The document discusses using virtual columns in Oracle databases to implement business rules and uniqueness constraints across tables in a declarative way. Virtual columns allow expressing attributes as SQL expressions of real columns, enabling indexing and foreign key constraints that check rules involving multiple tables or columns. Business rules that were previously only possible through procedural logic can now be enforced at the database level through virtual columns.

1. Lucas Jellema (AMIS, The Netherlands)
THE VERY, VERY LATEST IN
ORACLE DATABASE DEVELOPMENT
Oracle Open World 2012, San Francisco

2. THE VERY VERY VERY LATEST…
<Secret Code>

3. THE DATABASE
IN MODERN ARCHITECTURES
Oracle Open World 2012, San Francisco

4. NO SQL

5. THE TOP-3 EARNING EMPLOYEES
• What can you say about the result of this query with
respect to the question: “Who are our top three
earning employees?”
A. Correct Answer
B. Sometimes correct
C. Correct if there are never duplicate
salaries
D. Not Correct

6. IN-LINE VIEWS

7. SPECIAL „BUSINESS RULE‟: DEFAULT VALUE
• The default values is the value that should be inserted
for a column when the client has ignored the column
– not provided a value nor indicated NULL
• The default value is applied prior to the execution of
the Before Row trigger
– So :new.<column_value> has the value that will be
inserted
– The Before Row trigger has no built in way to telling
whether the value was provided by the client or
supplied as default by the database
• Default value is typically used for auditing purposes
– Note: default values for columns exposed in UI should
be set in the client

8. COLUMN DEFAULT
• Columns can have default values
– Static or literals
– SQL expressions evaluating to a static
– Pseudo-columns like USER and CURRENT_DATE
• DO NOT USE SYSDATE! DO NOT USE USER!
– References to Application Context parameters
• sys_context(‘USERENV’, ‘IP_ADDRESS’)..
– Some funny value to let the before row trigger know
that the real (complex) default must be calculated
create table citizens
( name varchar2(100) default 'John Doe'
, birthdate date default current_date - 1
, city varchar2(50) default
sys_context('KANE_CTX', 'DEFAULT_CITY' )
, zipcode varchar2(8) default 'XYXYXYXYXQQ'
)

9. APPLICATION CONTEXT
• Memory area that enables application developers to
define, set, and access key/value pairs
Application
• Rapid access in SQL and PL/SQL Context
Attribute Value Attribute Value
Pairs
Attribute Value
select sys_context('USERENV', 'SESSION_USER')
from dual
l_user:= sys_context('USERENV', 'SESSION_USER')
• Two Application Contexts
are always around:
– CLIENTCONTEXT and USERENV

10. APPLICATION CONTEXT APPEARANCES
• Per session (default)
– Stored in UGA, just like package state
• Globally Accessible (shared across all sessions)
– Stored in SGA
• Associated with a Client Identifier
– Attributes in a Globally Accessible Application Context
can explicitly be tied to the Client Identifier
– And are only accessible to sessions with that Client
Identifier

11. TYPICAL WEB ARCHITECTURE USING
CONNECTION POOL
JDBC Connection Pool
Session 1 Session 2 Session 3 Session 4
Package A Package B Package C
globals

12. PACKAGE STATE IS TIED TO DATABASE
SESSION
JDBC Connection Pool
Session 1 Session 2 Session 3 Session 4
globals
Package A Package B Package C
globals

13. PACKAGE STATE IS TIED TO DATABASE
SESSION – NOT WEB SESSION
JDBC Connection Pool
Session 1 Session 2 Session 3 Session 4
globals
Package A Package B Package C
globals

14. APPLICATION CONTEXT TO RETAIN
STATE FOR LIGHT WEIGHT END USERS
JDBC Connection Pool
Session 1 Session 2 Session 3 Session 4
globals ?
Package A Package B Package C
globals

15. APPLICATION CONTEXT TO RETAIN
STATE FOR LIGHT WEIGHT END USERS
JDBC Connection Pool
Session 1 Session 2 Session 3 Session 4
USERENV USERENV
Package A Global Context Package C
globals globals
globals

16. APPLICATION CONTEXT TO RETAIN
STATE FOR LIGHT WEIGHT END USERS
JDBC Connection Pool
Session 1 Session 2 Session 3 Session 4
USERENV USERENV USERENV
Package A Global Context Package C
globals globals
globals

17. PACKAGE GLOBALS: THE STATE OF THE
PACKAGE IN A SESSION
• This state is lost when the package is recompiled
– That is undesirable in a highly available environment
Package

