Transcript DB2 Information Management Software Presentation Template

®
IBM Software Group
An In-depth Look at Active Data Features
- Constraints and Triggers – in DB2 LUW
Petrus Chan, IBM Toronto Lab, [email protected]
© 2009 IBM Corporation
IBM Software Group | DB2 information management software
Agenda
 Active Data Features
 Overview of SQL Processing in DB2
 Constraints
 Triggers
 Semantic Query Optimization in DB2
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IBM Software Group | DB2 information management software
Active Data Features
 a mechanism whereby an SQL statement can invoke an action
that is not explicitly specified by the SQL statement
 Can be used to enable business rules enforcement
 Event – Condition – Action

when
Event

if
Database event
•
Update, delete, insert
Search condition on
Condition
•
Transition values
Database or External Action

•
then
Action
e.g. alert, reject,
fix up, log
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Categories of Active Data Features
 Constraints
 Declarative rules that ensure the validity of data values
 Triggers
 Automatic procedural actions that are triggered by update events on a given
table
 Materialized Query Table (MQT) maintenance
 Maintenance of materialized query results stored in a table, which can be used
by DB2 Optimizer to significantly improve performance of complex queries.
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Access Plan:
----------Total Cost: 63.9241
Query Degree: 1
Overview of SQL processing in DB2
Rows
RETURN
(
1)
Cost
I/O
|
25
GRPBY
(
2)
63.4613
2
|
829.44
MSJOIN
(
3)
55.1569
2
/---+----\
144
5.76
TBSCAN
FILTER
(
4)
(
7)
23.8489
23.6013
1
1
|
|
144
144
SORT
TBSCAN
(
5)
(
8)
23.7975
23.6013
1
1
|
|
144
144
TBSCAN
SORT
(
6)
(
9)
19.4513
23.5498
1
1
|
|
144
144
TABLE: PETRUS3
TBSCAN
T2
( 10)
Q1
19.4513
1
|
144
TABLE: PETRUS3
T1
Q2
Query
SELECT t1.c1,
sum (t2.c2)
FROM T1, T2
WHERE t1.c1 = t2.c1
GROUP BY t1.c1;
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IBM Software Group | DB2 information management software
Agenda
 Active Data Features
 Overview of SQL Processing in DB2
 Constraints
 Triggers
 Semantic Query Optimization in DB2
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IBM Software Group | DB2 information management software
Constraints in DB2
 Domain constraints – data type, nullability
 Key constraints – primary, unique
 Check constraints – domain restriction, primitive business rules
 Referential integrity constraints – foreign key
 Generated columns – derived attributes
 Functional dependencies – determined by
 Symmetric views – with check option
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Primary/Unique Key Constraints
 Purpose
 Enforcing the primary or candidate key semantics of an attribute
 Specification
CREATE TABLE PERSON(SSN INT NOT NULL UNIQUE, …);
CREATE TABLE PERSON(SSN INT NOT NULL, …, PRIMARY KEY(SSN));
ALTER TABLE PERSON ADD CONSTRAINT ssn_uk UNIQUE(SSN);
 Implementation
 Enforced by DB2 through the creation of a unique index on the columns of
the key.
 Semantically enforced as an end of statement constraint, through a
mechanism called deferred unique checking. UPDATE T SET C1 = C1+1
can be executed without raising an error.
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Check Constraints
 Purpose
 Can be used to enforce/restrict the domain of an attribute
 Can implement simple business rules based on values of other columns of
the same data row, e.g., CHECK(ship_date >= order_date)
 Specification
CREATE TABLE SALES_2004(ITEM_ID CHAR(16), SALE_DATE DATE
CHECK(SALE_DATE BETWEEN 01/01/2004 AND 12/31/2004), …);
ALTER TABLE EMPLOYEE ADD CONSTRAINT check_sex CHECK( SEX IN
(‘M’, ‘F’));
 Implementation
 Additional predicate corresponding to the check constraint is compiled into
the query graph of any INSERT, UPDATE or DELETE statements modifying
a given table
 Evaluated using the “after” image for each row, error is raised when check
condition is not satisfied
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Check constraints - example
db2 => ALTER TABLE EMPLOYEE ADD CONSTRAINT
chk_sex CHECK(sex IN ('M','F'))
db2 => INSERT INTO EMPLOYEE
VALUES('000070', 'EVA', 'D', 'PULASKI', …)
2) FILTER: (Filter)
...
