1. Materialized Views
Willie Albino May 15, 2003

2. Materialized Views – Agenda
What is a Materialized View?
Advantages and Disadvantages
How Materialized Views Work
Parameter Settings, Privileges, Query Rewrite
Creating Materialized Views
Syntax, Refresh Modes/Options, Build Methods
Examples
Dimensions
What are they?
Willie Albino May 15, 2003

3. What is a Materialized View?
A database object that stores the results of a query
Marries the query rewrite features found in Oracle Discoverer with the data refresh capabilities of snapshots
Features/Capabilities
Can be partitioned and indexed
Can be queried directly
Can have DML applied against it
Several refresh options are available
Best in read-intensive environments
Willie Albino May 15, 2003

4. Advantages and Disadvantages
Useful for summarizing, pre-computing, replicating and distributing data
Faster access for expensive and complex joins
Transparent to end-users
MVs can be added/dropped without invalidating coded SQL
Disadvantages
Performance costs of maintaining the views
Storage costs of maintaining the views
Willie Albino May 15, 2003

5. Database Parameter Settings
init.ora parameter
COMPATIBLE= (or above)
System or session settings
query_rewrite_enabled={true|false}
query_rewrite_integrity= {enforced|trusted|stale_tolerated}
Can be set for a session using
alter session set query_rewrite_enabled=true;
alter session set query_rewrite_integrity=enforced;
Privileges which must be granted to users directly
QUERY_REWRITE - for MV using objects in own schema
GLOBAL_QUERY_REWRITE - for objects in other schemas
Willie Albino May 15, 2003

6. Query Rewrite Details query_rewrite_integrity Settings:
enforced – rewrites based on Oracle enforced constraints
Primary key, foreign keys
trusted – rewrites based on Oracle enforced constraints and known, but not enforced, data relationships
Data dictionary information
Dimensions
stale_tolerated – queries rewritten even if Oracle knows the mv’s data is out-of-sync with the detail data
Willie Albino May 15, 2003

7. Query Rewrite Details (cont’d)
Query Rewrite Methods
Full Exact Text Match
Friendlier/more flexible version of text matching
Partial Text Match
Compares text starting at FROM clause
SELECT clause must be satisfied for rewrite to occur
Data Sufficiency
All required data must be present in the MV or retrievable through a join-back operation
Join Compatibility
All joined columns are present in the MV
Willie Albino May 15, 2003

8. Query Rewrite Details (cont’d)
Grouping Compatibility
Allows for matches in groupings at higher levels than those defined MV query
Required if both query and MV contain a GROUP BY clause
Aggregate Compatibility
Allows for interesting rewrites of aggregations
If SUM(x) and COUNT(x) are in MV, the MV may be used if the query specifies AVG(x)
Willie Albino May 15, 2003

9. Syntax For Materialized Views
CREATE MATERIALIZED VIEW <name>
TABLESPACE <tbs name> {<storage parameters>}
<build option>
REFRESH <refresh option> <refresh mode>
[ENABLE|DISABLE] QUERY REWRITE AS
SELECT <select clause>;
The <build option> determines when MV is built
BUILD IMMEDIATE: view is built at creation time
BUILD DEFFERED: view is built at a later time
ON PREBUILT TABLE: use an existing table as view source
Must set QUERY_REWRITE_INTEGRITY to TRUSTED
Willie Albino May 15, 2003

10. Materialized View Refresh Options
COMPLETE – totally refreshes the view
Can be done at any time; can be time consuming
FAST – incrementally applies data changes
A materialized view log is required on each detail table
Data changes are recorded in MV logs or direct loader logs
Many other requirements must be met for fast refreshes
FORCE – does a FAST refresh in favor of a COMPLETE
The default refresh option
Willie Albino May 15, 2003

