function not returning with precision

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• NLSSORT function not used with CHAR and VARCHAR2 column index

  Hello!
  
  Create a test bench:

  CREATE TABLE scott.nls_demo
        (
        col_varchar            varchar2(4),
        col_char               char(4),
        col_varchar_NLS_GERMAN varchar2(4),
        col_char_NLS_GERMAN    char(4)
        );
   
  INSERT INTO scott.nls_demo (
        col_varchar,
        col_char,
        col_varchar_NLS_GERMAN,
        col_char_NLS_GERMAN  )
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           substr(object_name,1,4),
           substr(object_name,1,4),
           substr(object_name,1,4)
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  COMMIT; 
  
  create index scott.i_varchar on scott.nls_demo (col_varchar);  
  create index scott.i_char    on scott.nls_demo (col_char);
  
  create index scott.i_varchar_NLS_GERMAN on scott.nls_demo ( NLSSORT(col_varchar_NLS_GERMAN,'nls_sort=''GERMAN_CI'''));  
  create index scott.i_char_NLS_GERMAN    on scott.nls_demo ( NLSSORT(col_char_NLS_GERMAN,   'nls_sort=''GERMAN_CI'''));
   

  Now "explain plan" these 8 select statements in SQL * more:
  

  variable c char(4);
  variable v varchar2(4);
  
  exec :c:= 'abc';
  exec :v:= 'abc';
  
  explain plan for SELECT /* 1*/ * FROM scott.nls_demo where col_varchar=:v;
  SELECT * FROM TABLE(dbms_xplan.display);
  
  explain plan for SELECT /* 2*/ * FROM scott.nls_demo where col_char=:c;
  SELECT * FROM TABLE(dbms_xplan.display);
  
  explain plan for SELECT /* 3*/ * FROM scott.nls_demo where col_varchar_NLS_GERMAN=:v;
  SELECT * FROM TABLE(dbms_xplan.display);
  
  explain plan for SELECT /* 4*/ * FROM scott.nls_demo where col_char_NLS_GERMAN=:c;
  SELECT * FROM TABLE(dbms_xplan.display);
  
  ALTER SESSION SET NLS_COMP = linguistic;
  ALTER SESSION SET NLS_SORT = german_ci;
  
  explain plan for SELECT /* 5*/ * FROM scott.nls_demo where col_varchar=:v;
  SELECT * FROM TABLE(dbms_xplan.display);
  
  explain plan for SELECT /* 6*/ * FROM scott.nls_demo where col_char=:c;
  SELECT * FROM TABLE(dbms_xplan.display);
  
  explain plan for SELECT /* 7*/ * FROM scott.nls_demo where col_varchar_NLS_GERMAN=:v;
  SELECT * FROM TABLE(dbms_xplan.display);
  
  explain plan for SELECT /* 8*/ * FROM scott.nls_demo where col_char_NLS_GERMAN=:c;
  SELECT * FROM TABLE(dbms_xplan.display);
   

  What I see on 11.2.0.2 is:
  
  1.) statement 1 would use the I_VARCHAR index, that is what I expected.
  2.) statement 2 would use the I_CHAR index, that is what I expected.
  3.) no clue used, because none are available right here for you. Understood.
  4.) no clue used, because none are available right here for you. Understood.
  
  And when define us NLS_SORT = german_ci:
  
  5.) no clue used, because none are available right here for you. Understood.
  6.) no clue used, because none are available right here for you. Understood.
  7.) I_VARCHAR_NLS_GERMAN we used. Large.
  8.) no index used, although I think that "i_char_NLS_GERMAN" would do the job...
  
  Why the index 'i_char_NLS_GERMAN' is not used with the 8 statement? Jonathan? Someone else?
  
  Thanks for your help!
  Marcus

  Not really a reason to not use TANK - although there are many of them.

  More than one reason to not always rely to "explain the plan for?

  All the variables passed in EXPLAINING the PLAN for are treated as VARCHAR2.
  In addition, there is no point setting the values of the variable because they will not cast a look either with MAP to EXPLAIN.

  SQL> CREATE TABLE nls_demo
    2        (
    3        col_varchar            varchar2(4),
    4        col_char               char(4),
    5        col_varchar_NLS_GERMAN varchar2(4),
    6        col_char_NLS_GERMAN    char(4)
    7        );
  
  Table created.
  
  SQL>
  SQL> INSERT INTO nls_demo (
    2        col_varchar,
    3        col_char,
    4        col_varchar_NLS_GERMAN,
    5        col_char_NLS_GERMAN  )
    6    SELECT
    7           substr(object_name,1,4),
    8           substr(object_name,1,4),
    9           substr(object_name,1,4),
   10           substr(object_name,1,4)
   11    FROM all_objects where rownum<5000;
  
  4999 rows created.
  
  SQL>
  SQL> commit; 
  
  Commit complete.
  
  SQL>
  SQL> create index i_varchar on nls_demo (col_varchar);  
  
  Index created.
  
  SQL> create index i_char    on nls_demo (col_char);
  
  Index created.
  
