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04/11/23 Yadav, Naresh 1
Materialized Views
ORACLE
04/11/23 Yadav, Naresh 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? Examples
04/11/23 Yadav, Naresh 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
04/11/23 Yadav, Naresh 4
Advantages and Disadvantages
Advantages 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
04/11/23 Yadav, Naresh 5
Database Parameter Settings
init.ora parameter COMPATIBLE=8.1.0 (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
04/11/23 Yadav, Naresh 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 Primary key, foreign keys Data dictionary information Dimensions
stale_tolerated – queries rewritten even if Oracle knows the mv’s data is out-of-sync with the detail data Data dictionary information
04/11/23 Yadav, Naresh 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
04/11/23 Yadav, Naresh 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)
04/11/23 Yadav, Naresh 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
04/11/23 Yadav, Naresh 10
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
Materialized View Refresh Options
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Materialized View Refresh Modes
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
04/11/23 Yadav, Naresh 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;
04/11/23 Yadav, Naresh 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
04/11/23 Yadav, Naresh 14
Materialized View Example (cont’d)
SQL> ALTER SESSION SET QUERY_REWRITE_INTEGRITY=TRUSTED;
SQL> ALTER SESSION SET QUERY_REWRITE_ENABLED=FALSE;
SQL> @mv_example.sql
CATEG_ID SITE_ID SUM(NET_REV) SUM(BOLD_FEE) COUNT(ITEM_ID)
-------- ------- ------------ ------------- --------------
1 0 -2.35 0 1
22 0 -42120.87 -306 28085
Elapsed: 01:32:17.93
Execution Plan---------------------------------------------------------- 0 SELECT STATEMENT Optimizer=HINT: FIRST_ROWS (Cost=360829
Card=6 Bytes=120) 1 0 SORT (GROUP BY) (Cost=360829 Card=6 Bytes=120) 2 1 PARTITION RANGE (INLIST 3 2 TABLE ACCESS (FULL) OF ‘ITEMS' (Cost=360077 Card=375154 Bytes=7503080)
04/11/23 Yadav, Naresh 15
Materialized View Example (cont’d)
SQL> ALTER SESSION SET QUERY_REWRITE_ENABLED=TRUE;
SQL> @mv_example.sql
CATEG_ID SITE_ID SUM(NET_REV) SUM(BOLD_FEE) COUNT(ITEM_ID)
-------- ------- ------------ ------------- --------------
1 0 -2.35 0 1
22 0 -42120.87 -306 28085
Elapsed: 00:01:40.47
Execution Plan----------------------------------------------------------------------------------------------
0 SELECT STATEMENT Optimizer=HINT: FIRST_ROWS (Cost=3749 Card=12 Bytes=276)
1 0 SORT (GROUP BY) (Cost=3749 Card=12 Bytes=276)
2 1 PARTITION RANGE (INLIST)
3 2 TABLE ACCESS (FULL) OF ‘ITEMS_SUMMARY_MV'
(Cost=3723 Card=7331 Bytes=168613)
04/11/23 Yadav, Naresh 16
Example of FAST REFRESH MVCREATE 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.email,
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.email, l.categ_id, l.site_id;
04/11/23 Yadav, Naresh 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
04/11/23 Yadav, Naresh 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
: : :
11 QTY_SOLD SUM
12 UNITS COUNT
04/11/23 Yadav, Naresh 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$_exceptions
04/11/23 Yadav, Naresh 20
Syntax For Creating A Dimension
CREATE DIMENSION <dimension name>
LEVEL [<level> IS <level_table.level_column>
<level> IS <level_table.level_column>…]
HIERARCHY <hierarchy_name>
( <child_level> CHILD OF <parent_level>
<child_level> CHILD OF <parent_level>…]
ATTRIBUTE <level> DETERMINES <dependent_column>
<level> DETERMINES <dependent_column>,…);
To validate a dimension:
exec dbms_olap.validate_dimension(<dim_name>,<owner>,FALSE,FALSE);
04/11/23 Yadav, Naresh 21
Example of Creating A DimensionCREATE DIMENSION time_dim
LEVEL CAL_DATE IS calendar.CAL_DATE
LEVEL PRD_ID IS calendar.PRD_ID
LEVEL QTR_ID IS calendar.QTR_ID
LEVEL YEAR_ID IS calendar.YEAR_ID
LEVEL WEEK_IN_YEAR_ID IS calendar.WEEK_IN_YEAR_ID
HIERARCHY calendar_rollup
(CAL_DATE CHILD OF
PRD_ID CHILD OF
QTR_ID CHILD OF YEAR_ID)
HIERARCHY week_rollup
(CAL_DATE CHILD OF
WEEK_IN_YEAR_ID CHILD OF YEAR_ID)
ATTRIBUTE PRD_ID DETERMINES PRD_DESC
ATTRIBUTE QTR_ID DETERMINES QTR_DESC;
04/11/23 Yadav, Naresh 22
Example of Validating A Dimension
SQL> exec dbms_olap.validate_dimension(‘time_dim’, USER, FALSE, FALSE);
PL/SQL procedure successfully completed.
