Hi Experts, the result of a table content in se16n?

Hi Experts,
in the ALV output of se16n, some columns are in green, what does this stand for? thanks.
Kind regards
Dawson

Hi Sudhakar,
Could you please give a detail info for this? becasue I haven't found the path you mentioned, normal display -> utilities -> color legend, where is the path? thanks in advance!
Kind regards
Dawson

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  • Execute a VO '4' times and show the result in single table at once.

    Hi,
    I want to execute single a VO query multiple times with different parameters and show the results together in a Table at once
    In Detail
    I have a table to which is associated with a VO.
    The VO contains SQL whose WhereClauseParameters need to be dynamically binded.say headerId and lineId
    Select ... from ....where headerId = :1 AND lineId = :2
    I have to pass these 4 values and show all the results in a single table
    headerId lineid
    H1 ............... L1
    H1 ............... L2
    H2 ............... L1
    H2 ............... L2
    I understand that i need to bind parameters dynamically and exceute the VO.
    As i have 4 different set of parameters, the view object will be executed 4 times.
    I want to show all the results together in a single table.
    How can I do it.
    thanks,
    Gowtam

    Hi Mani,
    Thanks a lot for the patience and detailed solution.I will try it out and tell you the status.
    Meanwhile, I have 2 questions on this solution(just curious)
    I will give you the snapshot of the table
    Table - ModelInfo
    Model......Tube..... Float....Size......Col5.....Col6.......Col7.......
    M1............T1.......... F1. .....1..........C15......C16.....C17.....
    M1............T1...........F1.......2..........C25......C26.....C27.....
    M1............T2......... .F2.......1..........C35......C36.....C37.....
    M1............T2...........F2.......2..........C45......C46.....C47.....
    M2............T1.......... F1. .....1..........
    M2.............T1..........F1.....2.........Cn5.......Cn6........Cn7
    .<continues...>
    .<till>
    .Mn............Tn..........Fn.......n........Cxy.......Cpq.......Crs....
    Question 1:
    if you notice this data,
    The Columns 5 to 7 are dependent on Combination of Model,Tube,Float and Size.
    Hence will this query work properly(without mixing up data from other Pk combination) and will it be efficient?(I Know this is a stupid qst, still double checking..As your solution assumes that each row is unique for Model only..which is not true)
    Select ...From....Where
    Model in(M1,M2,..Mn) AND Tube in(T1,T2..Tn) AND Float in(F1,F2,....Fn) and Size in(1,2...n).
    In short, will C15,C16 and C17 appear only with M1,T1,F1,1..I believe it will.
    Question 2:
    As I told,
    Third party program will return Array of Objects.
    Each object will have a variable called Flow along with
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    Third Party object : ObjModel
    Model......Tube..... Float....Size......Flow
    M1............T1.......... F1. .....1..........100
    M1............T1...........F2.......2...........200.
    M1............T2.......... F1.......1..........300
    M1............T2...........F2.......2..........400
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    Task2:Showing Transient data for each object returned from program.
    thanks,
    Gowtam

  • Shouldn't using WITH return the same results as if you'd put the results in a table first?

