TRX_DATE, DEPT, PRODUCT_LINE, PART_NUMBER,
    CUSTOMER_NUMBER, QUANTITY_SOLD, ORDER_NUMBER,
    INVOICE_NUMBER, EXT_SALES, EXT_COS,
    GROSS_PROFIT, ACCT_DATE,
    SHIPMENT_TYPE,
    FROM_ORGANIZATION_ID,
    FROM_ORGANIZATION_CODE)
    select a.trx_date,
    g.segment5 dept,
    g.segment4 prd,
    m.segment1 part,
    d.customer_number customer,
    b.quantity_invoiced units,
    --       substr(a.sales_order,1,6) order#,
    substr(ltrim(b.interface_line_attribute1),1,10) order#,
    a.trx_number invoice,
    (b.quantity_invoiced * b.unit_selling_price) sales,
    (b.quantity_invoiced * nvl(price.operand,0)) cos,
    (b.quantity_invoiced * b.unit_selling_price) -
    (b.quantity_invoiced * nvl(price.operand,0)) profit,
    to_char(to_date('2010/02/28 00:00:00','yyyy/mm/dd HH24:MI:SS'),'DD-MON-RR') acct_date,
    'DRP',
    l.ship_from_org_id,
    p.organization_code
    from   ra_customers d,
    gl_code_combinations g,
    mtl_system_items m,
    ra_cust_trx_line_gl_dist c,
    ra_customer_trx_lines b,
    ra_customer_trx_all a,
    apps.oe_order_lines l,
    apps.HR_ORGANIZATION_INFORMATION i,
    apps.MTL_INTERCOMPANY_PARAMETERS inter,
    apps.HZ_CUST_SITE_USES_ALL site,
    apps.qp_list_lines_v price,
    apps.mtl_parameters p
    where a.trx_date between to_date('2010/02/01 00:00:00','yyyy/mm/dd HH24:MI:SS')
    and to_date('2010/02/28 00:00:00','yyyy/mm/dd HH24:MI:SS')+0.9999
    and   a.batch_source_id = 1001     -- Sales order shipped other OU
    and   a.complete_flag = 'Y'
    and   a.customer_trx_id = b.customer_trx_id
    and   b.customer_trx_line_id = c.customer_trx_line_id
    and   a.sold_to_customer_id = d.customer_id
    and   b.inventory_item_id = m.inventory_item_id
    and   m.organization_id
         = decode(substr(g.segment4,1,2),'01',5004,'03',5004,
         '02',5003,'00',5001,5002)
    and   nvl(m.item_type,'0') <> '111'
    and   c.code_combination_id = g.code_combination_id+0
    and   l.line_id = b.interface_line_attribute6
    and   i.organization_id = l.ship_from_org_id
    and   p.organization_id = l.ship_from_org_id
    and   i.org_information3 <> '5108'
    and   inter.ship_organization_id = i.org_information3
    and   inter.sell_organization_id = '5108'
    and   inter.customer_site_id = site.site_use_id
    and   site.price_list_id = price.list_header_id
    and   product_attr_value = to_char(m.inventory_item_id)
    call        count       cpu   elapsed         disk        query      current         rows    misses
    Parse           1      0.47      0.56           11          197            0            0         1
    Execute         1   3733.40   3739.40        34893    519962154           11          188         0
    total           2   3733.87   3739.97        34904    519962351           11          188         1
    |         Rows Row Source Operation
    | ------------ ---------------------------------------------------
    |          188 HASH JOIN (cr=519962149 pr=34889 pw=0 time=2607.35)
    |          741 .TABLE ACCESS BY INDEX ROWID QP_PRICING_ATTRIBUTES (cr=519939426 pr=34889 pw=0 time=2457.32)
    |    254644500 ..NESTED LOOPS (cr=519939265 pr=34777 pw=0 time=3819.67)
    |    254643758 ...NESTED LOOPS (cr=8921833 pr=29939 pw=0 time=1274.41)
    |          741 ....NESTED LOOPS (cr=50042 pr=7230 pw=0 time=11.37)
    |          741 .....NESTED LOOPS (cr=48558 pr=7229 pw=0 time=11.35)
    |          741 ......NESTED LOOPS (cr=47815 pr=7223 pw=0 time=11.32)
    |         3237 .......NESTED LOOPS (cr=41339 pr=7223 pw=0 time=12.42)
    |         3237 ........NESTED LOOPS (cr=38100 pr=7223 pw=0 time=12.39)
    |         3237 .........NESTED LOOPS (cr=28296 pr=7139 pw=0 time=12.29)
