© 2009 IBM Corporation
IBM Information Management
Integrated Data Management
Vision and Roadmap
Curt Cotner
IBM Fellow
Vice President and CTO for IBM Database Servers
cotner@us.ibm.com
IBM Information Management
© 2009 IBM Corporation
2
What do Businesses Have?
A Collection of Disparate, Single
-
Purpose Products
CA ERwin
IBM InfoSphere Data Architect
Embarcadero ER/Studio
Sybase PowerDesigner
Design
IBM DB2 tools
BMC Patrol
Quest Central
Oracle Diagnostic
Pack
Operate
Oracle Tuning Pack
Solix EDMS
IBM Optim Data Growth Solution
Optimize
Quest Spotlight
Quest TOAD
IBM Data Studio Developer
Oracle JDeveloper
Develop
Embarcadero
Rapid SQL
IBM Comparison
Tool for DB2 z/OS
Embarcadero
Change Manager
Data Studio
Administrator
Deploy
Oracle Change
Management Pack
Quest
InTrust
Guardium
IBM Optim
Govern
Oracle
Vault
IBM Information Management
© 2009 IBM Corporation
The gaps create risk …
Loss of customers
Average customer churn rate up
2.5
%
after a breach
Loss of revenue
$
197
USD per customer record leaked
Average cost was ~ $
6.3
million / breach
in this study
Average cost for financial services
organizations was
17
% higher than
average
Fines, penalties or inability to
conduct business based on non
-
compliance
PCI
Sarbanes
-
Oxley (SOX)
HIPAA
Data Breach Disclosure Laws
Gramm
-
Leach
-
Bliley Act
Basel II
Source: “2007 Annual Study: Cost of a Data Breach” , The Ponemon Institute
IBM Information Management
© 2009 IBM Corporation
4
Driven by the increasing
numbers of physical
systems, system
management
has become the main
component of IT costs
and is growing rapidly
Many Servers, Much Capacity, Low Utilization =
$140B unutilized server assets
IBM Information Management
© 2009 IBM Corporation
5
What do Businesses Need?
An integrated environment to span today’s flexible roles
Manage data throughout its lifecycle
From design to sunset
Manage data across complex IT environments
Multiple interrelated databases, applications and platforms
Facilitate cross
-
functional collaboration
Within IT
Among Line of Business, Compliance functions
Across disparate skill sets
Optimize business value
Respond quickly to emerging opportunities
Improve quality of service
Reduce cost of ownership
Mitigate risk
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Introducing Integrated Data Management
Enabling organizations to more efficiently and effectively
Respond to emergent, data
-
intensive business opportunities
Meet service level agreements for data
-
driven applications
Comply with data privacy and data retention regulations
Grow the business while driving down total cost of ownership
An integrated, modular environment to design, develop, deploy,
operate, optimize and govern enterprise data throughout its
lifecycle on the System z platform
IBM Information Management
© 2009 IBM Corporation
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Integrated Data Management
Deliver increasing value across
the lifecycle
,
from requirements to
retirement
Facilitate collaboration and
efficiency across roles,
via
shared artifacts automation and
consistent interfaces
Increase ability to meet service
level agreements,
improving
problem isolation, performance
optimization, capacity planning,
and workload and impact analysis
Comply with data security,
privacy, and retention policies
leveraging shared policy, services,
and reporting infrastructure
Develop
Design
Deploy
Optimize
Operate
Models
Policies
Metadata
IBM Information Management
© 2009 IBM Corporation
8
InfoSphere Data Architect
Data Studio Developer
Optim Test Data Management
Optim Data Growth Solutions
Optim Data Privacy Solutions
The broadest range of capabilities for
managing the value of your data throughout its
lifetime
DB2 Performance Expert and
Extended Insight Feature
Data Studio pureQuery Runtime
DB2 Audit Management Expert
Database Encryption Expert
Data Studio Administrator
Develop
Design
Deploy
Optimize
Operate
Policies
Models
Metadata
DB
2
Optim Query Tuner
(a.k.a. Optimization Expert)
IBM Information Management
© 2009 IBM Corporation
9
Model
-
driven Governance
–
Automating Governance
Policies
Develop
Design
Deploy
Optimize
Operate
Standards
Models
Policies
Data Architect
Design
Discover,
import,
model,
relate,
standardize
Data Studio Administrator automatically checks
that encryption is used for the table containing
CCN due to PCI DSS rules.
