Materialized Views
Materialized Views – Agenda
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What is a Materialized View?
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How Materialized Views Work
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Syntax, Refresh Modes/Options, Build Methods
Examples
Dimensions
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2
Parameter Settings, Privileges, Query Rewrite
Creating Materialized Views
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Advantages and Disadvantages
What are they?
Examples
What is a Materialized View?
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A database object that stores the results of a query
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Features/Capabilities
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3
Marries the query rewrite features found in Oracle
Discoverer with the data refresh capabilities of snapshots
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
Advantages and Disadvantages
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Advantages
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Useful for summarizing, pre-computing, replicating and
distributing data
Faster access for expensive and complex joins
Transparent to end-users
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Disadvantages
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4
MVs can be added/dropped without invalidating coded SQL
Performance costs of maintaining the views
Storage costs of maintaining the views
Database Parameter Settings
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init.ora parameter
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System or session settings
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5
query_rewrite_enabled={true|false}
query_rewrite_integrity=
{enforced|trusted|stale_tolerated}
Can be set for a session using
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COMPATIBLE=8.1.0 (or above)
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
Query Rewrite Details
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query_rewrite_integrity Settings:
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enforced – rewrites based on Oracle enforced
constraints
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trusted – rewrites based on Oracle enforced constraints
and known, but not enforced, data relationships
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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
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6
Primary key, foreign keys
Data dictionary information
Query Rewrite Details (cont’d)
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Query Rewrite Methods
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Full Exact Text Match
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Partial Text Match
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All required data must be present in the MV or retrievable
through a join-back operation
Join Compatibility
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7
Compares text starting at FROM clause
SELECT clause must be satisfied for rewrite to occur
Data Sufficiency
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Friendlier/more flexible version of text matching
All joined columns are present in the MV
Query Rewrite Details (cont’d)
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Grouping Compatibility
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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
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Allows for interesting rewrites of aggregations
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8
If SUM(x) and COUNT(x) are in MV, the MV may be
used if the query specifies AVG(x)
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
9
Materialized View Refresh Options
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Refresh Options
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COMPLETE – totally refreshes the view
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FAST – incrementally applies data changes
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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
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Can be done at any time; can be time consuming
The default refresh option
Materialized View Refresh Modes
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Refresh Modes
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ON COMMIT – refreshes occur whenever a commit is
performed on one of the view’s underlying detail table(s)
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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
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Can be used with all types of materialized views
Manual Refresh Procedures
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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
Materialized View Example
CREATE MATERIALIZED VIEW items_summary_mv
ON PREBUILT TABLE
REFRESH FORCE
SELECT
AS
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;
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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
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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)
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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
2
1
3
2
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)
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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.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;
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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
--- ---------- ----- -------- ----- ------ -----------
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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
