Tuning a query - 'A-lines' are false

Hi all

I use 11 GR 2. I have 2 questions about a very simple query. My query is the following

Select * from fac_daily_trans_perform f, dim_performance p where f.performance_key = p.performance_key;

The fac_daily_trans_perform table has 635893 lines (and it is partitioned by range) and the dim_performance of the table has 5 rows.

My 2 questions are the following:

1. Although statistics were generated, the lines 'A' are wrong. On the plan is 50 but there are 635 K (estimated lines are correct). Do you know why this column is always wrong when I generate a plan?

2. my second question is fairly general, what would be the best way to address such a request either to refine a simple join (but which returns the number of rows)?

Thank you very much.
"PLAN_TABLE_OUTPUT"
"SQL_ID  a48hf3bhfbw25, child number 0"
"-------------------------------------"
"select * from fac_daily_trans_perform f, dim_performance p  where "
"f.performance_key = p.performance_key"
" "
"Plan hash value: 3635464132"
" "
"-------------------------------------------------------------------------------------------------------------------------------------"
"| Id  | Operation            | Name                    | Starts | E-Rows | A-Rows |   A-Time   | Buffers |  OMem |  1Mem |  O/1/M   |"
"-------------------------------------------------------------------------------------------------------------------------------------"
"|   0 | SELECT STATEMENT     |                         |      1 |        |     50 |00:00:00.01 |       6 |       |       |          |"
"|*  1 |  HASH JOIN           |                         |      1 |    635K|     50 |00:00:00.01 |       6 |   843K|   843K|     1/0/0|"
"|   2 |   TABLE ACCESS FULL  | DIM_PERFORMANCE         |      1 |      5 |      5 |00:00:00.01 |       2 |       |       |          |"
"|   3 |   PARTITION RANGE ALL|                         |      1 |    635K|     50 |00:00:00.01 |       4 |       |       |          |"
"|   4 |    TABLE ACCESS FULL | FAC_DAILY_TRANS_PERFORM |      3 |    635K|     50 |00:00:00.01 |       4 |       |       |          |"
"-------------------------------------------------------------------------------------------------------------------------------------"
" "
"Predicate Information (identified by operation id):"
"---------------------------------------------------"
" "
"   1 - access("F"."PERFORMANCE_KEY"="P"."PERFORMANCE_KEY")"
" "

But now, as I want to check if my 'A-lines' and my 'E-' are pretty much the same, how can I get my "real" 'A-lines?

You need to recover all the data.
In SQL Developer, you could F5 (run as a script) rather than F9 (run)

Tags: Database

Similar Questions

  • How to set up a query - 'A-lines' and 'E' are different.

    Hi all

    I use 11 g R2 and I'm trying to resolve a query. On the execution below plan, my E-lines and my A are different. As you can see, there is little the same line 22 to 43, but starting from line 21 to 1 E-lines are false. For example, on the content (RowSource) 12, E-lines is (1 * 179) and lines A is 8631.