11. Materialized View Refresh Modes
ON COMMIT – refreshes occur whenever a commit is performed on one of the view’s underlying detail table(s)
Available only with single table aggregate or join based views
Keeps view data transactionally accurate
Need to check alert log for view creation errors
ON DEMAND – refreshes are initiated manually using one of the procedures in the DBMS_MVIEW package
Can be used with all types of materialized views
Manual Refresh Procedures
DBMS_MVIEW.REFRESH(<mv_name>, <refresh_option>)
DBMS_MVIEW.REFRESH_ALL_MVIEWS()
START WITH [NEXT] <date> - refreshes start at a specified date/time and continue at regular intervals
Willie Albino May 15, 2003

12. Materialized View Example
CREATE MATERIALIZED VIEW items_summary_mv
ON PREBUILT TABLE
REFRESH FORCE AS
SELECT a.PRD_ID, a.SITE_ID, a.TYPE_CODE, a.CATEG_ID,
sum(a.GMS) GMS,
sum(a.NET_REV) NET_REV,
sum(a.BOLD_FEE) BOLD_FEE,
sum(a.BIN_PRICE) BIN_PRICE,
sum(a.GLRY_FEE) GLRY_FEE,
sum(a.QTY_SOLD) QTY_SOLD,
count(a.ITEM_ID) UNITS
FROM items a
GROUP BY a.PRD_ID, a.SITE_ID, a.TYPE_CODE, a.CATEG_ID;
ANALYZE TABLE item_summary_mv COMPUTE STATISTICS;
Willie Albino May 15, 2003

13. Materialized View Example (cont’d)
-- Query to test impact of materialized view
select categ_id, site_id,
sum(net_rev),
sum(bold_fee),
count(item_id)
from items
where prd_id in ('2000M05','2000M06','2001M07','2001M08')
and site_id in (0,1)
and categ_id in (2,4,6,8,1,22)
group by categ_id, site_id
save mv_example.sql
Willie Albino May 15, 2003

14. Materialized View Example (cont’d)
SQL> ALTER SESSION SET QUERY_REWRITE_INTEGRITY=TRUSTED;
SQL> ALTER SESSION SET QUERY_REWRITE_ENABLED=FALSE;
CATEG_ID SITE_ID SUM(NET_REV) SUM(BOLD_FEE) COUNT(ITEM_ID)
Elapsed: 01:32:17.93
Execution Plan
0 SELECT STATEMENT Optimizer=HINT: FIRST_ROWS (Cost= Card=6 Bytes=120)
SORT (GROUP BY) (Cost= Card=6 Bytes=120)
PARTITION RANGE (INLIST
TABLE ACCESS (FULL) OF ‘ITEMS' (Cost=360077
Card= Bytes= )
Willie Albino May 15, 2003

15. Materialized View Example (cont’d)
SQL> ALTER SESSION SET QUERY_REWRITE_ENABLED=TRUE;
CATEG_ID SITE_ID SUM(NET_REV) SUM(BOLD_FEE) COUNT(ITEM_ID)
Elapsed: 00:01:40.47
Execution Plan
SELECT STATEMENT Optimizer=HINT: FIRST_ROWS (Cost=3749 Card=12 Bytes=276)
SORT (GROUP BY) (Cost=3749 Card=12 Bytes=276)
PARTITION RANGE (INLIST)
TABLE ACCESS (FULL) OF ‘ITEMS_SUMMARY_MV'
(Cost=3723 Card=7331 Bytes=168613)
Willie Albino May 15, 2003

16. Example of FAST REFRESH MV
CREATE MATERIALIZED VIEW LOG ON ITEMS
TABLESPACE MV_LOGS STORAGE(INITIAL 10M NEXT 10M) WITH ROWID;
CREATE MATERIALIZED VIEW LOG ON CUSTOMERS
TABLESPACE MV_LOGS STORAGE(INITIAL 1M NEXT 1M) WITH ROWID;
CREATE MATERIALIZED VIEW cust_activity
BUILD IMMEDIATE
REFRESH FAST ON COMMIT AS
SELECT u.ROWID cust_rowid, l.ROWID item_rowid,
u.cust_id, u.custname, u. ,
l.categ_id, l.site_id, sum(gms), sum(net_rev_fee)
FROM customers u, items l
WHERE u.cust_id = l.seller_id
GROUP BY u.cust_id, u.custname, u. , l.categ_id, l.site_id;
Willie Albino May 15, 2003