Predicate Text:
-------------(1 =
CASE
WHEN NOT(Q4.$C0 IN ('M', 'F'))
THEN RAISE_ERROR(-545,
‘PETRUS.EMPLOYEE.CHK_SEX.')
ELSE 0 END)
Access Plan:
----------Total Cost:
13.3724
Query Degree: 1
Rows
RETURN
(
1)
Cost
I/O
|
0.04
FILTER
(
2)
13.3724
1
|
1
INSERT
(
3)
13.2904
1
/---+--\
1
77
TBSCAN TABLE: ADMIN
(
4)
EMPLOYEE
0.0048
0
|
1
TABFNC: SYSIBM
GENROW
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IBM Software Group | DB2 information management software
Referential Integrity

Purpose
 Defines an inclusion relationship between a foreign key (set of columns in the
referencing/child table) and a primary key (set of columns in the
referenced/parent table)
 Simply put, any non-NULL values of the foreign key must be present as a
value of the corresponding primary/unique key.

Specification (can be provided during CREATE or ALTER table)
 The definition of the referencing table (child table) contains a clause of the
form: FOREIGN KEY fk_name(fk_col1, fk_col2, …)
REFERENCES parent_table(pk_col1, pk_col2, …)
<cascading options>
where <cascading options> can be one or more of:
–
ON DELETE [ NO ACTION | RESTRICT | CASCADE | SET NULL ]
–
ON UPDATE [ NO ACTION | RESTRICT ]
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Referential Integrity (cont’d)
 Implementation
 UPDATE/INSERT of child table’s foreign key columns:
 Additional processing compiled into query graph to:
– Look up primary key values in the parent table.
– Raise error if not found.
 UPDATE/DELETE of parent.
 Additional processing compiled into query graph to:
 Depends on ON UPDATE and ON DELETE cascading options:
– RESTRICT – raise error if old value of the parent columns still has
corresponding children
– SET NULL – set foreign key columns in child table to NULL
– CASCADE – delete the children rows
– NO ACTION (default) – similar to RESTRICT, but enforced after other
constraints
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Referential integrity - example
Access Plan:
----------Total Cost:
Query Degree:
Rows
RETURN
(
1)
Cost
I/O
|
0.1232
FILTER
(
2)
77.8767
5.08
/--------+--------\
db2 => ALTER TABLE EMPLOYEE ADD CONSTRAINT
dept_fk FOREIGN KEY (workdept)
REFERENCES DEPARTMENT(deptno) ON
DELETE SET NULL ON UPDATE RESTRICT
db2 => UPDATE EMPLOYEE SET workdept=‘871’
WHERE empno=‘000010’
2) FILTER: (Filter)
...
Predicate Text:
-------------(1 =
CASE
WHEN (Q4.$C0 IS NOT NULL AND NOT EXISTS(SELECT
$RID$
FROM ADMIN.DEPARTMENT AS Q5
WHERE ('871' = Q5.DEPTNO)))
THEN RAISE_ERROR(-530, 'ADMIN.EMPLOYEE.DEPT_FK.')
ELSE 2 END)
77.8767
1
3.08
UPDATE
(
3)
75.557
5.08
/---+--\
3.08
TBSCAN
77
TABLE: ADMIN
1
IXSCAN
(
5)
1.97248
0
|
47
INDEX:
ADMIN
(
4)
34.747
2
|
77
TABLE: ADMIN
EMPLOYEE
DEPT_PK
EMPLOYEE
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IBM Software Group | DB2 information management software
Rows
RETURN
nd
(
1)
Cost
I/O
Cascaded
|
Update
3.08
db2 => DELETE FROM DEPARTMENT WHERE deptno='E11'
UPDATE
(
2)
90.8877
6.08
/---+--\
3.08
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3) NLJOIN: (Nested Loop Join)
NLJOIN TABLE: ADMIN
…
(
3)
EMPLOYEE
Predicate Text:
50.005
-------------3
Table Scan!