    All statistics have been generated and are up to date. Do you know what could be the problem?
    --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
    | Id  | Operation                                     | Name                      | Starts | E-Rows | A-Rows |   A-Time   | Buffers | Reads  | Writes |  OMem |  1Mem |  O/1/M   | Max-Tmp |
    --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
    |   0 | SELECT STATEMENT                              |                           |      1 |        |     50 |00:05:55.08 |     203K|  69975 |   1094 |       |       |          |         |
    |   1 |  SORT ORDER BY                                |                           |      1 |    179 |     50 |00:05:55.08 |     203K|  69975 |   1094 |  8307K|  1133K|          |         |
    |   2 |   HASH UNIQUE                                 |                           |      1 |    179 |   8631 |00:05:54.56 |     203K|  69317 |    180 |  4474K|  1861K|          |   16384 |
    |   3 |    NESTED LOOPS                               |                           |      1 |        |   8631 |00:05:54.04 |     203K|  69137 |      0 |       |       |          |         |
    |   4 |     NESTED LOOPS                              |                           |      1 |    179 |   8631 |00:05:23.24 |     194K|  63768 |      0 |       |       |          |         |
    |   5 |      NESTED LOOPS                             |                           |      1 |    179 |   8631 |00:05:13.51 |     177K|  61396 |      0 |       |       |          |         |
    |   6 |       NESTED LOOPS                            |                           |      1 |    179 |   8631 |00:04:03.74 |     151K|  52928 |      0 |       |       |          |         |
    |   7 |        NESTED LOOPS                           |                           |      1 |    179 |   8631 |00:03:32.15 |     125K|  46425 |      0 |       |       |          |         |
    |*  8 |         HASH JOIN                             |                           |      1 |    179 |   8631 |00:02:59.42 |   99470 |  40095 |      0 |  4379K|  1869K|     1/0/0|         |
    |*  9 |          HASH JOIN                            |                           |      1 |    179 |   8631 |00:02:59.15 |   98919 |  40067 |      0 |   909K|   909K|     1/0/0|         |
    |  10 |           TABLE ACCESS FULL                   | DIM_PERFORMANCE           |      1 |      5 |      5 |00:00:00.01 |       2 |      0 |      0 |       |       |          |         |
    |  11 |           NESTED LOOPS OUTER                  |                           |      1 |    179 |   8631 |00:02:59.06 |   98917 |  40067 |      0 |       |       |          |         |
    |  12 |            NESTED LOOPS                       |                           |      1 |    179 |   8631 |00:02:58.87 |   98917 |  40067 |      0 |       |       |          |         |
    |* 13 |             HASH JOIN                         |                           |      1 |    191 |   8758 |00:00:25.47 |   18101 |   2398 |      0 |  1000K|  1000K|     1/0/0|         |
    |  14 |              TABLE ACCESS FULL                | DIM_TYP_FLUIDE            |      1 |      3 |      3 |00:00:00.01 |       2 |      0 |      0 |       |       |          |         |
    |* 15 |              HASH JOIN                        |                           |      1 |    191 |   8758 |00:00:25.32 |   18099 |   2398 |      0 |   955K|   955K|     1/0/0|         |
    |  16 |               TABLE ACCESS FULL               | DIM_TYP_PDC               |      1 |      3 |      3 |00:00:00.01 |       2 |      0 |      0 |       |       |          |         |
    |  17 |               NESTED LOOPS                    |                           |      1 |        |   8758 |00:00:25.19 |   18097 |   2398 |      0 |       |       |          |         |
    |  18 |                NESTED LOOPS                   |                           |      1 |    191 |   8758 |00:00:06.46 |    9339 |    315 |      0 |       |       |          |         |
    |* 19 |                 HASH JOIN                     |                           |      1 |    191 |   8758 |00:00:00.67 |     565 |      0 |      0 |   880K|   880K|     1/0/0|         |
    |  20 |                  TABLE ACCESS FULL            | DIM_OFFRE                 |      1 |     22 |     22 |00:00:00.01 |       2 |      0 |      0 |       |       |          |         |
    |* 21 |                  HASH JOIN                    |                           |      1 |    191 |   8758 |00:00:00.53 |     563 |      0 |      0 |   779K|   779K|     1/0/0|         |
    |  22 |                   NESTED LOOPS                |                           |      1 |        |      1 |00:00:00.01 |       5 |      0 |      0 |       |       |          |         |
    |  23 |                    NESTED LOOPS               |                           |      1 |      1 |      1 |00:00:00.01 |       4 |      0 |      0 |       |       |          |         |
    |* 24 |                     TABLE ACCESS FULL         | DIM_CONTRAT               |      1 |      1 |      1 |00:00:00.01 |       3 |      0 |      0 |       |       |          |         |
    |* 25 |                     INDEX UNIQUE SCAN         | PK_CONTRACTANT_KEY        |      1 |      1 |      1 |00:00:00.01 |       1 |      0 |      0 |       |       |          |         |
    |* 26 |                    TABLE ACCESS BY INDEX ROWID| DIM_CONTRACTANT           |      1 |      1 |      1 |00:00:00.01 |       1 |      0 |      0 |       |       |          |         |
    |  27 |                   TABLE ACCESS FULL           | REL_SERVICE_POINT_CONTRAT |      1 |  54923 |  54923 |00:00:00.14 |     558 |      0 |      0 |       |       |          |         |
    |* 28 |                 INDEX UNIQUE SCAN             | PK_SP_KEY                 |   8758 |      1 |   8758 |00:00:05.66 |    8774 |    315 |      0 |       |       |          |         |
    |  29 |                TABLE ACCESS BY INDEX ROWID    | DIM_SERVICE_POINT         |   8758 |      1 |   8758 |00:00:18.58 |    8758 |   2083 |      0 |       |       |          |         |
    |  30 |             PARTITION RANGE SINGLE            |                           |   8758 |      1 |   8631 |00:02:33.32 |   80816 |  37669 |      0 |       |       |          |         |
    |* 31 |              TABLE ACCESS BY LOCAL INDEX ROWID| FAC_DAILY_TRANS_PERFORM   |   8758 |      1 |   8631 |00:02:33.18 |   80816 |  37669 |      0 |       |       |          |         |
    |* 32 |               INDEX RANGE SCAN                | IDX3_FAC_DAY_TRAN_PERF    |   8758 |      6 |    103K|00:00:16.05 |   17929 |   4751 |      0 |       |       |          |         |
    |  33 |            TABLE ACCESS BY INDEX ROWID        | DIM_DIAGNOSYS             |   8631 |      1 |      0 |00:00:00.12 |       0 |      0 |      0 |       |       |          |         |
    |* 34 |             INDEX UNIQUE SCAN                 | PK_DIAGNOSYS_KEY          |   8631 |      1 |      0 |00:00:00.05 |       0 |      0 |      0 |       |       |          |         |
    |  35 |          TABLE ACCESS FULL                    | DIM_DATE                  |      1 |  21914 |  21914 |00:00:00.05 |     551 |     28 |      0 |       |       |          |         |
    |  36 |         TABLE ACCESS BY INDEX ROWID           | DIM_RADIO_MODULE          |   8631 |      1 |   8631 |00:00:32.65 |   25895 |   6330 |      0 |       |       |          |         |
    |* 37 |          INDEX UNIQUE SCAN                    | PK_RADMODKEY              |   8631 |      1 |   8631 |00:00:08.38 |   17264 |   2122 |      0 |       |       |          |         |
    |  38 |        TABLE ACCESS BY INDEX ROWID            | DIM_METER_MODULE          |   8631 |      1 |   8631 |00:00:31.51 |   25895 |   6503 |      0 |       |       |          |         |
    |* 39 |         INDEX UNIQUE SCAN                     | PK_METMODKEY              |   8631 |      1 |   8631 |00:00:10.17 |   17264 |   2212 |      0 |       |       |          |         |
    |  40 |       TABLE ACCESS BY INDEX ROWID             | DIM_CUSTOMER              |   8631 |      1 |   8631 |00:01:09.66 |   25895 |   8468 |      0 |       |       |          |         |
    |* 41 |        INDEX UNIQUE SCAN                      | PK_CUSTOMER               |   8631 |      1 |   8631 |00:00:12.03 |   17264 |   2328 |      0 |       |       |          |         |
    |* 42 |      INDEX UNIQUE SCAN                        | PK_METER                  |   8631 |      1 |   8631 |00:00:09.63 |   17264 |   2372 |      0 |       |       |          |         |
    |  43 |     TABLE ACCESS BY INDEX ROWID               | DIM_METER                 |   8631 |      1 |   8631 |00:00:30.71 |    8631 |   5369 |      0 |       |       |          |         |
    --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
     
