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
in  
(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.
Follow the advice in the tuning threads as suggested by SomeoneElse.
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
AND    SEG.SEGMENT_COLUMN = 'SEGMENT99';However, the parentheses you use around comb_id make me question what your intention is here in the subquery?
Do you have multiple rows in ACC_BALANCE_STG for the same comb_id and last_update_date?
If so you may want to do a MAX on last_update_date, group by comb_id before doing the analytic restriction.
Edited by: DomBrooks on Jun 16, 2010 5:56 PM

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    Ashish

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                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') 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))
              OR (NVL (status, 'x') <> NVL (lag_status, 'x'))
              OR (NVL (isprotected, 2) <> NVL (lag_isprotected, 2))
              OR (NVL (dateofbirth, TO_DATE ('15000101', 'yyyymmdd')) <>
                           NVL (lag_dateofbirth, TO_DATE ('15000101', 'yyyymmdd'))
              OR (NVL (gender, 'x') <> NVL (lag_gender, 'x'))
              OR (NVL (sindigits, 'x') <> NVL (lag_sindigits, 'x'))
    ORDER BY ventity_id, action_date DESC
    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
                  NVL("STATUS",'x')<>NVL("LAG_STATUS",'x') OR NVL("ISPROTECTED",2)<>NVL("LAG_ISPROTECTED",2
                  ) 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

  • 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
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    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
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    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
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    Foreground Wait Events
    No data exists for this section of the report.
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    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
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    Wait Event Histogram
    No data exists for this section of the report.
    Back to Wait Events Statistics
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    Wait Event Histogram Detail (64 msec to 2 sec)
    No data exists for this section of the report.
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    Wait Event Histogram Detail (4 sec to 2 min)
    No data exists for this section of the report.
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    Wait Event Histogram Detail (4 min to 1 hr)
    No data exists for this section of the report.
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    Service Statistics
    No data exists for this section of the report.
    Back to Wait Events Statistics
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    Service Wait Class Stats
    No data exists for this section of the report.
    Back to Wait Events Statistics
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    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.
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    SQL ordered by CPU Time
    No data exists for this section of the report.
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    SQL ordered by User I/O Wait Time
    No data exists for this section of the report.
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    SQL ordered by Gets
    No data exists for this section of the report.
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    SQL ordered by Reads
    No data exists for this section of the report.
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    SQL ordered by Physical Reads (UnOptimized)
    No data exists for this section of the report.
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    SQL ordered by Executions
    No data exists for this section of the report.
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    SQL ordered by Parse Calls
    No data exists for this section of the report.
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    SQL ordered by Sharable Memory
    No data exists for this section of the report.
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    SQL ordered by Version Count
    No data exists for this section of the report.
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    Complete List of SQL Text
    No data exists for this section of the report.
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    Instance Activity Statistics
    Instance Activity Stats
    Instance Activity Stats - Absolute Values
    Instance Activity Stats - Thread Activity
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    Instance Activity Stats
    No data exists for this section of the report.
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    Instance Activity Stats - Absolute Values
    No data exists for this section of the report.
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    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
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    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

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    http://sqlblog.com/blogs/uri_dimant/
    MS SQL optimization: MS SQL Development and Optimization
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              station_close      = station_closed_total,
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          station_closed_total     := 0.0;
          station_all_report_total := 0.0;
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    Edited by: Indhu Ram on Mar 10, 2010 9:56 AM
    Edited by: Indhu Ram on Mar 10, 2010 10:58 AM
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