October 25–29, 2009 • Mandalay Bay • Las Vegas, Nevada1

Revolutionizing the Data Abstraction Layer with IBM Optim pureQuery

Dr. Vladimir Bacvanski, Vice President, InferData, vladimir@inferdata.com

Daniel Galvin, Consultant, Galvin Consulting, dang@galvinconsulting.comSession Number 2171

What is this revolution about?

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NO SLOW APPS!

NO BAD SQL!

GET CONTROL BACK !

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Show of Hands: What Data Access Technology Have You Used?

What’s most important to you?– Productivity

– Performance

– Security

– Portability

JDBC

iBatis

SQLJ

HibernateEJB Entity

Beans

JPA

mashuphttp Stored

Procedures

JSON

QoS goalsJSP

XML

JDBC

Runstats

Response Time!

SQL

Spring

REORG

Partition strategy

ApplicationDeveloper

SQLJ

JDBC

JPA

iBatis, . . .

SpringWhy does this query take so long?

I can’t believe I got called out last week. I wish I could see how these queries will run in production.

Writing Java code is so easy with this eclipse environment.I wish it was that easy to get the SQL right.

This ORM doesn’t allow me to leverage all my database’s SQL.

Static SQL? Sounds like another delay to getting my program deployed

Sometimes I need POJOs, sometime JSON, sometimes XML, what should I use?

Java Data Access – Two Views of the World

Database Developer& Administrator

Another runaway query! Where are these coming from? JDBC? Hmmm…

Inconsistent response time? How long will it take me to find the offending application sending bad SQL this time?

These ad-hoc queries are dangerous. We need a library of tested SQL interfaces.

Can I examine the SQL “before” the application is deployed?

Another GRANT request? This security administration is out of control.

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Application-Centric– Top-Down– Start with Object Domain

Model– ORM Mapping– Well supported in dynamic

languages and frameworks

Hybrid– Meet in the middle– Can be challenging w/o

comprising

Data-Centric– Bottom-UP– Start with Relational Data

Model– Not well supported in dynamic

languages and frameworks

Persistence Layer

TopDown

BottomUp

Meet in theMiddle

Data Mapping Approaches

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EJB, JPA, and Hibernate vs. The Database

DBA and SQL developer chasm Where is the SQL coming from? What is it? Where is it? How do we tune it? How de we manage it?

Performance Concerns: Some App Server vendors claim

(unsurprisingly) that Managed objects performs fine.

There are many user claims of bad Managed object performance is bad on the web.

As always, the truth is in the middle. And will depend on your app server,

application, database, etc ..

“Our top story: Large Customer moves from COBOL to Java to become more agile. In other news, DBA develop amnesia.”

Introducing pureQuery

pureQuery Components:Simple and intuitive API– Enables SQL access to databases or in-memory Java objects– Facilitates best practices Optim Development Studio (integrates with RAD/RSA)– Integrated development environment with Java and SQL

support – Improve problem isolation and impact analysisOptim pureQuery Runtime– Flexible static SQL deployment for DB2

A high-performance, data access platform to simplify developing, managing, securing, and optimizing data

access.

pureQuery Balances Productivity and Control

Managed objects Object-relational mapping

Spring templates

Full SQL control

Code all your SQL

Use SQL templates, inline only

Complex OR mapping and persistence management, but loss of controls

Adds container management option

JDBC / SQLJ

iBATIS

Hibernate

OpenJPA (EJB3)

Add basic OR mapping and annotated-method stylepureQuery

Code Development Productivity• Code Generation, Content Assist• Database aware, Java SQL Editor

Design Phase pureQuery close-up

SQL Performance Metrics• Find and sort query elapsed time

from Java

Java to SQL Integration• Categorize by Java, SQL, Database ,

Packages, track back to line of code

SQL Injection Prevention• Lock down SQL for Dynamic

Static SQL• Lock in Access plans, Improve Security,

Consistent Performance

Problem Determination• Monitor WebSphere Connection

Pool, JDBC Driver, Network• Track back to SQL and line of

code in the application

SQL Replacement• Replace Query w/o changing source

Existing JDBC to Static• Reroute Dynamic Queries to Static

Jump Start Application Design• Generate SQL and Code from Database Objects • Setup basic DAO Pattern

Oracle Support• Replace Query w/o changing

source

Code Example: JDBC Table Column TypeEMP NAME CHAR(64)

EMP ADDRESS CHAR(128)

EMP PHONE_NUM CHAR(10)

class Employee { String name; String homeAddress; String homePhone; …}

java.sql.PreparedStatement ps = con.prepareStatement( "SELECT NAME, ADDRESS, PHONE_NUM FROM EMP WHERE NAME=?");ps.setString(1, name);java.sql.ResultSet rs= ps.executeQuery();names.next();Employee myEmp = new Employee();myEmp.setName(rs.getString(1));myEmp.setHomeAddress(rs.getString(2));myEmp.setHomePhone(rs.getString(3));names.close();

Code Example: pureQuery

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Employee myEmp = db.queryFirst( "SELECT NAME, ADDRESS, PHONE_NUM FROM EMP WHERE NAME=?", Employee.class, name);

Even simpler, if we have a method getEmployee with a Java annotation or XML file with SQL for the query:

Employee myEmp = getEmployee(name);

WHY SHOULD BE THE DATA SPECIALISTS BE INTERESTED IN PUREQUERY?