    Predicate Information (identified by operation id):
    ---------------------------------------------------
     
       8 - access("T786"."DATE_KEY"="T1830"."DATE_KEY")
       9 - access("T786"."PERFORMANCE_KEY"="T2158"."PERFORMANCE_KEY")
      13 - access("T160"."FLUIDE_KEY"="T210"."FLUIDE_KEY")
      15 - access("T160"."TYP_PDC_KEY"="T217"."TYP_PDC_KEY")
      19 - access("T122"."OFFRE_KEY"="T298"."OFFRE_KEY")
      21 - access("T24"."CONTRAT_KEY"="T298"."CONTRAT_KEY" AND "T17"."CONTRACTANT_KEY"="T298"."CONTRACTANT_KEY")
      24 - filter("T24"."NOM_CONTRAT"='COMMUNAY ET REGION (SIE)')
      25 - access("T17"."CONTRACTANT_KEY"="T24"."CONTRACTANT_KEY")
      26 - filter("T17"."NOM_CONTRACTANT"='ER Rhône Alpes Auvergne')
      28 - access("T160"."SERVICE_POINT_KEY"="T298"."SERVICE_POINT_KEY")
      31 - filter("T786"."REPORTING_DATE"=TO_DATE(' 2013-02-09 00:00:00', 'syyyy-mm-dd hh24:mi:ss'))
      32 - access("T160"."SERVICE_POINT_KEY"="T786"."SERVICE_POINT_KEY")
      34 - access("T786"."DIAGNOSYS_KEY"="T2186"."DIAGNOSYS_KEY")
      37 - access("T786"."RADIO_MODULE_KEY"="T949"."RADIO_MODULE_KEY")
      39 - access("T786"."METER_MODULE_KEY"="T1191"."METER_MODULE_KEY")
      41 - access("T786"."CUSTOMER_KEY"="T2098"."CUSTOMER_KEY")
      42 - access("T786"."METER_KEY"="T1011"."METER_KEY")
     