  SQL>
  SQL> create index i_varchar_NLS_GERMAN on nls_demo ( NLSSORT(col_varchar_NLS_GERMAN,'nls_sort=''GERM
  AN_CI'''));  
  
  Index created.
  
  SQL> create index i_char_NLS_GERMAN    on nls_demo ( NLSSORT(col_char_NLS_GERMAN,   'nls_sort=''GERM
  AN_CI'''));
  
  Index created.
  
  SQL>
  SQL> variable c char(4);
  SQL> variable v varchar2(4);
  SQL>
  SQL> exec :c:= 'abc';
  
  PL/SQL procedure successfully completed.
  
  SQL> exec :v:= 'abc';
  
  PL/SQL procedure successfully completed.
  
  SQL>
  SQL> ALTER SESSION SET NLS_COMP = linguistic;
  
  Session altered.
  
  SQL> ALTER SESSION SET NLS_SORT = german_ci;
  
  Session altered.
  
  SQL>
  SQL> SELECT /* 8*/ * FROM nls_demo where col_char_NLS_GERMAN=:c;
  
  no rows selected
  
  SQL> SELECT * FROM TABLE(dbms_xplan.display_cursor);
  
  PLAN_TABLE_OUTPUT
  ----------------------------------------------------------------------------------------------------
  SQL_ID  9su0j5vzuwzyj, child number 0
  -------------------------------------
  SELECT /* 8*/ * FROM nls_demo where col_char_NLS_GERMAN=:c
  
  Plan hash value: 2830339923
  
  -------------------------------------------------------------------------------------------------
  | Id  | Operation                   | Name              | Rows  | Bytes | Cost (%CPU)| Time     |
  -------------------------------------------------------------------------------------------------
  |   0 | SELECT STATEMENT            |                   |       |       |     3 (100)|          |
  |   1 |  TABLE ACCESS BY INDEX ROWID| NLS_DEMO          |    50 |  2150 |     3   (0)| 00:00:01 |
  |*  2 |   INDEX RANGE SCAN          | I_CHAR_NLS_GERMAN |    20 |       |     1   (0)| 00:00:01 |
  -------------------------------------------------------------------------------------------------
  
  Predicate Information (identified by operation id):
  ---------------------------------------------------
  
     2 - access("NLS_DEMO"."SYS_NC00006$"=NLSSORT(:C,'nls_sort=''GERMAN_CI'''))
  
  Note
  -----
     - dynamic sampling used for this statement (level=2)
  
  23 rows selected.
  
  SQL> 
  

  Published by: Dom Brooks on February 21, 2011 15:39

• function not returning object table properly

  Rather than return a table, my function returns this:
  
  SCHEMA_OWNER. TBL_SUMS ([SCHEMA_OWNER. SUMS_OBJ])
  
  Did anyone see a syntax error in my function or the DOF of my table and object types?
  
  It is a stripped down, simplified version of my function:
  
  create or replace FUNCTION "F_TEST" (number of p_skey, p_start_date date, p_end_date date)
  RETURN tbl_sums
  
  IS
  
  tmp_A NUMBER;
  tmp_B NUMBER;
  
  l_tbl tbl_sums: = tbl_sums();
  
  BEGIN
  
  SELECT SUM (FieldA), SUM (FieldB)
  in tmpA, tmpB
  FROM MaTable where SKEY = p_skey
  and DATE_VALUE > = p_start_date
  and DATE_VALUE < p_end_date;.
  
  l_tbl.extend;
  l_tbl (l_tbl. (Count()): = sums_obj (p_start_date, p_end_date, p_skey, tmpA, tmpB);
  Return l_tbl;
  
  END;
  
  My models are:
  
  create or replace type sums_obj is object (DATE start_date, end_date DATE, skey NUMBER, SumA, SumB NUMBER);
  create or replace type tbl_sums is table of the sums_obj;
  
  
  Thank you!

  >
  RETURN tbl_kpi
  >
  What is 'tbl_kpi '? Which is not defined anywhere. Your original post said:
  >
  RETURN tbl_sums
  >
  We cannot help you if you don't publish what you actually use. Cut & paste is ok, but you have to paste the correct code.

  Your function returns a TABLE, but it is NOT in the PIPELINE. For example, if you query the DOUBLE function you will get a DATASET as a result.

  If you query the function AS A TABLE, you will get the "content" of the table.

  If you make your function a PIPELINED function then you use PIPE ROW to return each line but the function is always declared to return a TABLE. This is perhaps what is confusing you.

  Try the following code to see what the difference is.

  Here are two SQL types based on the EMP table in the scott schema.

