How to make a schema dependant of other schema - sql

Question

Got a question and I don't find the answer, can someone help me ? here is the situation :
I have a schema, that is a template.
And I want to have 10 schemas of this template.
But I want that everytime I change the structure of the template schema, like making a new column, the column is created in all the schemas related to the template schema.
is this possible with Oracle ?

Answer 1

As the others said, it is not possible in Oracle to do this by default. BUT, if your on the latest versions (12.2 and higher), and don't mind paying for the multitenant option, you can look into something called application containers. This will trade your schemas in a single DB for the same schema but in different PDBs. Application containers allows you to define the schema in a parent PDB (including tables, views, triggers, ....) and have every modification propagated to the PDBs (you sync each PDB when you want).

Answer 2

But I want that everytime I change the structure of the template schema, like making a new column, the column is created in all the schemas related to the template schema.
is this possible with Oracle ?
No, it is not. You would need to separately create the column in the table owned by each individual user (a.k.a. schema).

Answer 3

As Justin Cave suggested, your problem is practically screaming for Oracle Partitioning.
If you do not have Partitioning licensed, there is still the old (but free!) approach of making a partitioned view.
In this approach, you would keep your historical tables unchanged (i.e., don't go back and add new columns to them). Instead, you would create a partitioned view that includes each historical table (concatenated together via UNION ALL). The view definition can provide values for newer columns that did not exist in the original table that year.
A partitioned view also has the benefits of
Making it easy to report across multiple years
"Partition pruning" -- skipping tables that are not of interest in a given query
Here is a walk through of the approach:
Create tables for 2019 and 2020 data
CREATE TABLE matt_data_2019
( id NUMBER NOT NULL,
creation_date DATE NOT NULL,
data_column1 NUMBER,
data_column2 VARCHAR2(200),
CONSTRAINT matt_data_2019 PRIMARY KEY ( id ),
CONSTRAINT matt_data_2019_c1 CHECK ( creation_date BETWEEN to_date('01-JAN-2019','DD-MON-YYYY') AND to_date('01-JAN-2020','DD-MON-YYYY') - interval '1' second )
);
CREATE TABLE matt_data_2020
( id NUMBER NOT NULL,
creation_date DATE NOT NULL,
data_column1 NUMBER,
data_column2 VARCHAR2(200),
data_column3 DATE, -- This is new for 2020
CONSTRAINT matt_data_2020 PRIMARY KEY ( id ),
CONSTRAINT matt_data_2020_c1 CHECK ( creation_date BETWEEN to_date('01-JAN-2020','DD-MON-YYYY') AND to_date('01-JAN-2021','DD-MON-YYYY') - interval '1' second )
);
Notice there is a new column for 2020 that does not exist in 2019.
Put some test data in to ensure accurate test results...
INSERT INTO matt_data_2019 ( id, creation_date, data_column1, data_column2 )
SELECT rownum id,
to_date('01-JAN-2019','DD-MON-YYYY') + (dbms_random.value(0, 365*24*60*60-1) / (365*24*60*60)), -- Some random date in 2019
dbms_random.value(0,1000),
lpad('2019',200,'X')
FROM dual
CONNECT BY rownum <= 100000;
INSERT INTO matt_data_2020 ( id, creation_date, data_column1, data_column2, data_column3 )
SELECT rownum id,
to_date('01-JAN-2020','DD-MON-YYYY') + (dbms_random.value(0, 365*24*60*60-1) / (365*24*60*60)), -- Some random date in 2020
dbms_random.value(0,1000),
lpad('2020',200,'X'),
to_date('01-JAN-2021','DD-MON-YYYY') + (dbms_random.value(0, 365*24*60*60-1) / (365*24*60*60)) -- Some random date in 2021
FROM dual
CONNECT BY rownum <= 100000;
Gather statistics on both tables for accurate test results ...
EXEC DBMS_STATS.GATHER_TABLE_STATS(user,'MATT_DATA_2019');
EXEC DBMS_STATS.GATHER_TABLE_STATS(user,'MATT_DATA_2020');
Create a view that includes all the tables.
You would need to modify this view every time a new table was created.
CREATE OR REPLACE VIEW matt_data_v AS
SELECT 2019 source_year,
id,
creation_date,
data_column1,
data_column2,
NULL data_column3 -- data_column3 did not exist in 2019
FROM matt_data_2019
UNION ALL
SELECT 2020 source_year,
id,
creation_date,
data_column1,
data_column2,
data_column3 -- data_column3 did not exist in 2019
FROM matt_data_2020;
Check how Oracle will process a query specifying a single year
EXPLAIN PLAN SET STATEMENT_ID = 'MM' FOR SELECT * FROM MATT_DATA_V WHERE SOURCE_YEAR = 2020
SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY('PLAN_TABLE','MM'));
Plan hash value: 393585474
---------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
---------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 110K| 15M| 620 (2)| 00:00:01 |
| 1 | VIEW | MATT_DATA_V | 110K| 15M| 620 (2)| 00:00:01 |
| 2 | UNION-ALL | | | | | |
|* 3 | FILTER | | | | | |
| 4 | TABLE ACCESS FULL| MATT_DATA_2019 | 71238 | 9530K| 596 (2)| 00:00:01 |
| 5 | TABLE ACCESS FULL | MATT_DATA_2020 | 110K| 15M| 620 (2)| 00:00:01 |
---------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
3 - filter(NULL IS NOT NULL)
Note
-----
- dynamic statistics used: dynamic sampling (level=2)
Hmmm, it looks like Oracle is still including the 2019 table...
... but it isn't. That NULL IS NOT NULL filter condition will cause Oracle to skip the 2019 table completely.
Prove that Oracle is skipping the 2019 table when we ask for 2020 data ...
alter session set statistics_level = ALL;
SELECT * FROM MATT_DATA_V WHERE SOURCE_YEAR = 2020;
-- Be sure to fetch entire result set (e.g., scroll to the end in SQL*Developer)
SELECT *
FROM TABLE (DBMS_XPLAN.display_cursor (null, null,
'ALLSTATS LAST'));
SQL_ID 1u3nwcnxs20jb, child number 0
-------------------------------------
SELECT * FROM MATT_DATA_V WHERE SOURCE_YEAR = 2020
Plan hash value: 393585474
-------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers |
-------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 100K|00:00:00.21 | 5417 |
| 1 | VIEW | MATT_DATA_V | 1 | 110K| 100K|00:00:00.21 | 5417 |
| 2 | UNION-ALL | | 1 | | 100K|00:00:00.17 | 5417 |
|* 3 | FILTER | | 1 | | 0 |00:00:00.01 | 0 |
| 4 | TABLE ACCESS FULL| MATT_DATA_2019 | 0 | 71238 | 0 |00:00:00.01 | 0 |
| 5 | TABLE ACCESS FULL | MATT_DATA_2020 | 1 | 110K| 100K|00:00:00.09 | 5417 |
-------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
3 - filter(NULL IS NOT NULL)
Note
-----
- dynamic statistics used: dynamic sampling (level=2)
The results above show how Oracle skips the 2019 table when we don't ask for it.