    Also, line 31, my score is used with a local index and E-lines and A-lines are correct, but the index takes 02:33 minutes to get a 8758 ranks who seems to be excessive. EC which could I check/do to reduce it?
    |  30 |             PARTITION RANGE SINGLE            |                           |   8758 |      1 |   8631 |00:02:33.32 |   80816 |  37669 |      0 |       |       |          |         |
    |* 31 |              TABLE ACCESS BY LOCAL INDEX ROWID| FAC_DAILY_TRANS_PERFORM   |   8758 |      1 |   8631 |00:02:33.18 |   80816 |  37669 |      0 |       |       |          |         |
    Thank you very much!

    Hello

    (1) for a significant query, it is rare that the optimizer obtains all right cardinalities
    (2) but normally, it is not really necessary, in most cases just to be in the right ballpark (1-2 orders of magnitude)
    (3) as others already said, the optimizer in your case does that 1 error - in step 1, when evaluating a cardinality of a hash of several columns, the steps join upward simply reproduce this error over and over
    (4) rethink the cardinality of the join is always difficult, and especially when it comes to columns multiple joins because you have several possibilities made a mistake in the selectivity of unique columns, but also because there is a chance that there is a correlation between the columns attached; also, the optimizer uses many settings, called 'mental health controls', which does not make things more simple
    (5) you can try to create statistics on a column in the joined columns group for a more accurate forecast of join cardinality
    (6) there again, get all the cardinalities right does not guarantee that you will get a good plan - for example, you may be limited by the lack of an appropriate index
    (7) sometimes, and more feedback of cardinality (or even instead) it is better to tackle the problem from a different angle: see what operations are ineffective (e.g. rejection lines after spending a lot of e/s on their acquisition), see http://savvinov.com/2013/01/28/efficiency-based-sql-tuning/
    (8) in your case, you have noticed that you: step

    |* 31 |              TABLE ACCESS BY LOCAL INDEX ROWID| FAC_DAILY_TRANS_PERFORM   |   8758 |      1 |   8631 |00:02:33.18 |   80816 |  37669 |      0 |       |       |          |  
    

    is the biggest problem for this plan, even if the cardinality estimate of it's very precise
    (9) you can fix the problem by extending the IDX3_FAC_DAY_TRAN_PERF index to the REPORTING_DATE column: If you do this, then you won't need to 63 k logical reads to return lines k 103 just to reject 90% of them - you will reject them at an earlier stage (INDEX RANGE SCAN) and only need to at most 8 k readings to acquire the filtered lines by table rowid

    Best regards
    Nikolai

  • Write a SQL query with lines in columns

    All the

    I need help in writing a SQL query with lines in columns, let give u an example...

    drop table activity;

    CREATE TABLE 'ACTIVITY '.

    (

    "PROJECT_WID" NUMBER (22.0) NOT NULL,

    VARCHAR2 (150 CHAR) "PROJECT_NO."

    VARCHAR2 (800 CHAR) 'NAME '.

    );

    Insert in the ACTIVITY (PROJECT_WID, PROJECT_NO, NAME) values (1683691, '10007', 12-121');

    Insert in the ACTIVITY (PROJECT_WID, PROJECT_NO, NAME) values (1684994, '10008', 12-122');

    Insert in the ACTIVITY (PROJECT_WID, PROJECT_NO, NAME) values (1686296, '10009', 12-123');

    Insert in the ACTIVITY (PROJECT_WID, PROJECT_NO, NAME) values (2225222, '9040', 12-124');

    drop table lonet;

    CREATE TABLE 'LONET.

    (

    VARCHAR2 (150 CHAR) "NAME."

    NUMBER OF THE "ROOT."

    VARCHAR2 (150 CHAR) "ENTRYVALUE".

    );

    INSERT INTO LONET (NAME, ROOT, ENTRYVALUE) VALUES ("GAC", 1683691, "LDE");

    INSERT INTO LONET (NAME, ROOT, ENTRYVALUE) VALUES ('NAM', 1683691, 'LME');

    INSERT INTO LONET (NAME, ROOT, ENTRYVALUE) VALUES ('BAG', 1683691, 'ICE');

    INSERT INTO LONET (NAME, ROOT, ENTRYVALUE) VALUES ('PAP', 1683691, 'IKE');

    INSERT INTO LONET (NAME, ROOT, ENTRYVALUE) VALUES ('NAM', 1686291, "QTY");