  -- type to match emp record
  create or replace type emp_scalar_type as object
    (EMPNO NUMBER(4) ,
     ENAME VARCHAR2(10),
     JOB VARCHAR2(9),
     MGR NUMBER(4),
     HIREDATE DATE,
     SAL NUMBER(7, 2),
     COMM NUMBER(7, 2),
     DEPTNO NUMBER(2)
    )
    /
  
  -- table of emp records
  create or replace type emp_table_type as table of emp_scalar_type
  /
  

  Now - here's a function (similar to yours) that returns him EMP_TABLE_TYPE. NOTE: the function IS NOT PIPELINED

  CREATE OR REPLACE function SCOTT.get_emp1( p_deptno in number )
    return emp_table_type
    as
  tb emp_table_type;
  BEGIN
    select emp_scalar_type(empno, ename, job, mgr, hiredate, sal, comm, deptno)
      bulk collect into tb from emp where deptno = p_deptno;
    return tb;
  end;
  /
  

  If I simply select the function itself twice I get this:

  select get_emp1(20) from dual
  
  GET_EMP1(20)
  (DATASET)
  

  I can use TOAD or sql developer to examine this dataset and see the documents.

  But I can actually query the records by using the TABLE function:

  select * from table(get_emp1(20))
  
  EMPNO     ENAME     JOB     MGR     HIREDATE     SAL     COMM     DEPTNO
  7369     SMITH     CLERK     7902     12/17/1980     800          20
  7566     JONES     MANAGER     7839     4/2/1981     2975          20
  7788     SCOTT     ANALYST     7566     4/19/1987     3000          20
  7876     ADAMS     CLERK     7788     5/23/1987     1100          20
  7902     FORD     ANALYST     7566     12/3/1981     3000          20
  

  This is a similar function. It returns the same EMP_TABLE_TYPE, but it is a PIPELINED function.

  -- pipelined function
  create or replace function get_emp( p_deptno in number )
    return emp_table_type
    PIPELINED
    as
     TYPE EmpCurTyp IS REF CURSOR RETURN emp%ROWTYPE;
      emp_cv EmpCurTyp;
      l_rec  emp%rowtype;
    begin
      open emp_cv for select * from emp where deptno = p_deptno;
      loop
        fetch emp_cv into l_rec;
        exit when (emp_cv%notfound);
        pipe row( emp_scalar_type( l_rec.empno, LOWER(l_rec.ename),
            l_rec.job, l_rec.mgr, l_rec.hiredate, l_rec.sal, l_rec.comm, l_rec.deptno ) );
      end loop;
      return;
    end;
    /
  

  The ONLY way I can query this function is using the TABLE function:

  select * from table(get_emp(20))
  
  EMPNO     ENAME     JOB     MGR     HIREDATE     SAL     COMM     DEPTNO
  7369     smith     CLERK     7902     12/17/1980     800          20
  7566     jones     MANAGER     7839     4/2/1981     2975          20
  7788     scott     ANALYST     7566     4/19/1987     3000          20
  7876     adams     CLERK     7788     5/23/1987     1100          20
  7902     ford     ANALYST     7566     12/3/1981     3000          20
  

  The query of the PIPELINED function is the same and the result set is the same.

  The difference is that the PIPELINED function returns ONE LINE at a time and does NOT need to accumulate a large amount of data in a collection before returning. This collection uses the memory of expensive PGA and the more data you have the more memory it uses.

  Your function (and my only similar) return NO data until it has produced ALL of this. And he uses this expensive PGA memory. What is the point to create your collection at a time line and wait until you have everything before send it back you?

  You can easily modify your function and add PIPELINED to the declaration. Then, use the PIPE ROW clause to return each row that it is produced. Which will eliminate the need of collecting (and memory) within the service.

  You can also then follow up calls to function if you need to.

  See 'Use of functions Table in pipeline and parallel' in the data cartridge Developer Guide
  http://docs.Oracle.com/CD/B28359_01/AppDev.111/b28425/pipe_paral_tbl.htm

  There is little use for your function that is not in the pipeline, but returns a type of table, unless you used to store the array type in a column of an object table.

  There are many uses for PIPELINED functions.

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  SQL> create or replace type TIntegers is table of integer;
    2  /
  
  Type created.
  
  SQL>
  SQL> --// our sample pipeline simply spews 2 numbers for eevry number input - simple
  SQL> --// to use for the testcase below
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  Function created.
  
  SQL>
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    2          --// ignore this part as it only builts a base table
    3          --// for us to use to select values for input to
    4          --// to the pipeline - in "real world" use this table
    5          --// will already exist
    6          select
    7                  level
    8          from    dual
    9          connect by level <= 10
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   12          --// we run the pipeline as a nested table column
   13          --// in the SQL projection - the CAST is important
   14          --// in order to establish the nested table type
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   17                  cast(
   18                          FooPipe(d.n) as TIntegers
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   24          p.n,
   25          pipe_val.*
   26  from       pipe_line p, TABLE(p.array)  pipe_val
   27  /
  
           N COLUMN_VALUE
  ---------- ------------
           1            1
           1           -1
           2            2
           2           -2
           3            3
           3           -3
           4            4
           4           -4
           5            5
           5           -5
           6            6
           6           -6
           7            7
           7           -7
           8            8
           8           -8
           9            9
           9           -9
          10           10
          10          -10
  
  20 rows selected.
  
  SQL>
  

  Not sure I like it. What is the real problem that this method (driving a pipeline with input of a base table rows) is supposed to address? There may be a simpler and more elegant approach...

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  my original question was

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