    First off, here's my version info:
    BANNER
    Oracle Database 11g Enterprise Edition Release 11.1.0.7.0 - 64bit Production
    PL/SQL Release 11.1.0.7.0 - Production
    CORE 11.1.0.7.0 Production
    TNS for HPUX: Version 11.1.0.7.0 - Production
    NLSRTL Version 11.1.0.7.0 - Production
    I just reread the documentation again on the subquery factoring clause of SELECT statement, and I didn't see any restrictions that would apply.
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    Sorry if the example seems a little esoteric.  I was trying to put something together to help illustrate another problem, so it was convenient to use the same statements to illustrate this problem.
    drop table mat1;
    create table mat1 as
    with skus as (
      select level as sku_id
      from dual
      connect by level <= 1000
      tran_dates as (
      select to_date('20130731', 'yyyymmdd') + level as tran_date
      from dual
      connect by level <= 31
      sku_dates as (
      select s.sku_id,
      t.tran_date,
      case when dbms_random.value * 5 < 4
      then 0
      else 1
      end as has_changes,
      round(dbms_random.value * 10000, 2) as unit_cost
      from skus s
      inner join tran_dates t
      on 1 = 1
    select d.sku_id,
      d.tran_date,
      d.unit_cost
      from sku_dates d
      where d.has_changes = 1
    drop table mat2;
    create table mat2 as
    select m.sku_id,
      m.tran_date,
      m.unit_cost,
      min(m.tran_date) over (partition by m.sku_id order by m.tran_date rows between 1 following and 1 following) as next_tran_date
      from mat1 m
    drop table mat3;
    create table mat3 as
    with skus as (
      select level as sku_id
      from dual
      connect by level <= 1000
      tran_dates as (
      select to_date('20130731', 'yyyymmdd') + level as tran_date
      from dual
      connect by level <= 31
      sku_dates as (
      select s.sku_id,
      t.tran_date,
      case when dbms_random.value * 5 < 4
      then 0
      else 1
      end as has_changes,
      round(dbms_random.value * 10000, 2) as unit_cost
      from skus s
      inner join tran_dates t
      on 1 = 1
      tmp as (
      select d.sku_id,
      d.tran_date,
      d.unit_cost
      from sku_dates d
      where d.has_changes = 1
    select m.sku_id,
      m.tran_date,
      m.unit_cost,
      min(m.tran_date) over (partition by m.sku_id order by m.tran_date rows between 1 following and 1 following) as next_tran_date
      from tmp m
    select count(*) from mat2;
    select count(*) from mat3;
      from tmp m
    select count(*) from mat2;
    select count(*) from mat3;
    select count(*) from mat2;
      COUNT(*)
         31000
    Executed in 0.046 seconds
    select count(*) from mat3;
      COUNT(*)
             0
    Executed in 0.031 seconds