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Motivations of the Data Specialists

SQL Performance Tuning Ease of Tuning Autonomy of Developers Predictability of an Optimized Data Access Path

Reduction of Costs to satisfy SQL statements Optimized Access Paths Reduction of CPU intensive components of SQL Execution Utilization of Specialty Processors

Capacity Planning Hardware Utilization

Problem Determination capabilities

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pureQuery Capabilities

Static SQL for Runtime with Dynamic SQL Execution in Development

pureQuery can utilize SELECT INTO from a Java application With Client Optimization, Static SQL from existing JDBC with

no changes to the Application Homogeneous and Heterogeneous Batching of Statements Statically bound packages are easy to EXPLAIN and monitor

for changes in access path pureQuery coupled with IBM Optim Performance Monitoring

provides E2E Performance Monitoring and Problem Determination

Impact analysis is greatly improved by the static packages and the ability to tie each statement to a method in the application code

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STATIC VS. DYNAMIC SQL EXECUTION

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Static vs. Dynamic SQL

Check Plan/Package Authorization and look for

stmt in Cache

Parse SQL Statement

Check Table/View authorization

Compute Access Path

Execute Statement

Validate SQL against DB2 Catalog

Dynamic SQL – Full Prepare

(~ 300,000 lines of code)

Check Plan/Package Authorization and look for

stmt in Cache

Execute Statement

Dynamic SQL – Short Prepare (~ 15,000 lines

of code)

Create Skeleton in EDM Pool

Copy skeleton from cache to local DB2 thread storage

Check Plan/Package Authorization

Execute Statement

Load package into EDM if not previously loaded

Static SQL

Cost of Prepare

CPU cost of Short Prepare on DB2 9 for z/OS – between 400µs and 1ms

CPU cost of Full Prepare on DB2 9 for z/OS – approximately 30 to 50ms. Cost could be much higher and generally increase with complexity.

Trial ResultsEstimated CPU Savings

(In DB2 CPU)

0

1

2

3

4

5

6

7

8

9

10

Avg CPUTime (ms)

JDBC

pureQuery

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How well does it work? – Java applications

In-house testing shows significant performance improvements

IRWW – an OLTP workload, Type 4 driverCache hit ratio between 70 and 85%23 % improvement in throughput using pureQuery over dynamic JDBC15% - 25% reduction on CPU per transaction over dynamic JDBC

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360420 446

485524

0

100

200

300

400

500

No

rmalized

Th

rou

gh

pu

t (I

TR

)

Normalized Throughput by API for JDBC Type 4 Driver

-35%

-14%

6%15%

25%

-50%

% in

crea

se/r

edu

ctio

n in

CP

U p

er

tran

sn c

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DB

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% increase/reduction in CPU per transaction compared to JDBC using Type 4 driver

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How well does it work? - .Net applications

Throughput during static execution increased by 159% over dynamic SQL execution assuming a 79% statement cache hit ratio

*Any performance data contained in this document were determined in various controlled laboratory environments and are for reference purposes only. Customers should not adapt these performance numbers to their own environments as system performance standards. The results that may be obtained in other operating environments may vary significantly. Users of this document should verify the applicable data for their specific environment.

IRWW – OLTP application

Application accesses DB2 for z/OS

BATCHING SQL STATEMENTS

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Homogeneous & Heterogeneous Batch

Homogeneous Batch – all instances in the batch are the same statement and require only 1 line turn

Heterogeneous Batch – allows different SQL statements to be included in batch.

Both Utilize Multi-Row Insert

Heterogeneous Batches may contain 0 to many Homogeneous Batches

Heterogeneous Batch Examplepublic int[][] insertAgentAndPolicies(AgentTO agentTO, PolicyTO[] policyTO) {

Data data = DataFactory.getData(ds, pdqProps);

try {

AgentData agentData = DataFactory.getData(AgentData.class,

data);

PolicyData policyData = DataFactory.getData(PolicyData.class,

data); data.startBatch(HeterogeneousBatchKind.heterogeneousModify__);

agentData.insertAgent(agentTO);

policyData.insertPolicies(policyTO);

return data.endBatch();

} finally {

data.close();

}

}

Client Optimization

Allows you to bind static SQL packages from existing JDBC code

Avoids the cost of rewriting the application to code to the pureQuery API

Allows Heterogeneous batch with minor changes to the code

None of the productivity advantages are realized. Code is still maintained in JDBC.