Getting Information About an MV
Getting information about the aggregate columns of a materialized
view:
SELECT POSITION_IN_SELECT
CONTAINER_COLUMN
POSITION,
COLUMN,
AGG_FUNCTION
FROM USER_MVIEW_AGGREGATES
WHERE MVIEW_NAME=‘ITEMS_SUMMARY_MV’;
POSITION
COLUMN
AGG_FUNCTION
--------
-----------------
------------
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GMS
SUM
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NET_REV
SUM
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:
:
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QTY_SOLD
SUM
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UNITS
COUNT
Dimensions
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A way of describing complex data relationships
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Used to perform query rewrites, but not required
Defines hierarchical relationships between pairs of columns
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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$_exceptions
Syntax For Creating A Dimension
CREATE DIMENSION <dimension name>
LEVEL [<level> IS <level_table.level_column>
<level> IS <level_table.level_column>…]
HIERARCHY <hierarchy_name>
( <child_level> CHILD OF <parent_level>
<child_level> CHILD OF <parent_level>…]
ATTRIBUTE <level> DETERMINES <dependent_column>
<level> DETERMINES <dependent_column>,…);
To validate a dimension:
exec dbms_olap.validate_dimension(<dim_name>,<owner>,FALSE,FALSE);
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Example of Creating A Dimension
CREATE DIMENSION time_dim
LEVEL CAL_DATE IS calendar.CAL_DATE
LEVEL PRD_ID
IS calendar.PRD_ID
LEVEL QTR_ID
IS calendar.QTR_ID
LEVEL YEAR_ID
IS calendar.YEAR_ID
LEVEL WEEK_IN_YEAR_ID IS calendar.WEEK_IN_YEAR_ID
HIERARCHY calendar_rollup
(CAL_DATE CHILD OF
PRD_ID CHILD OF
QTR_ID CHILD OF YEAR_ID)
HIERARCHY week_rollup
(CAL_DATE CHILD OF
WEEK_IN_YEAR_ID CHILD OF YEAR_ID)
ATTRIBUTE PRD_ID DETERMINES PRD_DESC
ATTRIBUTE QTR_ID DETERMINES QTR_DESC;
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Example of Validating A Dimension
SQL> exec dbms_olap.validate_dimension(‘time_dim’, USER, FALSE, FALSE);
PL/SQL procedure successfully completed.
SQL> select * from mview$_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);
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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;
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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>
2
3
4
select c.qtr_id, sum(l.gms) gms
from items l, calendar c
where l.end_date=c.cal_date
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)
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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>
2
3
4
select c.qtr_id, sum(l.gms) gms
from items l, calendar c
where l.end_date=c.cal_date
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)
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Summary
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Materialized Views
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Dimensions
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reduce system cpu/io resource requirements by precalculating 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
allow you to “tell” Oracle about complex data
relationships which can be used to rewrite queries
References
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Using Oracle9i Materialized Views (Technet Oracle By Example)
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Oracle Expert-One-On-One – Thomas Kyte
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The Secrets of Materialized Views
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http://www.akadia.com/services/ora_materialized_views.html
OLAP DB-Design with Dimensions
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http://www.akadia.com/services/ora_olap_dimensions.html
The Secrets of Dimensions
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http://technet.oracle.com/products/oracle9i/htdocs/9iober2/obe9ir2/obedwh/html/mv/mv.htm
http://www.akadia.com/services/ora_dimensions.html
Requirements for FAST REFRESH
Requirement
Must be based on detail tables only
Must be based on a single table
Each table can appear only once in the FROM list
Cannot contain nonrepeating expressions (ROWNUM, SYSDATE, etc)
Cannot contain references to RAW or LONG RAW
Cannot contain the GROUP BY clause
The SELECT list must include the ROWIDs of all the detail tables
Expressions can be included in the GROUP BY and SELECT clause as
long as they are the same in each
Aggregates are allowed but cannot be nested
If SELECT clause contains AVG, it must also contain COUNT
If SELECT clause contains SUM, it must also contain COUNT
If SELECT clause contains VARIANCE, it must also contain COUNT
and SUM
If SELECT clause contains STDDEV, it must also contain COUNT and
SUM
The join predicates of the WHERE clause can included AND but not OR
The HAVING and CONNECT BY clauses are not allowed
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Joins Only
Joins &
Single Table
Aggregates Aggregates
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Rqmts For FAST REFRESH (cont’d)
Requirement
Sub-queries, inline views, or set functions such as UNION are not
allowed
A WHERE clause is not allowed
COUNT(*) must be present
MIN and MAX are not allowed
Unique constraints must exist on the join columns of the inner table, if
an outer join is used
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
A materialized view log containing ROWID must exist for each detail
table
Any non aggregate expressions in the SELECT and GROUP BY
clauses must be non-modified columns
DML allowed on detailed tables
Direct path data load allowed
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Joins Only
X
Joins &
Single Table
Aggregates Aggregates
X
X
X
X
X
X
X
X
X
X
X
X
X
X