Data Studio Administrator would create fine grained
access control rules to prevent DBAs or other
unauthorized people from viewing CCN values.
Our Design tool has been
extended to include
application context
information about the
customer’s data. For
example:
semantic meaning (SSN,
home phone number,
medical privacy data, credit
card number, PIN code,
etc.)
masking algorithm that
should be used to present
the data in reports
Data Architect specifies column CCN
contains a credit card number, and the
data masking algorithm.
Data Studio Developer would prevent copy of rows
containing CCN column values from PROD to TEST
due to PCI DSS rules, unless Optim product is used
to anonymize data.
Data Architect emits runtime
metadata for Optim so that it knows
which columns to anonymize, etc.
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© 2009 IBM Corporation
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InfoSphere Data Architect
InfoSphere Data Architect is a collaborative, data design solution
to discover, model, relate, and standardize diverse data assets.
Key Features
Create logical and physical data models
Discover, explore, and visualize the
structure of data sources
Discover or identify relationships
between disparate data sources
Compare and synchronize the structure
of two data sources
Analyze and enforce compliance to
enterprise standards
Support across heterogeneous
databases
Integration with the Rational Software
Delivery Platform, Optim, IBM
Information Server, and IBM Industry
Models
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© 2009 IBM Corporation
Protect Privacy
De
-
identify Data
Encrypt Data
Secure Data
Prevent Access
Restrict Access
Monitor Access
Audit Data
Audit Access
Audit Privileges
Audit Users
Optim Data Privacy Solution
Database Encryption Expert
Label Based Access Control
Trusted Context
Data Studio Developer and
pureQuery Runtime
Data Governance
Retain Data
Data Archival
Data Retention
Data Retirement
DB2 Audit Management Expert
Tivoli Security Information and
Event Manager
Optim Data Growth Solution
Manage Lifecycle
Model policies
Integrate tools
InfoSphere Data Architect
Optim Test Data Management
IBM Information Management
© 2009 IBM Corporation
12
Data Studio Administrator
GA July 2008 for DB2 LUW servers
Compare, Sync and Alter
DDL roundtrip support
Extended Alter
Impact Analysis
Change model
Physical modeling,
Unified Change Project
Advanced Data Movement (HPU)
Scheduling & Enhanced Advanced Deployment
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© 2009 IBM Corporation
13
13
High Performance Unload
What is it?
A utility for unloading data at very high speed (minimum wall clock time). Also can extract
individual tables from DB2 backups. While unloading, it can repartition the data for even faster,
parallel reloading on a different system which has a different partitioning layout from the one
being unloaded from.
What’s its value to customers?
Reduced costs by speeding up operations which require the unloading of large amounts of DB2
data.
Been used in a number of disaster recovery situations by extracting individual tables from DB2
backups.
Speeding up the process of migrating a DB2 server to new hardware.
New features and functions:
System migration performed entirely by HPU. The unloading and repartitioning of the data,
sending of it across the network and loading using DB2 LOAD command all handled by HPU.
•
Today, you have to build complicated scripts to do this process
Improved autonomics. One memory tuning parameter instead of several. Tell HPU how much
memory it can use, and HPU will figure out the best way to use it.
Simplification of syntax by eliminating some keywords for specifying certain HPU functions
through the use of “templates” to define the output file names.