17. Getting Information About an MV
Getting information about the key columns of a materialized view:
SELECT POSITION_IN_SELECT POSITION,
CONTAINER_COLUMN COLUMN,
DETAILOBJ_OWNER OWNER,
DETAILOBJ_NAME SOURCE,
DETAILOBJ_ALIAS ALIAS,
DETAILOBJ_TYPE TYPE,
DETAILOBJ_COLUMN SRC_COLUMN
FROM USER_MVIEW_KEYS
WHERE MVIEW_NAME=‘ITEMS_SUMMARY_MV’;
POS COLUMN OWNER SOURCE ALIAS TYPE SRC_COLUMN
1 PRD_ID TAZ ITEMS A TABLE PRD_ID
2 SITE_ID TAZ ITEMS A TABLE SITE_ID
3 TYPE_CODE TAZ ITEMS A TABLE TYPE_CODE
4 CATEG_ID TAZ ITEMS A TABLE CATEG_ID
Willie Albino May 15, 2003

18. Getting Information About an MV
Getting information about the aggregate columns of a materialized view:
SELECT POSITION_IN_SELECT POSITION,
CONTAINER_COLUMN COLUMN,
AGG_FUNCTION
FROM USER_MVIEW_AGGREGATES
WHERE MVIEW_NAME=‘ITEMS_SUMMARY_MV’;
POSITION COLUMN AGG_FUNCTION
6 GMS SUM
7 NET_REV SUM
: : :
QTY_SOLD SUM
UNITS COUNT
Willie Albino May 15, 2003

19. Dimensions A way of describing complex data relationships
Used to perform query rewrites, but not required
Defines hierarchical relationships between pairs of columns
Hierarchies can have multiple levels
Each child in the hierarchy has one and only one parent
Each level key can identify one or more attribute
Child join keys must be NOT NULL
Dimensions should be validated using the DBMS_OLAP.VALIDATE_DIMENSION package
Bad row ROWIDs stored in table: mview$_exceptions
Willie Albino May 15, 2003

20. Syntax For Creating A Dimension
CREATE DIMENSION <dimension name>
LEVEL [<level> IS <level_table.level_column>
<level> IS <level_table.level_column>…]
HIERARCHY <hierarchy_name>
( <child_level> CHILD OF <parent_level>
<child_level> CHILD OF <parent_level>…]
ATTRIBUTE <level> DETERMINES <dependent_column>
<level> DETERMINES <dependent_column>,…);
To validate a dimension:
exec dbms_olap.validate_dimension(<dim_name>,<owner>,FALSE,FALSE);
Willie Albino May 15, 2003

21. Example of Creating A Dimension
CREATE DIMENSION time_dim
LEVEL CAL_DATE IS calendar.CAL_DATE
LEVEL PRD_ID IS calendar.PRD_ID
LEVEL QTR_ID IS calendar.QTR_ID
LEVEL YEAR_ID IS calendar.YEAR_ID
LEVEL WEEK_IN_YEAR_ID IS calendar.WEEK_IN_YEAR_ID
HIERARCHY calendar_rollup
(CAL_DATE CHILD OF
PRD_ID CHILD OF
QTR_ID CHILD OF YEAR_ID)
HIERARCHY week_rollup
WEEK_IN_YEAR_ID CHILD OF YEAR_ID)
ATTRIBUTE PRD_ID DETERMINES PRD_DESC
ATTRIBUTE QTR_ID DETERMINES QTR_DESC;
Willie Albino May 15, 2003