(Q5.$C0 = Q6.WORKDEPT)
/---------+--------\
1
3.08
Old deptno value
DELETE
TBSCAN
(
4)
(
6)
15.2581
34.747
1
2
 Note the table scan when
/---+---\
|
1
47
77
executing the look up of the
IXSCAN
TABLE: ADMIN
TABLE: ADMIN
secondary table.
(
5)
DEPARTMENT
EMPLOYEE
1.97248
 Create index on foreign key
0
|
columns to avoid this
47
INDEX: ADMIN
Referential integrity – 2
example
DEPT_PK
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Generated columns
 Purpose
 Deriving values of a column based on other columns on the same row
 Specification (CREATE or ALTER TABLE)
CREATE TABLE Persons(first_name VARCHAR(64), last_name VARCHAR(64),
last_name_upper GENERATED ALWAYS AS UPPER(last_name));
 Implementation
 The SQL compiler will substitute the column value or the DEFAULT keyword
with the generated column expression whenever necessary
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Generated columns - Example
 Can be used to implement “index on expression”:
 create index idx1 on table_name (expr(col1))
 Instead:
 create generated column col2 as expr(col1)
 create index on generated column c2
 NOT ALLOWED
 A typical MDC example:
CREATE TABLE ORDERS( O_ORDKEY INT NOT NULL, O_CUSTKEY INT NOT NULL,
O_PRICE FLOAT NOT NULL, O_ORDERDATE DATE NOT NULL,
OG_ORDERMONTH GENERATED ALWAYS AS (INTEGER(O_ORDERDATE)/100),
PRIMARY KEY o_key (O_ORDERKEY))
ORGANIZE BY ( OG_ORDERMONTH );

The default value for the generated column will be replaced by the generated
column expression.
INSERT INTO ORDERS VALUES(151, 32, 16.97, CURRENT DATE, DEFAULT);
---> INSERT INTO ORDERS VALUES(151, 32, 16.97, CURRENT DATE, INTEGER(CURRENT DATE)/100);
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Functional dependencies
 Purpose
 To capture the functional dependency between columns of the same table,
other than the implicit dependency on the key
 Can occur due to denormalization
 Typical example: attribute_code  attribute_description
 Specification
CREATE TABLE PRODUCT(prod_key CHAR(15) NOT NULL, smu_code
VARCHAR(6) NOT NULL, smu_desc VARCHAR(35), ..., prod_desc
VARCHAR(30), CONSTRAINT FD1 CHECK (smu_desc DETERMINED BY
smu_code) NOT ENFORCED ENABLE QUERY OPTIMIZATION;
ALTER TABLE product ADD CHECK ( prod_desc DETERMINED BY
prod_key) NOT ENFORCED;
 Implementation
 Purely informational, currently cannot be created as enforced
 Currently exploited during MQT matching, possible other uses in the future
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Symmetric views – Views with CHECK OPTION
 Purpose
 Often, views are created to control user’s access to base table.
 Regular views do not restrict modifications that do not conform to view definition.
Example:
 Create view view1 as (SELECT * FROM EMPLOYEE WHERE WORKDEPT=‘E21’)
 User can insert into view1 with workdept = E22
 But subsequent select * from view1 cannot see the row.
 View with CHECK OPTION (or Symmetric View) can be used to restrict the
modification.
 Specification
CREATE VIEW DEPT_E21_EMPLOYEES AS
(SELECT * FROM EMPLOYEE WHERE WORKDEPT=‘E21’) WITH CHECK OPTION;
 Implementation
 Similar to a check constraint, any predicate in the where clause of the view are applied
against the new values of the rows during an update through the view.
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Symmetric views – Views with CHECK OPTION (2)
 LOCAL vs. CASCADED CHECK OPTION
 View over another view
 LOCAL – must satisfy definitions of current view and all underlying views that
also have a check option
 CASCADED (default) – must satisfy definitions of current view and all
underlying views, regardless of whether they have a check option or not.
create view VIEW1 as Select
empno, empname, deptno from
EMP where dept10 = 10;
Create view VIEW2 as Select
empno, empname, deptno from
VIEW1 where empno > 20
Predicates
checked
Y=LOCAL
Y=CASCADED
view1
none
none
view2
empno > 20
dept10 = 10
Empno > 20
WITH Y CHECK OPTION;
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Costs vs. Benefits of Constraints
Benefit of
(1) Preventing application
errors
vs.