•
Existing syntax also supported for backward compatibility
Modified 12/07/2006
© 2009 IBM Corporation
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Optimizing Your WebSphere Applications
with Data Studio
IBM Information Management
© 2009 IBM Corporation
15
What’s so Great About DB2 Accounting for CICS Apps?
z/OS LPAR
CICS AOR1
Txn1
-
Pgm1
-
Pgm2
CICS AOR2
TxnA
-
PgmX
-
PgmY
DB2PROD
CICS AOR3
Txn1
-
Pgm1
-
Pgm2
App CPU PLAN
Txn1 2.1
TN1PLN
TxnA 8.3
TNAPLN
DB2 Accounting for CICS apps allows you to study
performance data from many perspectives:
•
By transaction (PLAN name)
•
By program (package level accounting)
•
By address space (AOR name)
•
By end user ID (CICS thread reuse)
This flexibility makes it very easy to isolate performance
problems, perform capacity planning exercises, analyze
program changes for performance regression, compare
one user’s resource usage to another’s, etc.
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JDBC Performance Reporting and Problem Determination
–
Before pureQuery
Application Server
DB
2
or IDS
A1
A2
A5
A3
A6
A4
USER1
USER
1
USER1
User CPU
PACKAGE
USER1 2.1 JDBC
USER1 8.3 JDBC
USER1 22.0 JDBC
What is visible to the DBA?
-
IP address of WAS app server
-
Connection pooling userid for WAS
-
app is running JDBC or CLI
What is not known by the DBA?
-
which app is running?
-
which developer wrote the app?
-
what other SQL does this app issue?
-
when was the app last changed?
-
how has CPU changed over time?
-
etc.
Data Access Logic
Persistence Layer
DB2 Java Driver
EJB Query Language
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What’s so Great About Data Studio pureQuery Accounting for
WebSphere Applications?
z/OS LPAR
CICS AOR2
TxnA (PLANA)
-
PgmX
-
PgmY
App CPU
TxnA 2.1
TxnB 8.3
Data Studio and pureQuery provide the same granularity
for reporting WebSphere’s DB2 resources that we have
with CICS:
•
By transaction (Set Client Application name )
•
By class name (program
-
package level accounting)
•
By address space (IP address)
•
By end user ID (DB2 trusted context and DB2 Roles)
This flexibility makes it very easy to isolate performance
problems, perform capacity planning exercises, analyze
program changes for performance regression, compare
one user’s resource usage to another’s, etc.
Unix or Windows
WAS 21.22.3.4
TxnA (Set Client App=TxnA)
-
ClassX
-
ClassY
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Simplifying Problem Determination Scenario
Application Developer
Available for each db access
SQL text generated
Access path
Cost estimates
Estimated response time
Elapsed & CPU time
Data transfer (getpages)
Tuning advice
Database Administrator
Available for each SQL
Application name
Java class name
Java method name
Java object name
Source code line number
Source code context
J
-
LinQ transaction name
Last compile timestamp
Java
Profiling
pureQuery
DRDA
Extentions
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Using pureQuery to Foster Collaboration and Produce Enterprise
-
ready Apps
Application Server
Catalog data for SQL
Application
Meta data
DB2 or IDS
Prod
A
4
A1
A1
A6
A6
A2
A2
A3
A
3
A4
A4
A5
A5
A1
A4
A5
Performance
Data
Warehouse
Application
Developer
Database
Administrator
A1
A6
A2
A3
A4
A
5
Use pureQuery app metadata
as a way to communicate in terms
familiar to both DBA and developer
Application
Meta data
DB2 or IDS
Dev System
A1
A6
A2
A
3
A4
A5
A1
A4
A5
IBM Information Management
© 2009 IBM Corporation
20
Data Studio Developer
--
pureQuery Outline
Speed up problem isolation for developers
–
even when using frameworks
Capture application
-
SQL
-
data object
correlation (with or without the source
code)
Trace SQL statements to using code
for faster problem isolation
Enhance impact analysis identifying
application code impacted due to
database changes
Answer “Where used” questions like
“Where is this column used within the
application?”