    |         1027 ..........NESTED LOOPS (cr=17656 pr=4471 pw=0 time=3.81)
    |         1027 ...........NESTED LOOPS (cr=13537 pr=4404 pw=0 time=3.30)
    |          486 ............NESTED LOOPS (cr=10873 pr=4240 pw=0 time=0.04)
    |          486 .............NESTED LOOPS (cr=10385 pr=4240 pw=0 time=0.03)
    |          486 ..............TABLE ACCESS BY INDEX ROWID RA_CUSTOMER_TRX_ALL (cr=9411 pr=4240 pw=0 time=0.02)
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        l_stmt_ref     TYPE REF TO cl_sql_statement,
        l_dref         TYPE REF TO data,
        l_res_ref      TYPE REF TO cl_sql_result_set,
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              'A.INCO1 LIKE ? AND'
              'A.INCO2 LIKE ? AND'
              'A.ZSALES >= ? AND A.ZSALES <= ? AND'
              'A.KUNNR  >= ? AND A.KUNNR <= ? AND'
              'A.PRBATCH  >= ? AND A.PRBATCH <= ? AND'
              'A.VKBUR  >= ? AND A.VKBUR <= ? AND'
              'A.VKGRP  >= ? AND A.VKGRP <= ? AND'
              'B.WRKST  >= ? AND B.WRKST <= ? AND'
              'B.MTART  >= ? AND B.MTART <= ? AND'
              '? BETWEEN A.DATAB AND A.DATBI AND'
              'B.GROES LIKE ? AND'
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              'B.SPDINDEX LIKE ? AND'
              'B.RIM LIKE ? AND'
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              'order by A.MATNR'
        INTO l_stmt SEPARATED BY space.                         "#EC NOTEXT
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      l_stmt_ref->set_param( l_dref ).
    *binding other references here
      GET REFERENCE OF l_col33 INTO l_dref.
      l_stmt_ref->set_param( l_dref ).
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      l_col1  = sy-mandt.
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      l_col33 = p_mgroup.
    *  PERFORM trace_2 USING 'EXECUTE_QUERY' l_stmt l_col1 l_col2.
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      GET REFERENCE OF l_itab INTO l_dref.
      l_res_ref->set_param_table( l_dref ).
    * get the complete result set
      l_row_cnt = l_res_ref->next_package( ).
    * display the contents of the output table
    *  PERFORM trace_next_package USING l_itab.
    *  PERFORM trace_result USING l_row_cnt 'rows fetched'.
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      free l_itab.
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      l_res_ref->close( ).
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    *  FORM disconnect
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    FORM disconnect
      USING   p_con_ref TYPE REF TO cl_sql_connection
      RAISING cx_sql_exception.
      DATA: l_con_name TYPE dbcon-con_name.
      l_con_name = p_con_ref->get_con_name( ).
      CHECK l_con_name <> cl_sql_connection=>c_default_connection.
    *  PERFORM trace_0 USING 'CLOSE CONNECTION' l_con_name.
      p_con_ref->close( ).
    *  PERFORM trace_result USING l_con_name 'closed'.
    ENDFORM.                    "disconnect
    *  FORM handle_sql_exception
    *  Write appropriate error messages when a SQL exception has occured
    *  -->  P_SQLERR_REF  reference to a CX_SQL_EXCEPTION object
    FORM handle_sql_exception
      USING p_sqlerr_ref TYPE REF TO cx_sql_exception.
      FORMAT COLOR COL_NEGATIVE.
      IF p_sqlerr_ref->db_error = 'X'.
        WRITE: / 'SQL error occured:', p_sqlerr_ref->sql_code,
               / p_sqlerr_ref->sql_message.                     "#EC NOTEXT
      ELSE.
        WRITE:
          / 'Error from DBI (details in dev-trace):',
            p_sqlerr_ref->internal_error.                       "#EC NOTEXT
      ENDIF.
    ENDFORM.                    "handle_sql_exception

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