End-to-End monitoring lacks some introspective capability into the coding

Creation of the static packages requires that you run the code.

Some overhead at runtime related to resolution of statements to static packages

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DB2 Data Servers

pureQuery client optimization enables static execution for JDBC applications (custom-developed, framework-based, or packaged) Existing JDBC Application

JDBC Driver w/ pureQuery

Dynamic SQL execution Static SQL execution

Optimize Existing JDBC Applications

Captured SQL- related

metadata

Capture Configure Bind Execute

"The ability to use static SQL with pureQuery is huge. Recently, I worked with a client who could reduce CPU usage by 7 percent thanks to this one feature."

— David Beulke, Pragmatic Solutions Inc.

Improve performance for DB2 – without changing a line of code

Why should DBAs care ?

DBAs have little to no visibility of application SQL before deployment, no opportunity for review and optimization

Problem isolation takes days with contemporary environments such as Java, PHP, .NET, etc due to inability to trace SQL to Java application and source code

Constantly increasing Java application workload taxes existing systems – need to fit more work into existing systems

SQL injection represents an increasing risk to data security

Why should Developers care ?

Get data access right the first time !

Get it done faster - Improved productivity

Single environment that spans Java application and database development

Improved problem isolation and resolution

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Control performance– Decide at deployment time how the SQL is executed– Understand and lock down the access plan for SQL– Replace suboptimal SQL without changing the application

Control security– Prevent SQL injection– Prevent execution of unauthorized SQL– Better manage database security

See inside applications that are driving your database– Understand where SQL comes from– Understand when frameworks and ORM’s are getting in the way

Simplify problem determination and troubleshooting– Correlate problem SQL with applications, ORM’s and frameworks

Optim pureQuery Runtime

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How do I start with pureQuery?

Existing applications– Optimize existing JDBC (and .NET!) applications

– No code changes needed

– Have to go through the client optimization process to get to static SQL

New applications– Use the pureQuery API

– Development codes using one API regardless of whether it is deployed dynamically or statically

– DBA deploys statically

– No need to go through client optimization process

Other – JPA, iBatis, Hibernate

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pureQuery Facilitates Best Practices

Supports both inline SQL and Java annotations (method) Intuitive interfaces for common data retrieval and manipulation scenarios hides JDBC complexity

– Query First– Homogeneous Batch

Reduce network trips to the database – Query Over Java Collections– Heterogeneous Batch

Use custom result handlers to map results to POJO’s, XML, JSON, …

Write high performance Java data access applications, Part 3: Data Studio pureQuery API best practices

-- Vitor Rodrigueshttp://www.ibm.com/developerworks/db2/library/techarticle/dm-808rodrigues/?S_TACT=105AGX01&S_CMP=LP

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A Typical Application Architecture with pureQuery

Sometimes additional layers are required– Workflow

– Data federation

– Workspace

Presentation Layer

Business Service Layer

Data Access Layer

pureQuery

Database

Using the pure-query API to access the

database.Provides a technology neutral API to the data used by the business

services

Never use the pureQuery API directly.

Gets data from the Data Access Layer

Implements the U/I or network protocols using

the business services

pureQuery makes this layer easy, fast, consistent and

traceable

RAD or RSA / Optim Development Studio Data Centric Development Scenario

Presentation

•Dojo, JSF, …

Application

•Business Logic

Objects

•Access to data

Tables

•Data

Write in JavaUsing RAD+WAS FP for Web 2.0

Write in Java with pureQueryUsing Optim Dev. Studio in RAD

Access generated Java data objects from code developed in RADWAS Feature

Pack for Web 2.0

Demo

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Demo!

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Conclusion: pureQuery Revolutionary Advantages

Excellent performance– Static and dynamic SQL is captured during test and optimized

before deployment

– Enables lock-in of access path

Great productivity– Excellent tool support through Optim Development Studio

• Shell share with Rational tools

– Mapping from SQL to Java captured and traceable

– Facilitates collaboration between DBA’s and developers• Performance tuning, impact analysis

Better security– Limits SQL injection

– Controlled database access

Where to go Next? Resources and more…

Optim Development Studio – http://www.ibm.com/software/data/optim/development-studio/

IBM pureQuery– http://

www.ibm.com/software/data/optim/purequery-platform/faq.html

pureQuery Custom Training – InferData, IBM Business Partner http://www.inferdata.com

– Course: Developing Database Applications with Optim Development Studio and pureQuery

– http://www.inferdata.com/training/data/optim_purequery_training.html

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Web, Blogs

Integrated Data Management (Optim and Data Studio)– http://www.ibm.com/developerworks/spaces/optim

Vladimir’s Blog: On Building Software– http://www.OnBuildingSoftware.com

Twitter:– http://twitter.com/OnSoftware

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