Materialized view with tables in different schemas

Hello,
I want to create a materialized view with a table from a different schema in the SELECT statement. For materialized view I would like to apply the "REFRESH COMPLETE ON COMMIT" option.
Here the code:
CREATE MATERIALIZED VIEW S1.MV_EXAMPLE
TABLESPACE TS1
PCTFREE 0
BUILD IMMEDIATE
REFRESH COMPLETE ON COMMIT
AS
SELECT T.COLUMN1 COLUMN
FROM S2.TABLE1 T
I can't execute this SQL because I get an "insufficient privileges" error to this table:
FROM S2.TABLE1 T
FEHLER in Zeile 9:
ORA-01031: Insufficient privileges
User S1 has the following privileges:
CREATE SESSION
CREATE SNAPSHOT
CREATE TABLE
CREATE QUERY REWRITE
SELECT ANY TABLE
User S2 has the following privileges:
CREATE SESSION
CREATE SNAPSHOT
CREATE TABLE
CREATE QUERY REWRITE
ALTER ANY SNAPSHOT
Which privileges are missing?
Thanks, Mathias

Thanks Kamal for your answer!
S1 has the grant select directly. But I solveld the problem. The system privilege "ON COMMIT REFRESH" was missing for S1. This has to be set if any of the tables are outside the owner's schema of the materialized view (ORACLE documentation - Data Warehouse Guide).
But one thing is not clear to me yet and the ORACLE documentation doesn't give me an answer. I can set the refresh-attribute ON COMMIT on a materialized view containing only joins when a group by clause is set. If the group by clause is missing I can't! Why?
Regards, Mathias

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    "M6" NUMBER,
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    SUM(FCT_POSITION.BASE_REALIZED_PNL) OVER (HIERARCHY DIM_CALENDAR.CALENDAR BETWEEN UNBOUNDED PRECEDING AND CURRENT MEMBER WITHIN ANCESTOR AT DIMENSION LEVEL DIM_CALENDAR."YEAR")
    are eligible for query rewrites or these are considered advanced for query rewrite purposes.
    I was hoping to find an example with YTD window function on physical fact dim tables  with optimizer rewriting it to Cube Org. MV but not much success.
    Thanks in advance

    I dont think this is possible.
    (My own reasoning)
    Part of the reason query rewrite works for base measures only (not calc measures in olap like ytd would be) is due to the fact that the data is staged in olap but its lineage is understandable via the olap cube mappings. That dependency/source identification is lost when we build calculated measures in olap and i think its almost impossible for optimizer to understand the finer points relating to an olap calculation defined via olap calculation (olap dml or olap expression) and also match it with the equivalent calculation using relational sql expression. The difficulty may be because both the olap ytd as well as relational ytd defined via sum() over (partition by ... order by ...) have many non-standard variations of the same calculation/definition. E.g: You can choose to use or choose not to use the option relating to IGNORE NULLs within the sql analytic function. OLAP defn may use NASKIP or NASKIP2.
    I tried to search for query rewrite solutions for Inventory stock based calculations (aggregation along time=last value along time) and see if olap cube with cube aggregation option set to "Last non-na hierarchical value" works as an alternative to relational calculation. My experience has been that its not possible. You can do it relationally or you can do it via olap but your application needs to be aware of each and make the appropriate backend sql/call. In such cases, you cannot make olap (aw/cubes/dimensions) appear magically behind the scenes to fulfill the query execution while appearing to work relationally.
    HTH
    Shankar

  • Updatable Materialized View with Union ALL

    (please don't ask about db structure)
    DB: 11gR2
    create table table_1  (
        id number primary key,
        val varchar2(100)
    create table table_2  (
        id number primary key,
        val varchar2(100)
    insert into table_1(id) values (0);
    insert into table_1(id) values (2);
    insert into table_1(id) values (3);
    insert into table_1(id) values (4);
    insert into table_1(id) values (5);
    insert into table_2(id) values (10);
    insert into table_2(id) values (12);
    insert into table_2(id) values (13);
    insert into table_2(id) values (14);
    insert into table_2(id) values (15);
    update table_1 set val='Table1 val:'||id;
    update table_2 set val='Table2 val:'||id;
    create view v_table_all as
    select * from table_1
    view V_TABLE_ALL created.
    select * from v_table_all;
    ID                     VAL                                                                                                 
    0                      Table1 val:0                                                                                        
    2                      Table1 val:2                                                                                        
    3                      Table1 val:3                                                                                        
    4                      Table1 val:4                                                                                        
    5                      Table1 val:5                                                                                        
    select column_name, updatable, insertable, deletable
    from user_updatable_columns
    where table_name = 'V_TABLE_ALL'
    COLUMN_NAME                    UPDATABLE INSERTABLE DELETABLE
    ID                             YES       YES        YES      
    VAL                            YES       YES        YES      
    update v_table_all set val='XXX changed' where id = 3;
    1 row updated.
    select * from table_1;
    ID                     VAL                                                                                                 
    0                      Table1 val:0                                                                                        
    2                      Table1 val:2                                                                                        
    3                      XXX changed                                                                                         
    4                      Table1 val:4                                                                                        
    5                      Table1 val:5                                                                                        
    rollback;
    select * from table_1;
    ID                     VAL                                                                                                 
    0                      Table1 val:0                                                                                        
    2                      Table1 val:2                                                                                        
    3                      Table1 val:3                                                                                        
    4                      Table1 val:4                                                                                        
    5                      Table1 val:5                                                                                        
    create or replace view v_table_all as
    select * from table_1
    union select * from table_2;
    view V_TABLE_ALL created.
    select * from v_table_all;
    ID                     VAL                                                                                                 
    0                      Table1 val:0                                                                                        
    2                      Table1 val:2                                                                                        
    3                      Table1 val:3                                                                                        
    4                      Table1 val:4                                                                                        
    5                      Table1 val:5                                                                                        
    10                     Table2 val:10                                                                                       
    12                     Table2 val:12                                                                                       
    13                     Table2 val:13                                                                                       
    14                     Table2 val:14                                                                                       
    15                     Table2 val:15  
    select column_name, updatable, insertable, deletable
    from user_updatable_columns
    where table_name = 'V_TABLE_ALL'
    COLUMN_NAME                    UPDATABLE INSERTABLE DELETABLE
    ID                             NO        NO         NO       
    VAL                            NO        NO         NO       
    trying update:
    update v_table_all set val='XXX changed' where id = 3;
    SQL-Fehler: ORA-01732: Datenmanipulationsoperation auf dieser View nicht zulässig
    01732. 00000 -  "data manipulation operation not legal on this view"
    *Cause:   
    *Action:
    drop view v_table_all;
    view V_TABLE_ALL dropped.all is ok before this point.
    now we want create a new materialized view with some query
    create  materialized view v_table_all
    as
    select * from table_1
    union all select * from table_2 ;
    materialized view V_TABLE_ALL created.
    select column_name, updatable, insertable, deletable
    from user_updatable_columns
    where table_name = 'V_TABLE_ALL'
    COLUMN_NAME                    UPDATABLE INSERTABLE DELETABLE
    ID                             YES       YES        YES      
    VAL                            YES       YES        YES       it seems to be ok with update.
    but...
    update v_table_all set val='XXX changed' where id = 3;
    SQL-Fehler: ORA-01732: Datenmanipulationsoperation auf dieser View nicht zulässig
    01732. 00000 -  "data manipulation operation not legal on this view"
    *Cause:   
    *Action:How can solve this issue??
    Any suggestion