Use with modern Java frameworks
e.g. Hibernate, Spring, iBatis,
OpenJPA
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Java Persistence Technologies with pureQuery
JPA API
pureQuery API
JPA Runtime
pureQuery Runtime
JDBC w/pureQuery
IBM
Database
pureQuery Metadata,
Manageability
Spring
iBatis
JDBC
SQLJ
High Speed API
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© 2009 IBM Corporation
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Client Optimization
Improve Java data access performance for DB2
–
without changing a line of code
Captures SQL for Java applications
Custom
-
developed, framework
-
based, or packaged applications
Bind the SQL for static execution without changing a line of code
New bind tooling included
Delivers static SQL execution value to existing DB
2
applications
Making response time predictable and stable by locking in the SQL access path pre
-
execution, rather than re
-
computing at access time
Limiting user access to tables by granting execute privileges on the query packages
rather than access privileges on the table
Aiding forecasting accuracy and capacity planning by capturing additional workload
information based on package statistics
Drive down CPU cycles to increase overall capability
Choose between dynamic or static execution at deployment time,
rather than development time
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Data Studio pureQuery Runtime for z/OS
In
-
house testing shows double
-
digit reduction in CPU costs over dynamic
JDBC
IRWW
–
an OLTP workload,
Type 4 driver
Cache hit ratio between 70 and 85%
15%
-
25% reduction on CPU per txn
over dynamic JDBC
274
360
420
446
485
524
0
100
200
300
400
500
Normalized Throughput (ITR)
EJB 2
JPA
JDBC
pQ Method Dynamic
Client Optimizn Static
pQ Method Static
Normalized Throughput by API for JDBC Type 4 Driver
-35%
-14%
6%
15%
25%
-50%
% increase/reduction in CPU per
transn compared to JDBC
EJB 2
JPA
pQ Method Dynamic
Client Opt. Static
pQ Method Static
% increase/reduction in CPU per transaction compared
to JDBC using Type 4 driver
IBM Information Management
© 2009 IBM Corporation
24
Have You Heard of SQL Injection?
IBM Information Management
© 2009 IBM Corporation
25
Toughest issue for Web applications
–
Problem diagnosis
and resolution
Web
Browser
Users
Web
Server
Application
Server
DB2
Server
Business Logic
Data Access Logic
Persistence Layer
DB
2
Java Driver
JDBC
Package
EJB Query Language
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©
2009
IBM Corporation
26
Customer Job Roles
–
A Barrier to a “Holistic View”
Application
Server
DB
Server
Data Access Logic
Persistence Layer
DB Java Driver
JDBC
Package
EJB Query Language
WebSphere
Connection
Pool
Business
Logic
1
3
5
4
2
Application
Developer
System
Programmer
DBA
Network
Admin
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27
How do we plan to help?
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Scenario
It seems that the first application server has a
problem.
Double
-
click to drill
-
down.
In this situation, all applications are equally
affected, and the problem seems not to be in
the data server.
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29
Scenario
-
continued
Double
-
click to drill
-
down and display detail
information.
Most of the time is spent for „WAS connection
pool wait“ time.
IBM Information Management
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30
Scenario
–
continued
5 second wait time indicates that the maximum
number of allowed connections is not
sufficient…
… which becomes also evident when
comparing the parameters and
metrics of this client with other clients.