    I think there's something else going on.
    I made the change you suggested, with a slight modification to retain the same functionality of flagging ~80% of the rows as not having changes.  I then copied that section of my script - included below - and pasted it into my session twice.  Unfortunately, I got different results each time.  I have had a number of strange problems when using the WITH clause, which is one of the reasons I jumped at posting something here when I encountered it again in this context.
    Can you help me understand why this would happen?
    drop table mat3;
    create table mat3 as
    with skus as (
      select level as sku_id
      from dual
      connect by level <= 1000
      tran_dates as (
      select to_date('20130731', 'yyyymmdd') + level as tran_date
      from dual
      connect by level <= 31
      sku_dates as (
      select s.sku_id,
      t.tran_date,
      case when dbms_random.value(1,100) * 5 < 400
      then 0
      else 1
      end as has_changes,
      round(dbms_random.value * 10000, 2) as unit_cost
      from skus s
      inner join tran_dates t
      on 1 = 1
      tmp as (
      select d.sku_id,
      d.tran_date,
      d.unit_cost
      from sku_dates d
      where d.has_changes = 1
    select m.sku_id,
      m.tran_date,
      m.unit_cost,
      min(m.tran_date) over (partition by m.sku_id order by m.tran_date rows between 1 following and 1 following) as next_tran_date
      from tmp m
    select count(*) from mat2;
    select count(*) from mat3;
    152249 < mattk > drop table mat3;
    Table dropped
    Executed in 0.016 seconds
    152249 < mattk > create table mat3 as
                             2  with skus as (
                             3   select level as sku_id
                             4   from dual
                             5   connect by level <= 1000
                             6   ),
                             7   tran_dates as (
                             8   select to_date('20130731', 'yyyymmdd') + level as tran_date
                             9   from dual
                            10   connect by level <= 31
                            11   ),
                            12   sku_dates as (
                            13   select s.sku_id,
                            14   t.tran_date,
                            15   case when dbms_random.value(1,100) * 5 < 400
                            16   then 0
                            17   else 1
                            18   end as has_changes,
                            19   round(dbms_random.value * 10000, 2) as unit_cost
                            20   from skus s
                            21   inner join tran_dates t
                            22   on 1 = 1
                            23   ),
                            24   tmp as (
                            25   select d.sku_id,
                            26   d.tran_date,
                            27   d.unit_cost
                            28   from sku_dates d
                            29   where d.has_changes = 1
                            30   )
                            31  select m.sku_id,
                            32   m.tran_date,
                            33   m.unit_cost,
                            34   min(m.tran_date) over (partition by m.sku_id order by m.tran_date rows between 1 following and 1 following) as next_tran_date
                            35   from tmp m
                            36  ;
    Table created
    Executed in 0.53 seconds
    152250 < mattk > select count(*) from mat2;
      COUNT(*)
             0
    Executed in 0.047 seconds
    152250 < mattk > select count(*) from mat3;
      COUNT(*)
         31000
    Executed in 0.047 seconds
    152250 < mattk >
    152251 < mattk > drop table mat3;
    Table dropped
    Executed in 0.016 seconds
    152252 < mattk > create table mat3 as
                             2  with skus as (
                             3   select level as sku_id
                             4   from dual
                             5   connect by level <= 1000
                             6   ),
                             7   tran_dates as (
                             8   select to_date('20130731', 'yyyymmdd') + level as tran_date
                             9   from dual
                            10   connect by level <= 31
                            11   ),
                            12   sku_dates as (
                            13   select s.sku_id,
                            14   t.tran_date,
                            15   case when dbms_random.value(1,100) * 5 < 400
                            16   then 0
                            17   else 1
                            18   end as has_changes,
                            19   round(dbms_random.value * 10000, 2) as unit_cost
                            20   from skus s
                            21   inner join tran_dates t
                            22   on 1 = 1
                            23   ),
                            24   tmp as (
                            25   select d.sku_id,
                            26   d.tran_date,
                            27   d.unit_cost
                            28   from sku_dates d
                            29   where d.has_changes = 1
                            30   )
                            31  select m.sku_id,
                            32   m.tran_date,
                            33   m.unit_cost,
                            34   min(m.tran_date) over (partition by m.sku_id order by m.tran_date rows between 1 following and 1 following) as next_tran_date
                            35   from tmp m
                            36  ;
    Table created
    Executed in 0.078 seconds
    152252 < mattk > select count(*) from mat2;
      COUNT(*)
             0
    Executed in 0.031 seconds
    152252 < mattk > select count(*) from mat3;
      COUNT(*)
             0
    Executed in 0.047 seconds

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    Attachments:
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          7369 SPENCER    CLERK           7902 17-DEC-80        800                    20
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          7782 BOEHMER    MANAGER         7839 09-JUN-81       2695                    10
          7788 PADFIELD   ANALYST         7566 09-DEC-82       3000                    20
          7839 SCHNEIDER  PRESIDENT            17-NOV-81       5500                    10
          7844 GASPAROTTO SALESMAN        7698 08-SEP-81       1500          0         30
          7876 CAVE       CLERK           7788 12-JAN-83       1100                    20
          7900 CLARKE     CLERK           7698 03-DEC-81        950                    30
          7902 JAFFAR     ANALYST         7566 03-DEC-81       3000                    20
          7934 ROBERTSON  CLERK           7782 23-JAN-82       1430                    10
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      endif.
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      call function 'VIEW_MAINTENANCE_CALL'
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          action                               = 'U'
          view_name                            = p_tabnm
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         foreign_lock                         = 2
         invalid_action                       = 3
         no_clientindependent_auth            = 4
         no_database_function                 = 5
         no_editor_function                   = 6
         no_show_auth                         = 7
         no_tvdir_entry                       = 8
         no_upd_auth                          = 9
         only_show_allowed                    = 10
         system_failure                       = 11
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                    where tabname = p_tabnm.
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    Seshu

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    Hi,
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    Receipt
    Sys_id10
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    Category
    1001
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    1002
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    AMB
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