Cost of data integrity
enforcement /
maintenance
(2) Enabling optimizations

Informational Constraints: if the integrity is enforced outside of the
database (e.g. ETL processes), informational constraints can provide
the benefit without the additional cost
db2 => ALTER TABLE DEPARTMENT ALTER FOREIGN KEY dept_fk NOT ENFORCED
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Enforced vs. Informational Constraints
 By default:
 the constraints are enforced by the database engine, frequently there is cost
associated with enforcement.
 all constraints are exploited during query optimization
 Check and Referential Integrity constraints can be ENFORCED or
NOT
 Functional dependencies purely informational (cannot be enforced)
 If an informational constraint is enabled for query optimization, then
the user must ensure that informational constraints are satisfied at all
times, otherwise the query results could become incorrect
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Agenda
 Active Data Features
 Overview of SQL Processing in DB2
 Constraints
 Triggers
 Semantic Query Optimization in DB2
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Introduction to Triggers
 Automatic procedural actions that are triggered by update events on
a given table
 Trigger types: BEFORE, AFTER and … INSTEAD OF
 Granularity: trigger execution can be either per row, or per statement
 Procedural SQL extensions can be used to implement the trigger logic
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For each row triggers - BEFORE
 Usually used to validate or fix up data before modification
 Typical application: look at the new value of one or more columns of
the current row, compare it to other rows in the table (possibly using
aggregation) or reference against another table, if value doesn’t
conform, fix it up or raise an error.
 No database modifications are allowed inside before triggers
 Simple before triggers are “inlined” into the main data flow, more
complex ones will result in a join below the U/D/I operation
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BEFORE trigger - example
 Sample business rule: Disallow
salary increases of over 25%
CREATE TRIGGER VERIFY_RAISE
NO CASCADE
BEFORE UPDATE OF SALARY ON EMPLOYEE
REFERENCING NEW AS N OLD AS O
FOR EACH ROW
MODE DB2SQL
WHEN(N.SALARY > O.SALARY*1.25)
SIGNAL SQLSTATE ‘75000’
(‘Salary increase over limit’);
Rows
RETURN
(
1)
Cost
I/O
|
77
UPDATE
(
2)
1015.6
79
/---+---\
77
77
FILTER
TABLE: ADMIN
(
3)
EMPLOYEE
25.8637
2
|
77
FILTER
(
4)
25.8115
2
This trigger is
|
“inlined” here.
77
Typically you would
TBSCAN
expect the trigger
(
5)
body joined to the
25.7725
main flow of data.
2
|
77
TABLE: ADMIN
EMPLOYEE
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For each row triggers - AFTER
 Can be used for:
 database assertion validation based on the after state
 Example: archiving, versioning and replication of data
 Executed once per each row modification
 Can access the row transition variables NEW and OLD, corresponding
to the before and after image of the row
 Body can contain arbitrarily complex procedural-like logic inside a
BEGIN ATOMIC … END block
 Starting in V82 DB2 offers the ability to issue a CALL statement within
a trigger body to invoke a stored procedure.
 Packaged trigger (in development)
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AFTER row level trigger - example
 Implementing versioning with an
after for each row trigger:
CREATE TRIGGER AFTTR1
AFTER UPDATE OF WORKDEPT ON EMPLOYEE
REFERENCING OLD AS O
FOR EACH ROW MODE DB2SQL
BEGIN ATOMIC
DECLARE LAST_NEWEST DATE;
SET LAST_NEWEST =
(SELECT END_DATE
FROM EMP_DEPT_HISTORY
WHERE EMPNO=O.EMPNO
ORDER BY 1 DESC
FETCH FIRST 1 ROW ONLY);
INSERT INTO EMP_DEPT_HISTORY
VALUES(O.EMPNO, O.WORKDEPT,
LAST_NEWEST, CURRENT DATE);
END%
UPDATE EMPLOYEE SET WORDEPT=‘D21’
WHERE EMPNO=‘000230’%
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For each statement triggers - AFTER
 Executed once per triggering statement, even if no rows affected by
the update/delete/insert
 Can reference the set of old and new row values via the transition
tables
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AFTER statement level trigger - example
 Auditing of table data changes
CREATE TRIGGER EMP_AUDIT
AFTER UPDATE ON EMPLOYEE
REFERENCING OLD_TABLE AS OLDT NEW_TABLE AS NEWT
FOR EACH STATEMENT MODE DB2SQL
INSERT INTO EMP_AUDIT
SELECT O.EMPNO, O.LASTNAME, N.LASTNAME,
O.WORKDEPT, N.WORKDEPT, O.PHONENO,
N.PHONENO, O.JOB, N.JOB, O.EDLEVEL,
N.EDLEVEL, O.SALARY, N.SALARY,
O.BONUS, N.BONUS, O.COMM, N.COMM
FROM OLDT O, NEWT N
WHERE O.EMPNO=N.EMPNO;
UPDATE EMPLOYEE SET WORKDEPT=‘D21’
WHERE EMPNO=‘000230’;
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Triggers on Views – INSTEAD OF
 Some views are considered not
updatable by DB2.