22. Example of Validating A Dimension
SQL> exec dbms_olap.validate_dimension(‘time_dim’, USER, FALSE, FALSE);
PL/SQL procedure successfully completed.
SQL> select * from mview$_exceptions;
no rows selected.
-- Main cause of errors is a child level having multiple parents
-- If above query returns rows, the bad rows can be found as follows:
select * from calendar
where rowid in
(select bad_rowid from mview$_exceptions);
Willie Albino May 15, 2003

23. Example of Using Dimensions
-- Step 1 of 4
-- Create materialized view (join-aggregate type)
CREATE MATERIALIZED VIEW items_mv
BUILD IMMEDIATE
REFRESH ON DEMAND
ENABLE QUERY REWRITE AS
SELECT l.slr_id ,
c.cal_date,
sum(l.gms) gms
FROM items l,
calendar c
WHERE
l.end_date=c.cal_date
GROUP BY
l.slr_id, c.cal_date;
Willie Albino May 15, 2003

24. Example of Using Dimensions (cont’d)
-- Step 2 of 4: (not really required, for demonstration only)
-- Execute query based on “quarter”, not “date”, without a time dimension
-- Note that the detail tables are accessed
SQL> select c.qtr_id, sum(l.gms) gms
2 from items l, calendar c
3 where l.end_date=c.cal_date
4 group by l.slr_id, c.qtr_id;
Execution Plan
SELECT STATEMENT Optimizer=CHOOSE (Cost=16174 Card=36258 Bytes= )
SORT (GROUP BY) (Cost=16174 Card=36258 Bytes= )
HASH JOIN (Cost=81 Card= Bytes= )
TABLE ACCESS (FULL) OF ’CALENDAR' (Cost=2 Card=8017 Bytes=128272)
TABLE ACCESS (FULL) OF ’ITEMS' (Cost=76 Card=69993 Bytes= )
Willie Albino May 15, 2003

25. Example of Using Dimensions (cont’d)
-- Step 3 of 4: Create time dimension (see slide #21 for SQL)
@cr_time_dim.sql
Dimension Created
-- Step 4 of 4: Rerun query based on “quarter” with time dimension
SQL> select c.qtr_id, sum(l.gms) gms
2 from items l, calendar c
3 where l.end_date=c.cal_date
4 group by l.slr_id, c.qtr_id;
Execution Plan
SELECT STATEMENT Optimizer=CHOOSE (Cost=3703 Card= Bytes= )
SORT (GROUP BY) (Cost=3703 Card= Bytes= )
HASH JOIN (Cost=31 Card= Bytes= )
VIEW (Cost=25 Card=8017 Bytes=128272)
SORT (UNIQUE) (Cost=25 Card=8017 Bytes=128272)
TABLE ACCESS (FULL) OF ‘CALENDAR’ (Cost=2 Card=8017 Bytes=128272)
TABLE ACCESS (FULL) OF ‘ITEMS_MV’ (Cost=3 Card=10962 Bytes=383670)
Willie Albino May 15, 2003

26. Summary Materialized Views Dimensions
reduce system cpu/io resource requirements by pre-calculating and storing results of intensive queries
allow for the automatic rewriting of intensive queries
are transparent to the application
have storage/maintenance requirements
can understand complex data relationships
can be refreshed on demand or on a schedule
Dimensions
allow you to “tell” Oracle about complex data relationships which can be used to rewrite queries
Willie Albino May 15, 2003

27. References
Using Oracle9i Materialized Views (Technet Oracle By Example)
Oracle Expert-One-On-One – Thomas Kyte
The Secrets of Materialized Views
OLAP DB-Design with Dimensions
The Secrets of Dimensions
Willie Albino May 15, 2003

28. Willie Albino May 15, 2003

29. Requirements for FAST REFRESH
Willie Albino May 15, 2003

30. Rqmts For FAST REFRESH (cont’d)
Willie Albino May 15, 2003