18. PACKAGE GLOBALS CAN BE REPLACED BY
APPLICATION CONTEXT
• The Application Context is untouched by
recompilation of the package
– All ‘globals’ in the application context retain their values
Package
Application Context

19. EBR TO KILL PLANNED DOWNTIME
(BECAUSE OF APPLICATION UPGRADE)
Application
Application X
X
VERSION 1
VERSION 2

20. TIME TRAVELLING

21. FLASHBACK
• Introduced in 9i
• Based on UNDO
• Initially only for recovery
• As of 11g – Total Recall option with
Flashback Data Archive
– Controlled history keeping
• Look back into history
– Query trends (version history)
– Difference reporting
– Audit trails (Replace journaling tables)
• Require trick for transaction history: WHO?
• Also: when is the start of history?

22. DATABASE IN MODERN ARCHITECTURE
Mobile WS
Business Tier Cache/Grid
Enterprise (L1, L2, L3)
Service Bus
Services
Standard
Application
Database s
Database Legacy
Application
s

23. MULTI TIER ARCHITECTURE
Mobile WS
Business Tier Cache/Grid
Enterprise HTTP REST JDBC (L1, L2, L3)
Service Bus HTTP SOAP JPA (H/EL)
FTP/WEBDAV
Services DB QRCN
HTTP
JMX, JMX
Monitor, Tra
ce, Audit Stored Encapsulation
Database Procedures Decoupling
Authentication & Caching
Fine Grained Business Logic
Authorization

24. APPLICATION ARCHITECTURE:
DRIVE APPLICATION FROM META DATA
• Agility
• Design Time at Run Time
• Define part of the application behavior and appearance
through meta-data (outside the base source code)
– The default settings are defined by developers and
deployed along with the application
– Read and interpreted at run time
– Manipulated and re-read
and re-interpreted at run time Application
• Note: very similar to the way
the database operates:
– Data Dictionary is the
meta-data driving the
behavior of the database meta

25. SEPARATE
BASE DATA AND CUSTOMIZED DATA
• If a value is changed during site-level implementation
– Or run time customization
• It should be kept apart from the base „meta-data‟
– To prevent overwriting customized data when the new
release arrives
– To allow for (temporarily) reverting to base data
• A simple solution: the Complex View with two
underlying tables approach
– Note: Select…
For Update Of
is not allowed ORIGINAL_NAME
IO trg
Customized
Values
New release BaseValues

26. REPLACE THE ORIGINAL SINGLE TABLE
WITH A TWO-TABLE BASE/CUSTOM SPLIT
• rename <original> to <base>
• create table <customizations>
as
select * from base where rownum = 0
• create or replace view <original>
as
select * from <customizations>
union all
select * from <base> b
left outer join
<customizations> c
on (b.id = c.id)
where c.rowid is null

27. REPLACE THE ORIGINAL SINGLE TABLE
WITH A TWO-TABLE BASE/CUSTOM SPLIT (2)
• create or replace trigger handle_insert_trg
instead of insert on original
for each row
begin
insert into <customizations> (col, col2,…)
values(:new.col, :new.col2,…);
end;
• create or replace trigger handle_update_trg
instead of update on original
for each row
begin
update <customizations>
set col = :new.col, …
where id = :new.id ;
if sql%rowcount = 0
then
insert into <customizations> (id, col, col2,…)
(select id, :new.col, :new.col2 from base where id = :new.id);
end if;
end;

28. APPLICATION ARCHITECTURE: NO SQL
• NO SQL
– Complex SQL is
hidden away inside
the database
– Cache to not have Web Browser
to query all the time
from the database
– … and to not take
the overhead of a
commit for not so
important data JEE Application Server
NO SQL
– Process first – in
memory, on
middle tier
(BigData and CEP) -
and only persist
what is useful RDBMS
SQL

29. QUERY RESULT CHANGE NOTIFICATION
• Continuous Query Notification:
– Send an event when the result set for a query changes
– Background process calls PL/SQL Handler or Java
Listener or OCI client when the
Java
commit has occurred Listener
– Event contains rowid
of changed rows
• Used for:
– Refreshing specific
data caches (middle
tier, global context)
– (custom) Replication
PL/SQL