 Example: view with joins
 Instead Of Trigger on a view allows
you to “intercept” the
update/delete/insert issued against
the view and replace it with
operations on the underlying tables.
 Currently only row level INSTEAD
OF triggers supported in DB2
 Execute at the same time as after
triggers
CREATE VIEW EMPLOYEE_WITH_DEPT_INFO AS
(SELECT E.*, D.DEPTNAME, D.MGRNO, D.LOCATION
FROM EMPLOYEE E, DEPARTMENT D
WHERE E.WORKDEPT = D.DEPTNO);
CREATE TRIGGER INSTTR1
INSTEAD OF UPDATE ON EMPLOYEE_WITH_DEPT_INFO
REFERENCING NEW AS N
FOR EACH ROW MODE DB2SQL
BEGIN ATOMIC
UPDATE EMPLOYEE E SET
(FIRSTNME, MIDINIT, LASTNAME, WORKDEPT,
PHONENO, HIREDATE, JOB, EDLEVEL, SEX,
BIRTHDATE, SALARY, BONUS, COMM) =
(N.FIRSTNME, N.MIDINIT, N.LASTNAME,
N.WORKDEPT, N.PHONENO, N.HIREDATE, N.JOB,
N.EDLEVEL, N.SEX, N.BIRTHDATE, N.SALARY,
N.BONUS, N.COMM)
WHERE N.EMPNO = E.EMPNO;-UPDATE DEPARTMENT D
SET (DEPTNAME, MGRNO, LOCATION) =
(N.DEPTNAME, N.MGRNO, N.LOCATION)
WHERE N.WORKDEPT = D.DEPTNO;-END;
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INSTEAD OF trigger - example
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Interaction of Triggers and Constraints
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Database utilities and constraints and triggers
 Implications of triggers and constraints for utilities:
 Bulk LOAD utility:
 Data type, nullability and key constraints enforced during load.
 Referential integrity and check constraints not verified during load
– table placed in check pending state after load
– constraints must be verified in a separate step using the SET
INTEGRITY statement.
 If load was incremental (append) the constraint checking will be
incremental as well
 Generated columns can be generate during load, or by SET INTEGRITY
 Triggers not fired!
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Agenda
 Active Data Features
 Overview of SQL Processing in DB2
 Constraints
 Triggers
 Semantic Query Optimization in DB2
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Overview of SQL processing in DB2
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IBM Software Group | DB2 information management software
Semantic Query Optimization in DB2
 Semantic query optimization (SQO) = the use of integrity constraints
to optimize the evaluation of a query
 Mostly during the query rewrite and query optimization phases
 elimination of unnecessary processing based on additional semantic
information provided by the integrity constraints
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Exploiting Check Constraints
 Check constraint and generated column serve as derived predicate.
 The predicate will be exploited by DB2 Query Rewrite Theorem Prover.
 One common usage is to prove a FALSE predicate for the elimination of a
subgraph or a branch
 Example:
Check Constraint: alter table t1 add constraint chk1 check (c1 > 5)
Query:
select * from t1 where c1 < 5
 Query Rewrite will prove that no row in T1 will satisfy the 2 predicates – will replace it
with a FALSE predicate (1=0).