    Looks like user_updatable_columns sort of thinks the MV is just a table - I don't know about that...
    An MV on a single table can be updated - I tried that and it works:
    create materialized view mv_table_1 for update
    as
    select * from table_1;I noticed [url http://download.oracle.com/docs/cd/E11882_01/server.112/e16579/advmv.htm#sthref294]examples stating the UNION ALL needs a "marker" so Oracle can know from the data which source table a row in the MV originates from - like this:
    create materialized view v_table_all for update
    as
    select 'T1' tab_id, table_1.* from table_1
    union all
    select 'T2' tab_id, table_2.* from table_2 ;But that also fails (the "marker" requirement was specifically for FAST REFRESH, so it was just a long shot ;-) )
    What are you planning to do?
    <li>Create the MV.
    <li>Update records in the MV - which then is no longer consistent with the source data.
    <li>Schedule a complete refresh once in a while - thereby overwriting/losing the updates in the MV.
    If that is the case, I suggest using a true table rather than an MV.
    <li>Create table t_table_all as select ... .
    <li>Update records in the table - which then is no longer consistent with the source data.
    <li>Schedule a job to delete table and insert into table select ... once in a while - thereby overwriting/losing the updates in the table.
    In other words a kind of "do it yourself MV".
    I cannot see another way at the moment? But perhaps try in the data warehousing forum - the people there may have greater experience with MV's ;-)

  • Create materialized view with specific column sizes

    Hi all,
    I'm trying to create a materialized view with a specific a column size. Something like
    create materialized view test_mv
    refresh force on demand
    as
    select id,
           cast(my_compound_field as nvarchar2(50))
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                  field1 || field2 my_compound_field
           from   my_table);But Oracle seems to ignore the cast and takes the maximum size it finds for field1 || field2 in the select query. The resulting table has a column nvarchar2(44) instead of nvarchar2(50).
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    Edit: Some additional info to clarify my case:
    field1 and field2 are defined as nvarchar2(25). field1 || field2 can theoretically have a length of 50, but there is currently no data in my table that results in that length, the max is 44. I am afraid that there will be data in the future that exceeds 44, resulting in an error when the MV is refreshed!
    Edited by: Pleiadian on Jan 25, 2011 2:06 PM

    Cannot reproduce what you are saying is happening.
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    SQL> create materialized view tmv as
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    Materialized view created.
    SQL> desc tmv
    Name                                      Null?    Type
    A                                                  NVARCHAR2(50)
    B                                                  NVARCHAR2(50)
    C                                                  NVARCHAR2(100)
    SQL> drop materialized view tmv;
    Materialized view dropped.
    SQL> create materialized view tmv as
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    Materialized view created.
    SQL> desc tmv
    Name                                      Null?    Type
    A                                                  NVARCHAR2(50)
    B                                                  NVARCHAR2(50)
    C                                                  NVARCHAR2(10)
    SQL> select * from v$version;
    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 Linux: Version 11.1.0.7.0 - Production
    NLSRTL Version 11.1.0.7.0 - Production
    SQL>Edited by: 3360 on Jan 25, 2011 8:10 AM
    And with data
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    1 row created.
    SQL> commit;
    Commit complete.
    SQL> desc tmv
    Name                                      Null?    Type
    A                                                  NVARCHAR2(50)
    B                                                  NVARCHAR2(50)
    C                                                  NVARCHAR2(10)
    SQL> select * from tmv;
    A
    B                                                  C
    3123423423143hhshgvcdcvw
    ydgeew  gdfwe   dfefde  wfjjjjjjj                      3123423423

  • How to create materialized  view with parameter and index ?

    Hi all,
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    Thanks
    Damby

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    What is the purpose behind those 2 parameters?

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