10.2.0.4 for "non-mainstream" platforms - release date?

According to
SAP on Oracle
--> SAP on Oracle Development Update
patch 10.2.0.4 for non-mainstream platforms (Windows IA64, Linux IA64 etc.) was to be released "in August", now we have mid september and patches are still not available.
Any idea why this is postponed and if there is a new date?
Markus

lol
If that was true then it´s even more ununderstandable, that the "mainstream platforms" are already released
Markus

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                 28             49
                 29             50
                 30             51
                 32             52
                 33             53
    ENDPOINT_NUMBER ENDPOINT_VALUE
                 34             54
                 35             55
                 37             56
                 38             57
                 39             58
                 41             59
                 42             60
                 43             61
                 45             62
                 46             63
                 48             64
    ENDPOINT_NUMBER ENDPOINT_VALUE
                 49             65
                 51             66
                 52             67
                 54             68
                 56             69
                 57             70
                 59             71
                 60             72
                 62             73
                 64             74
                 66             75
    ENDPOINT_NUMBER ENDPOINT_VALUE
                 67             76
                 69             77
                 71             78
                 73             79
                 75             80
    60 rows selected.Checking the selectivity for value 75(which is the popular value as per information from dba_tab_histograms
    SQL> set autotrace on
    SQL> select count(*) from t1 where skew=75;
      COUNT(*)
            75
    Execution Plan
    Plan hash value: 4273422929
    | Id  | Operation         | Name  | Rows  | Bytes | Cost (%CPU)| Time     |
    |   0 | SELECT STATEMENT  |       |     1 |     3 |     1   (0)| 00:00:01 |
    |   1 |  SORT AGGREGATE   |       |     1 |     3 |            |          |
    |*  2 |   INDEX RANGE SCAN| T1_I1 |    86 |   258 |     1   (0)| 00:00:01 |
    Predicate Information (identified by operation id):
       2 - access("SKEW"=75)Skipped the Statistics information for keep example short.
    selectivity for 75 (popular value) = 2/75 = 0.02666
    Cardinality for 75 is = selectivity * num_rows = 0.02666*3240 = 86.3784 (rounded to 86) >> Here selectivity and cardinality are correct and displayed in autotrace.
    SQL> select count(*) from t1 where skew=8;
      COUNT(*)
             8
    Execution Plan
    Plan hash value: 4273422929
    | Id  | Operation         | Name  | Rows  | Bytes | Cost (%CPU)| Time     |
    |   0 | SELECT STATEMENT  |       |     1 |     3 |     1   (0)| 00:00:01 |
    |   1 |  SORT AGGREGATE   |       |     1 |     3 |            |          |
    |*  2 |   INDEX RANGE SCAN| T1_I1 |    29 |    87 |     1   (0)| 00:00:01 |
    Predicate Information (identified by operation id):
       2 - access("SKEW"=8)how the cardinality is 29 calculated. I think the formula for selectivity is
    select for 1(non popular value) = density * num_rows = .013973812 * num_rows (which is 45 approx) but in autotrace its 29
    SQL> select count(*) from t1 where skew = 46;
      COUNT(*)
            46
    Execution Plan
    Plan hash value: 4273422929
    | Id  | Operation         | Name  | Rows  | Bytes | Cost (%CPU)| Time     |
    |   0 | SELECT STATEMENT  |       |     1 |     3 |     1   (0)| 00:00:01 |
    |   1 |  SORT AGGREGATE   |       |     1 |     3 |            |          |
    |*  2 |   INDEX RANGE SCAN| T1_I1 |    29 |    87 |     1   (0)| 00:00:01 |
    Predicate Information (identified by operation id):
       2 - access("SKEW"=46)46 is also non popular value
    So how the value is calculated for these values?

    Your example seems to be based on Jonathan Lewis's article:
    http://jonathanlewis.wordpress.com/2012/01/03/newdensity/
    In this article, he does walk through the calculation of selectivity for non-popular values.
    The calculation is not density but NewDensity, as seen in a 10053 trace, which takes into account the number of non-popular values AND the number of non-popular buckets
    The article describes exactly how 29 is derived.Hi Dom,
    Yes i used the same sample script of create the data sets. I should have checked Jonathan's blog for new density calculations. So selectivity works out as two either ways
    1) selectivity(non popular) = Newdensity(took from 10053 traces) * rum_rows
    or
    2) non-popular rows/ non_popular values (where non-popular values can be derived from 10053 traces and non popular rows are (3240 * (74-31)/74 = ) 1883
    Thanks for pointing to right blog

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