 The subgraph that evaluates the scan of T1 will be changed to:
Select * from values(1) where 1=0
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Exploiting Check Constraints: Another Example
 create view SALES
(SALES_2006 UNION ALL
SALES_2007 UNION ALL
SALES_2008)
 Check constraints:
SALES_2006 - check (Year = 2006)
SALES_2007 - check (Year = 2007)
SALES_2008 - check (Year = 2008)
 Query:
select * from SALES where Year = 2007
Query Rewrite will:
(1) Compile in the check constraint
predicate
(2) push down the predicate Year=2007
through union all operations
(3) derives a FALSE predicate for branch
2006 and 2008
(4) eliminates the two branches altogether
SELECT …
WHERE YEAR=2007
PUSH DOWN
(YEAR=2007)
THRU UNION ALL
PREDICATE DERIVED
FROM THE CHECK
CONSTRAINT
UNION ALL
SELECT
(YEAR = 2006)
SELECT
(YEAR = 2007)
SELECT
(YEAR = 2008)
SALES_2006
SALES_2007
SALES_2008
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Exploiting Referential Integrity
 Redundant join elimination
CREATE VIEW EMPLOYEE_WITH_DEPT_INFO AS
(SELECT E.*, D.DEPTNAME,
D.MGRNO, D.LOCATION
FROM EMPLOYEE E, DEPARTMENT D
WHERE E.WORKDEPT = D.DEPTNO);
select empno, lastname, workdept
from employee_with_dept_info;
 Join with the
DEPARTMENT table
eliminated entirely from
the query
 Need to compensate with
workdept is not null
SELECT
SELECT
JOIN
EMPLOYEE
EMPLOYEE
DEPARTMENT
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Exploiting Referential Integrity (2)
 Group by pushdown through join
select deptno, deptname,
sum(salary)
from employee, department
where workdept=deptno
group by deptno, deptname
GROUP BY pushed
down below the join
(along the child table)
GROUPBY
JOIN
EMPLOYEE
DEPARTMENT
=> reduces number of
rows participating in the
join
GROUPBY
JOIN
DEPARTMENT
EMPLOYEE
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Exploiting Generated Columns
CREATE TABLE ORDERS( O_ORDKEY INT NOT NULL, O_CUSTKEY INT NOT NULL,
O_PRICE FLOAT NOT NULL, O_ORDERDATE DATE NOT NULL,
...
OG_ORDERMONTH GENERATED ALWAYS AS (INTEGER(O_ORDERDATE)/100),
PRIMARY KEY o_key (O_ORDERKEY))
ORGANIZE BY ( OG_ORDERMONTH );
SELECT * FROM ORDERS WHERE INTEGER(O_ORDERDATE)/100 = 200901;
---> SELECT FROM ORDERS WHERE OG_ORDERMONTH = 200901;

The generated expression in the query will be replaced by the
generated column.

The predicate on generated column is used to exploit an index
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Exploiting NOT NULL constraint, Uniqueness and
Functional Dependency
 NOT NULL
 Example: MQT matching (more on this later)
 Whenever possible declare columns as NOT NULL, do not leave nullable by
default.
 Uniqueness
 can be exploited to remove DISTINCT processing, explicit and implicit, to avoid
unnecessary SORT operators:
 Example 1:
create table emp (empno int not null unique, empname char(30));
select distinct * from emp ;
 Example 2: MERGE statement duplicate checking
 Functional Dependency
 Example: MQT matching (more on this later)
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Summary
 Data integrity constraints implement business rules and application
logic within the database server
 If data integrity is maintained outside of the database, informational
constraints can be defined
 Constraints provide valuable information to Query Rewrite for query
optimization
 Triggers offer more flexibility by allowing procedural logic
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IBM Software Group | DB2 information management software
Selected Further Reading
 Roberta Cochrane, Hamid Pirahesh, Nelson Mendonça Mattos:
Integrating Triggers and Declarative Constraints in SQL Database
Sytems. VLDB 1996: 567-578
 Hamid Pirahesh, T. Y. Cliff Leung, Waqar Hasan: A Rule Engine for
Query Transformation in Starburst and IBM DB2 C/S DBMS. ICDE
1997: 391-400
 Qi Cheng, Jarek Gryz, Fred Koo, T. Y. Cliff Leung, Linqi Liu, Xiaoyan
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