29
05/09/22 Yadav, Naresh 1 Materialized Views ORACLE

materialized view

Embed Size (px)

Citation preview

Page 1: materialized view

04/11/23 Yadav, Naresh 1

Materialized Views

ORACLE

Page 2: materialized view

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

Page 3: materialized view

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

Page 4: materialized view

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

Page 5: materialized view

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

Page 6: materialized view

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

Page 7: materialized view

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

Page 8: materialized view

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)

Page 9: materialized view

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

Page 10: materialized view

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

Page 11: materialized view

04/11/23 Yadav, Naresh 11

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

Page 12: materialized view

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;

Page 13: materialized view

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

Page 14: materialized view

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)

Page 15: materialized view

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)

Page 16: materialized view

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;

Page 17: materialized view

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

Page 18: materialized view

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

Page 19: materialized view

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

Page 20: materialized view

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);

Page 21: materialized view

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;

Page 22: materialized view

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);

Page 23: materialized view

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;

Page 24: materialized view

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)

Page 25: materialized view

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)

Page 26: materialized view

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

Page 27: materialized view

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

Page 28: materialized view

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

Page 29: materialized view

04/11/23 Yadav, Naresh 29

Materialized Views