© 2009 IBM Corporation
IBM Information Management
Future enhancements to
Data Studio and pureQuery
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© 2009 IBM Corporation
32
DB2 Performance Expert futures
--
Associate SQL with Java Source
Heat Chart
Dashboard
Alerts
SLAs
In
-
flight analysis
䑡D慢慳a:⁁捣ount楮i
St慴敭敮e⁴數t
schema
E2E elapsed
occurrences
sort time
phys. I/O
SELECT TIME FROM UNIVERSE
SAP3
132.13
1323
123.32
1.303
SELECT SALARY FROM PAYMENT …
SYSIBM
323.4
221
11.3
32.1
DELETE FROM ACCOUNT WHERE AID
= 3…
PROC
23.3
435
32322.3
32.1
TOP 3 currently running SQL Statements
TOP by
DS elapsed
DS CPU time
Physical I/O
Sort time
-
+
-
+
-
+
SELECT TIME FROM UNIVERSE
Stmt text
Analyze
Application
DS user ID
KARN
Client IP addr / hostname
TPKARN.de.ibm.com
Client user ID
KARN
Client workstation name
TPKARN
Client application name
Jawaw.exe
Client accounting
N/A
application name
Online banking
application contact
hkarn@de.bm.com
package
West.OLBank
class
Account
method
Transfer()
source line
314
Time distribution
Force application
Stop SQL
sorting
Resource usage
Query cost estimates
18.456
Buffer Pools
Data
–
hit ratio (%)
43.4%
Data
–
physical reads / min
4323
Index
–
hit ratio (%)
54.2%
Index
–
physical reads / min
3214
Statement information
X
DS Proc
USER CPU
SYSTEM CPU
Unacc wait
DS sorting
Statement elapsed time
Current
132.13 sec
last day
239.40 sec
last week
15.60 sec
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2009
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33
OpenJPA and Hibernate
--
SQL Query Generation
JPA Query
Select emp_obj(),
dept_obj()
SQL
Select * from EMP
WHERE …
Select * from DEPT
WHERE …
JPA
query
transform
•
Hibernate and OpenJPA often rewrite queries
•
No database statistics are used
–
entirely heuristic!!!
•
Can often result in poorly performing queries
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© 2009 IBM Corporation
34
pureQuery
--
More Visibility, Productivity, and
Control of Application SQL
Capture SQL
Share, review, and optimize SQL
Revise/optimize SQL and validate equivalency without
changing the application
Bind for static execution to lock in service level or run
dynamically
Restrict SQL to eliminate SQL injection
Capture
Review
Optimize
Revise
Restrict
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35
Visualize execution
metrics
Execute, tune,
share, trace,
explore SQL
Replace SQL
without changing
the application
Position in
Database Explorer
Visualize application
SQL
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36
OpenJPA, Hibernate, iBatis
--
Batch Queries
JPA Query
new dept_obj …
new emp_obj …
new dept_obj …
new emp_obj …
SQL
INSERT INTO DEPT …
INSERT INTO EMP …
INSERT INTO DEPT …
INSERT INTO EMP …
JPA
query
rewrite
•
OpenJPA,
Hibernate, and iBatis “batch” queries to reduce network traffic
•
Batches must contain executions of a single prepared statement
•
Referential integrity constraints can change batch size:
•
2
network trips without RI (one for EMP, one for DEPT)
•
4
network trips if RI disables batching
•
pureQuery can convert the above example to a single network trip,
regardless of whether RI is used or not…
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Support for Oracle in
Data Studio Developer
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38
Oracle Object Management support in Data Studio
•
Create/Alter/Drop for all
objects
•
Tables, Synonyms,
Sequences
•
Functions
•
Views/materialized views
Physical objects
Performance objects
Integrity objects
Procedures and Functions
User Defined Types
Events
Space
•
Create/Alter/Drop
•
Tablespace, Extents,
Free Lists, logging
•
LOB Attributes
•
Buffer pools
•
Create/Alter/Drop
•
Partitions (Range, Hash,
List)
•
Indexes
•
Create/Alter/Drop
•
Constraints (primary,
unique, check, foreign)
•
Triggers
•
Before/After/Foreach
types
•
Trigger events
•
Create/Alter/Drop
•
Table Types
•
Object Types
•
Array Types
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39
Design Lifecycle
Logical Modeling
Capture business requirements
Represent an organization’s Data
Abstract complex heterogeneous environments
Often associated with a Domain Model
•
Dedicated vocabulary
Physical Modeling
Platform specific implementation
•
Tables, Constraints, Data Types
•
Disk and Security requirements
•
Caching and Fast access strategies
Leverage and Validate against platform key features and constraints
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Advanced heterogeneous support
IBM
ORACLE
Physical Data Modeling
Logical Data Modeling
Oracle