30. CONTINUOUS PROCESSING OF DATA
STREAMS USING CQL
• Aggregation, Spot deviation, Match on complex
patterns

31. WHO IS AFRAID OF RED, YELLOW AND BLUE
• Table Events
– Column Seq number(5)
– Column Payload varchar2(200)

32. SOLUTION USING LEAD
• With LEAD it is easy to compare a row with its
successor(s)
– As long as the pattern is fixed, LEAD will suffice
with look_ahead_events as
( SELECT e.*
, lead(payload) over (order by seq) next_color
, lead(payload,2) over (order by seq) second_next_color
FROM events e
)
select seq
from look_ahead_events
where payload ='red'
and next_color ='yellow'
and second_next_color='blue'

33. THE SHOPPING ALGORITHM

34. THE SHOPPING ALGORITHM
• shopForItem Item ( String itemName) {
driveToShop;
Item item = buyItemAtShop ( itemName);
driveHomeFromShop;
return item;
}

35. GET THIS WEEK‟S GROCERIES
getGroceries Item[] ( String[] shoppingList) {
Item[] items = new Item[ shoppingList.length];
for (int i=0; i < shoppingList.length; i++) {
items[i] = shopForItem (shoppingList[i]);
}
return items;
}

36. PENSION FUND – SEPTEMBER 2012
Employer < >
Participants
Job & Benefits

37. FETCHING THE DATA OF THE PENSION
FUND FOR THE WEB APPLICATION
select *
1 record
< >
from employers
where id = < 324>
select * 100s records
from participants
where employer_id = < 324>
select * 10s records
from benefits
where participant_id = <#>

38. REPORTING ON MANY EMPLOYERS
select *
100s records
from employers 1 query
select * 10k records
from participants 100s queries
where employer_id = <#>
select * 100k records
from benefits 10k queries
where participant_id = <#>

39. APPLICATION ARCHITECTURE –
BULK RETRIEVE
• Have the database bulk up the data retrieval
• Return Ref Cursor, Types and Collections or
JSON/XML
Benefits Package
select *
from employers
where id in <some set> select *
from participants
where employer_id in <some set>
select b.*
from benefits b join participants p
on (p.id = b.participant_id)
where p.employer_id in <some set>

40. APPLICATION ARCHITECTURE –
SERVICE ENABLING
WebLogic Server Database
Native DB
WebService
HTTP EPG
Java/JEE
PL/SQL
package
SOA Suite JDBC
AQ
View
Oracle Other Table
Service Bus (Email, FTP/File, XML
DB
XMPP/Chat)
Chat/IM XMPP
Server File/FTP Server
Email Server

41. XML/JSON
Relational/Oracle Type
JEE Server Database
11g Native DB
WebService
HTTP
10g
http
ADF BC
EPG
JSON/ CSV
Java App SDO /SDO WS XML PL/SQL
XML & XSD
WS
JAX-WS
package
Ref Cursor
JPublisher
DB Types & Coll
SOA WS JDBC XML
8i Types
Suite AQ
Adapters
AQ
JMS Queue JMS
utl_file, View
JMS
BFILE,
Oracle EJB
EJB/JPA URITYPE
Service Pojo Other Table
(Email, FTP/File, 9i XML
Bus File
XMPP/Chat) DB
FTP UMS
Chat/IM XMPP
Server
File/FTP Server
Email Server

42. THE TALKING DATABASE
Details on the Employee. Employee
name is Smith, his job is Analyst. He
works in department 20…
EMP

43. THE TALKING DATABASE
PL/SQL
exposed through dbms_epg

44. BUSINESS RULES
• Data Oriented Rules or Data Constraints
• Declarative support in database
– For referential integrity
• Order must be for a Customer
– For attribute and tuple rules
• Salary must be numeric,
• Hiredate may not be in the future,
• End date must come after begin date
• No declarative support for complex data rules – across
multiple records and tables
– A department in France may not have less then 20%
female employees
– Order items of type weapon may not be part of an
order that ships around Christmas

45. BUSINESS RULES –
WHERE AND HOW TO IMPLEMENT
• Criteria:
– Safe
– Well performant
– Reusable and maintainable
– Productive to implement
• Options
– Client side
• JavaScript
– Middle-tier
• Java, Enterprise Service Bus
– Database
• Constraints and triggers are statement level – i/o
transaction level

46. RDBMS NOT ALWAYS EXCLUSIVELY
ACCESSED THROUGH ONE LAYER
SOA, ESB,
WebServices
Batch Bulk
Processes Standard
Applications
Database
Data Replication & Legacy
Synchronization Applications

47. 11G VIRTUAL COLUMNS
• Add columns to a table based on an
expression
– Using ‘real’ columns, SQL Function and User Defined
Functions
– No data is stored for Virtual
Columns, only meta-data
VIRTUAL
– Virtual Columns can be
indexed
alter table emp
ADD
(income AS (sal + nvl(comm,0)))