SQL> select * from mview$_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);
04/11/23 Yadav, Naresh 23
Example of Using Dimensions-- Step 1 of 4
-- Create materialized view (join-aggregate type)
CREATE MATERIALIZED VIEW items_mvBUILD IMMEDIATEREFRESH ON DEMANDENABLE QUERY REWRITEASSELECT 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;
04/11/23 Yadav, Naresh 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=1160256) SORT (GROUP BY) (Cost=16174 Card=36258 Bytes=1160256) HASH JOIN (Cost=81 Card=5611339 Bytes=179562848) TABLE ACCESS (FULL) OF ’CALENDAR' (Cost=2 Card=8017 Bytes=128272) TABLE ACCESS (FULL) OF ’ITEMS' (Cost=76 Card=69993 Bytes=1119888)
04/11/23 Yadav, Naresh 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=878824 Bytes=44820024) SORT (GROUP BY) (Cost=3703 Card=878824 Bytes=44820024) HASH JOIN (Cost=31 Card=878824 Bytes=44820024) 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)
04/11/23 Yadav, Naresh 26
Summary
Materialized Views 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
04/11/23 Yadav, Naresh 27
Requirements for FAST REFRESH
Requirement Joins Only Joins & Aggregates
Single Table Aggregates
Must be based on detail tables only X X X Must be based on a single table X Each table can appear only once in the FROM list X X X Cannot contain nonrepeating expressions (ROWNUM, SYSDATE, etc) X X X Cannot contain references to RAW or LONG RAW X X X Cannot contain the GROUP BY clause X The SELECT list must include the ROWIDs of all the detail tables X Expressions can be included in the GROUP BY and SELECT clause as long as they are the same in each
X X
Aggregates are allowed but cannot be nested X X If SELECT clause contains AVG, it must also contain COUNT X X If SELECT clause contains SUM, it must also contain COUNT X If SELECT clause contains VARIANCE, it must also contain COUNT and SUM
X X
If SELECT clause contains STDDEV, it must also contain COUNT and SUM
X
The join predicates of the WHERE clause can included AND but not OR X The HAVING and CONNECT BY clauses are not allowed X X X
04/11/23 Yadav, Naresh 28
Rqmts For FAST REFRESH (cont’d)
Requirement Joins Only Joins &
Aggregates Single Table Aggregates
Sub-queries, inline views, or set functions such as UNION are not allowed
X X X
A WHERE clause is not allowed X COUNT(*) must be present X MIN and MAX are not allowed X Unique constraints must exist on the join columns of the inner table, if an outer join is used
X
A materialized view log must exist that contains all column referenced in the materialized view, and it must have been created with the LOG NEW VALUES clause
X
A materialized view log containing ROWID must exist for each detail table
X
Any non aggregate expressions in the SELECT and GROUP BY clauses must be non-modified columns
X
DML allowed on detailed tables X X Direct path data load allowed X X X
04/11/23 Yadav, Naresh 29
Materialized Views