Support
•
Visualize
•
Design Privileges
•
Storage and Data Partition
•
Advanced Code Generation
•
Analyze Impact
•
Validate
IBM Data Studio
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41
Visualize Oracle Data Sources
High fidelity display of the Catalog Information
Load on Demand technology
Instantaneous connection
Fast retrievals
Enable Physical Data Model transformation
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42
Managing Oracle Tables
Tree
-
Based
Representation
Object
Properties
Editor
SQL and
Results of the
Execution
Context
-
Sensitive
Actions
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43
Oracle Privileges Support
Physical Model enables Design capability
Grant appropriate privileges and roles to users
More detailed display allows finer
-
grained control
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44
Oracle Storage
Storage properties display
Ability to design Table Spaces
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Data Partition
Table and Materialized View support
Range partition
List partition
Hash partition
Composite partition
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PL/SQL Development
Integrated Query Editor support
Content Assist
Parser support (2009) with Error reporting
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47
PL/SQL Deployment
Execution Configuration
Separation of concerns
•
Better decouple configuration from definition and implementation
Deployment and Debugging
Runtime Target initialization
Authorization configuration
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Optimization Expert
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Understanding Query with Query Annotation
Original and
transformed
Query
Formatted, reorganized query text
Annotations (catalog stats, cost estimation)
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VISUAL PLAN HINT
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Provide hints for AccessType
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ACCESS PLAN GRAPH (APG)
The
Access Plan Graph
screen displays the access path on the right, and relevant statistics on the left.
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53
Query Advisor
Predicate that should be
considered for re
-
write to get
better performance
Re
-
write
advice and
details
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54
Access Path Advisor
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STATISTICS ADVISOR
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56
Index Advisor
Index
Recommendations
DDL to create
the new index
statement
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57
Common Connection Repository
Enhancing the value propositions on
Team support
Centralized connection properties for sharing between
DBA and Developers
Improve usability and up
-
and
-
running scenarios
Give controls to DBAs on connection properties
settings
Eliminates the need to configure each database server
on each client desktop
“push down” of client properties to allow DBAs to
control and override application behaviors
Key Features
Integrated solution to Eclipse Data Source Explorer
Integration with upcoming Web DBA tooling
Create or connect to Connection Repository
Connect to database using existing definitions
Create new definition
Logical grouping of connection definitions
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58
Data & Object Movement
•
Value Proposition
–
•
Provide for the copying of database
objects and data between
homogeneous
and
heterogeneous
databases within Data Studio
•
Key Features
•
Copy objects at various levels
–
complete databases to a fixed number
of rows from a single table
•
Action performed in Data Source
Explorer
–
Copy/Paste and Drag/Drop
•
Can automatically copy rows from
related tables using:
•
RI in database
•
Data Architect model
•
Optim application models
•
Data Relationship Analyzer
•
Can optionally annonymize the rows
using Optim Test Database Manager
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pureQuery Runtime improvements
“client optimization” for non
-
Java SQL applications (convert
dynamic SQL to static)
.NET apps
CLI apps (including Ruby, PHP, etc.)
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Where to get IBM Data Studio ?
IBM Data Studio
www.ibm.com/software/data/studio
•
FAQs / Tutorials
•
Downloads
•
Forum
/ Blogs
•
Join the IBM Data Studio user community
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Contract with IBM Corp.
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