    INSERT INTO LONET (NAME, ROOT, ENTRYVALUE) VALUES ('PAP', 1686291, 'MAX');

    INSERT INTO LONET (NAME, ROOT, ENTRYVALUE) VALUES ("GAC", 1684994, "MTE");

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    INSERT INTO LONET (NAME, ROOT, ENTRYVALUE) VALUES ('FMT', 1684994, 'NICE');

    INSERT INTO LONET (NAME, ROOT, ENTRYVALUE) VALUES ('FMR', 1684994, 'RAY');

    INSERT INTO LONET (NAME, ROOT, ENTRYVALUE) VALUES ('BAG', 1686296, "CAQ");

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    INSERT INTO LONET (NAME, ROOT, ENTRYVALUE) VALUES ("ANDR", 1686296, "REYL");

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    look like output

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    16836911000712-121LDELMELCELKE
    16849941000812-122MTEnullnullMAC
    16862961000912-123nullnullCAQQAQ
    2225222904012-124nullnullnullnull

    two problems, in that I am running

    1. I dono how simply we can convert rows to columns

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    ask for your help in this

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    Hello

    This is called pivoting.

    Here's a way to do it:

    WITH relevant_data AS

    (

    SELECT a.project_wid, a.project_no, b.SID

    , l.name AS lonet_name, l.entryvalue

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    LEFT OUTER JOIN lonet l.root = a.project_wid l

    )

    SELECT *.

    OF relevant_data

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    FOR lonet_name IN ("GAC" IN the gac

    "NAM" AS nam

    'BAG' IN the bag

    "RAC" AS cars

    )

    )

    ORDER BY project_wid

    ;

    Output:

    PROJECT_WID PROJECT_NO GAC NAM BAG RAC NAME

    ----------- ---------- ---------- ---------- ---------- ---------- ----------

    1683691 12 - 10007 121 LDE LME LCE LKE

    1684994 MAC MTE 10008 12-122

    1686296 12 - 10009 123 QAC QAQ

    2225222 9040 12 - 124

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    to reproduce this problem:

    1. create a test application simulating recording in real time on the screen. For example, create a new GUI application (for example, in visual basic, delphi, etc.), several (for example six) textbox, control and set multiline = true (or use TMemo components in delphi), add the button and code to add rows in a loop (for example 200 iterations) these textbox/TMemo controls (see the sample code below). Build the executable

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    Windows 2000 seems to be ok, xp, 7, Server 2003/2008 have some problems

    is there something that we could do to make the third-party application with real-time logging to the multiline/TMemo text box does not slow down or suspend our services that are running on the same PC, when someone connect via RDP? also, it would be great if microsoft could fix this problem

    example code:

    For i As Integer = 1 to 200
    Dim s As String = «»
    J As Integer = 1 to 10
    Convert.ToString (i) & s = s & ""
    Next J
    TextBox1.AppendText (s & Chr (13) & 10)

    J As Integer = 1 to 10
    Convert.ToString (i) & s = s & ""
    Next J
    TextBox2.AppendText (s & Chr (13) & 10)

    J As Integer = 1 to 10
    Convert.ToString (i) & s = s & ""
    Next J
    TextBox3.AppendText (s & Chr (13) & 10)

    J As Integer = 1 to 20
    Convert.ToString (i) & s = s & ""
    Next J
    TextBox4.AppendText (s & Chr (13) & 10)

    J As Integer = 1 to 20
    Convert.ToString (i) & s = s & ""
    Next J
    TextBox5.AppendText (s & Chr (13) & 10)

    J As Integer = 1 to 20
    Convert.ToString (i) & s = s & ""
    Next J
    TextBox6.AppendText (s & Chr (13) & 10)
    Next I

    var
    i: Integer;
    s:string;
    Start
    for i: = 1 to 200 start
    s:='';
    While length<20 do="" s:="s+intToStr(i)+'">
    glMemo1.Lines.Add (s);

    While length<40 do="" s:="s+intToStr(i)+'">
    glMemo2.Lines.Add (s);

    While length<60 do="" s:="s+intToStr(i)+'">
    glMemo3.Lines.Add (s);

    While length<80 do="" s:="s+intToStr(i)+'">
    glMemo4.Lines.Add (s);

    While length<100 do="" s:="s+intToStr(i)+'">
    glMemo5.Lines.Add (s);

    While length<200 do="" s:="s+intToStr(i)+'">
    glMemo6.Lines.Add (s);
    end;

    Thank you
    Paulius

    http://social.technet.Microsoft.com/forums/en-us/itproxpsp/threads

    you might do better at the forum above. Good luck. :)

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