combining two tables

Hello

I have a while loop that runs trough each case in a box structure. Each of these cases produced a 1 d table. How can I combine these tables in a 2d array. An attempt with two cases is attempted in the attached diagram.

The problem is it seems to fill the first column with zeroes when you add the second row in table

Hi Jagwa,

first: use a registry to offset instead of tunnels. In this way, the result of the first iteration is not lost in the 2nd

"It seems to fill the first column with zeroes" - no, just the table of origin once again, but now by replacing the second row!

2nd:

When your loop runs twice, all the time why not use a FOR loop instead? No need to check for "I".<>

Tags: NI Software

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    OK, now you give other useful information - that there always will be combinations of amounts in table2 to match values in table1. (It is difficult to help when you say the specs one both :-))

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  7     select 123 id, 100 value from dual union all
  8     select 123 id, 50  value from dual union all
  9     select 123 id, 100 value from dual union all
 10     select 123 id, 100 value from dual union all
 11     select 123 id, 100 value from dual union all
 12     select 123 id, 100 value from dual
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 15  -- End of test data
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 28     ),0) minval,
 29     sum(tab1.value) over (
 30        partition by tab1.id
 31        order by tab1.rn
 32        rows between unbounded preceding and current row
 33     ) maxval
 34     from (
 35        select
 36        table1.*,
 37        row_number() over (
 38           partition by table1.id
 39           order by table1.value desc
 40        ) rn
 41        from table1
 42     ) tab1
 43  ) t1
 44  join (
 45     select
 46     tab2.*,
 47     sum(tab2.value) over (
 48        partition by tab2.id
 49        order by tab2.rn
 50     ) sumval
 51     from (
 52        select
 53        table2.*,
 54        row_number() over (
 55           partition by table2.id
 56           order by table2.value desc
 57        ) rn
 58        from table2
 59     ) tab2
 60  ) t2
 61  on (t2.id = t1.id)
 62  where t2.sumval > t1.minval
 63  and t2.sumval <= t1.maxval
 64  order by
 65  t1.id,
 66  t1.rn,
 67  t2.rn
 68  ;

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---------- -- ---------- ---------- ---------- ---------- ---------- ---------- ----------
       123 A3        300        100          1          0        300          1        100
       123 A3        300        100          1          0        300          2        200
       123 A3        300        100          1          0        300          3        300
       123 A2        200        100          2        300        500          4        400
       123 A2        200        100          2        300        500          5        500
       123 A1        150        100          3        500        650          6        600
       123 A1        150         50          3        500        650          7        650

7 rows selected.

    It doesn't seem to work for your sample data, but it is much too simple a rule at work in general. My "rule" is simply of sorts data according to the value descending and adding up to what 'enough' of values have been added.

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  2     select 'A1' name, 1 id, 100 value from dual union all
  3     select 'A2' name, 1 id, 200 value from dual union all
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  5     select 'B1' name, 2 id, 100 value from dual union all
  6     select 'B2' name, 2 id, 200 value from dual
  7  ), table2 as (
  8     select 1 id, 25  value from dual union all
  9     select 1 id, 75  value from dual union all
 10     select 1 id, 50  value from dual union all
 11     select 1 id, 50  value from dual union all
 12     select 1 id, 175 value from dual union all
 13     select 1 id, 225 value from dual union all
 14     select 2 id, 25  value from dual union all
 15     select 2 id, 50  value from dual union all
 16     select 2 id, 75  value from dual union all
 17     select 2 id, 100 value from dual union all
 18     select 2 id, 50  value from dual
 19  )
 20  --
 21  -- End of test data
 22  --
 23  select
 24  t1.id, t1.name, t1.value, t2.value,
 25  t1.rn, t1.minval, t1.maxval,
 26  t2.rn, t2.sumval
 27  from (
 28     select
 29     tab1.*,
 30     nvl(sum(tab1.value) over (
 31        partition by tab1.id
 32        order by tab1.rn
 33        rows between unbounded preceding and 1 preceding
 34     ),0) minval,
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 37        order by tab1.rn
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 41        select
 42        table1.*,
 43        row_number() over (
 44           partition by table1.id
 45           order by table1.value desc
 46        ) rn
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 50  join (
 51     select
 52     tab2.*,
 53     sum(tab2.value) over (
 54        partition by tab2.id
 55        order by tab2.rn
 56     ) sumval
 57     from (
 58        select
 59        table2.*,
 60        row_number() over (
 61           partition by table2.id
 62           order by table2.value desc
 63        ) rn
 64        from table2
 65     ) tab2
 66  ) t2
 67  on (t2.id = t1.id)
 68  where t2.sumval > t1.minval
 69  and t2.sumval <= t1.maxval
 70  order by
 71  t1.id,
 72  t1.rn,
 73  t2.rn
 74  ;

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---------- -- ---------- ---------- ---------- ---------- ---------- ---------- ----------
         1 A3        300        225          1          0        300          1        225
         1 A2        200        175          2        300        500          2        400
         1 A2        200         75          2        300        500          3        475
         1 A1        100         50          3        500        600          4        525
         1 A1        100         50          3        500        600          5        575
         1 A1        100         25          3        500        600          6        600
         2 B2        200        100          1          0        200          1        100
         2 B2        200         75          1          0        200          2        175
         2 B1        100         50          2        200        300          3        225
         2 B1        100         50          2        200        300          4        275
         2 B1        100         25          2        200        300          5        300

11 rows selected.

    In this data set simple ranking by value won't work - it should have been A3: (225,75), A2: (175,25) and A1: (50.50).

    I can't really think of a reasonably easy way to do this in SQL only. Maybe using the clause TYPE would be possible, but not negligible. It is possible, it would be easier to solve this problem in PL/SQL in iterating through a few tables and intelligently to try different combinations, rather than creating all combinations in a huge piece of brute force SQL.

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    select  A.col1, A.col2 as KEY_OLD, B.col5 as KEY_NEW
from    A, B
where (B.col1 = 'literal_1') and (B.col2 = 'literal_2') and (A.col1 = B.col3) and (A.col2 = B.col4)
    And now, I want to update this view and set KEY_OLD = KEY_NEW.

    Because of the first three conditions in the where clause for each entry in the table A there is just a matching entry in the table B.
    So the table should be preserved in the join key.

    But during the update
    update (select  A.col1, A.col2 as KEY_OLD, B.col5 as KEY_NEW
            from    A, B
            where (B.col1 = 'literal_1') and (B.col2 = 'literal_2') and (A.col1 = B.col3) and (A.col2 = B.col4)
           )
set     KEY_OLD = KEY_NEW;
    I get an error ORA-01779.

    I did the updates on inline views this way several times in recent weeks and it work very well.
    But so far the unique constraint on the table B was just a column ;-)

    So what I need is to make it work with the unique constraint on the application of the three-column table B.

    Thank you very much in advance for any help.

    Hartmut cordially

    Preserved key criteria must be met by the join columns, the optimizer does not agree (in fact I never tried in 11g) just a combination of columns, literals and join.

    The alternatives you have are subqueries online (which as you point out can do rather worse), the command MERGE or indicator BYPASS_UJVC semi undocumented.

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