48. UNIQUENESS RULES
USING VIRTUAL COLUMNS
• Business Rule:
– Not more than one manager per department
alter table emp
add constraint only_one_mgr_in_dept_uk
unique (one_mgr_flag)
alter table emp
ADD
( one_mgr_flag as
( case when job ='MANAGER'
then deptno
end
)
)

49. CHALLENGE: ORDERS BELONG TO A
CUSTOMER IN ONE OF TWO TABLES
• The Orders table contains Order records for
customers – either Dutch or Australian customers
• These customers are stored in two different tables
• Can we implement referential integrity to ensure that
the order‟s customer exists?
OZ_CUSTOMER
ORDER
?
Id
Name
Country DUTCH_CUSTOMER
Customer_Id
…. Id
Name

50. USING VIRTUAL COLUMNS
IN FOREIGN KEY RELATIONS
• A foreign key can be created on a Virtual Column
– That means for example we can have a single column
with some id
– And two virtual columns with CASE expressions that
produce NULL or the ID value
– With Foreign Keys on the Virtual Columns
OZ_CUSTOMER
ORDER
Id
Country Name
DUTCH_CUSTOMER
Customer_Id
Dutch_id (VC) Id
Australian_id (VC) Name

51. USING VIRTUAL COLUMNS
IN FOREIGN KEY RELATIONS
alter table orders alter table orders
add (australian_ctr_id as add constraint odr_ocr_fk
(case country foreign key (australian_ctr_id)
when 'OZ' references oz_customer (id)
then customer_id
end))
OZ_CUSTOMER
ORDER
Id
Country Name
DUTCH_CUSTOMER
Customer_Id
Dutch_id (VC) Id
Australian_id (VC) Name
alter table orders
add (dutch_ctr_id as alter table orders
(case country add constraint odr_dcr_fk
when 'NL' foreign key (dutch_ctr_id)
then customer_id references dutch_customer
end)) (id)

52. FOREIGN KEY SHOULD ONLY REFER TO
CERTAIN RECORDS USING VC
• Foreign Key can reference a UK based on a Virtual
Column
• That allows a „conditional foreign key‟ or a foreign key
that can only reference specific records in the
referenced table
– Only refer to Women in the PEOPLE table for the
Mother Foreign Key
– Only refer to Values in the Domain Values table for the
Domain Name == ‘COLORS’

53. RESTRICTED FOREIGN KEYS USING
VIRTUAL COLUMNS
alter table domain_values
alter (country_value as
add table domain_values
(case domain_name
add (country_value as
alter table domain_values when 'COUNTRIES'
(case domain_name
then domain_value
when 'COUNTRIES'
add (color_value as end))
then domain_value
(case domain_name end))
when 'COLORS'
then domain_value DOMAIN_VALUES
end))
CARS Id
Domain_Name
Domain_Value
ID
Color_Value
Make Gender_Value
Type OrderStatus_Value
Color Country_Value
Year ShipmentMethod_Value
alter table cars
add constraint car_clr_fk
foreign key (color)
references domain_values
(color_value)

54. LACK OF WATERTIGHTNESS
IN TRIGGER BASED RULE VALIDATOIN

55. VALIDATION
• Statement time validation means:
DML in different session
DML More DML Commit
validation validation
• To prevent leakage we should validate at commit time
– Logically correct as transaction is the logical unit
– Effects from other sessions between statement and
commit are taken into account
• However: Oracle unfortunately does not provide us with
a pre-commit or on-commit trigger
• Workarounds:
– Dummy Table with Materialized View On Commit Refresh
and Trigger on Materialized View
– Do a soft-commit by calling a package to do the actual
commit – that will first do transaction level checks
• Supported by a deferred check constraint that is violated by
each operation that potentially violates a business rule

56. SAFE SOLUTION: USE CUSTOM LOCKS
• Prior to validating a certain business rule for a specific
record – acquire a custom lock
– That identifies both Rule and Record
– Using dbms_lock
DML in different session
DML More DML Commit
validation validation
• When a record is being validated for a certain rule,
other sessions have to wait
• The commit (or rollback) releases all locks
• Validation in a different session will include all
committed data

57. SUMMARY
• Inline Views
• Defaulting
• Application Context
• Flashback and the time dimension
• NoSQL means smart SQL
– Cache refresh driven by change notification
– Streaming analysis before persisting
• Decoupling galore
– Bulk retrieval
– Service enabling
• Business Rules
• EBR
• 12c promises even more