TopLink: Now and in the future, O-R Mapping Product of Choice

Doug Clarke Principal Product Manager, Oracle9iAS TopLink

Oracle Corporation

Speaker’s Qualifications

Doug has a decade of experience in OO Persistence

– Development, Consulting & Training

Product Manager for TopLink product

Underestimation

Managing persistence related issues is the most underestimated challenge in enterprise Java today – in terms of complexity, effort and maintenance

Agenda Ways to access RDB from J2EE Impedance Mismatch TopLink Overview

– TopLink in Development– Runtime Architecture– O-R Mapping Flexibility– Queries– Transactions– Caching– Locking– Performance Features

TopLink Roadmap

J2EE Access of Relational Data Direct JDBC

– Direct SQL calls– Use rows and result sets directly

Persistence Layer– Accessed as objects or components– Transparent that the data is stored in RDB– Persistence layer in middle tier handles object-

relational mapping and infrastructure– Required if doing business logic in the middle

tier!– Focus of this Session

Direct JDBC

JDBC is NOT a persistence framework– JDBC is a database

connection utility – Ok for “Window on data”

style application– Ok when business logic is

entrenched on database– J2EE becomes a

presentation layer…

SQLrows

JDBC

Object Persistence Layer

Abstracts persistence details from the application layer

SQLrows

Objects

Persistence Layer

Objectsobject-level

querying and creationresults are objects

results arereturned as

raw data

API uses SQLor databasespecific calls

object creation and updates through object-level API

J2EE & J2EE & Web Web

ServicesServices

JDBC

Problem

Building Java applications with relational databases is a VERY challenging and labor intensive problem to solve

– Fundamentally different technology– Different skill sets– Different staff/ownership– Different modeling and design principles

Differences must be resolved to fulfill business requirements

?

Impedance MismatchFactor J2EE Relational Databases

Logical View Of Data

Objects, methods, inheritance

Tables, SQL, stored procedures

Scale Hundreds of megabytes Gigabytes, terabytes

Relationships Memory references Foreign keys

Uniqueness Internal object id Primary keys

Key Skills Java development, object modeling

SQL, Stored Procedures, data management

Tools IDE, Source code management, Object Modeler, etc

Schema designer, query manager, database configuration, etc

Object Level Options

Depends on what component architecture is used:

– Entity Beans BMP – Bean Managed Persistence– Entity Beans CMP – Container Managed

Persistence– POJO – “Plain Ol’ Java Objects” via Persistence

Layer May be “home-grown” following “DAO” Data Access

Object patterns May use JDO – “Java Data Objects” May use off the shelf products

J2EE Architectures

J2EE Architecture Options– Servlets– JSP– Session Beans– Message Driven Beans– Web Services

Bottom Line – Java application needs to access relational data somehow…

Oracle9iAS TopLink Solution

Oracle9iAS TopLink provides a proven, powerful “out of the box” solution to address the diversity between Java and Databases

Oracle9Oracle9iiAS AS TopLinkTopLink

TopLink in Development

IMPO

RT

GEN

ERA

TE

IMP

OR

T

(.class)

GE

NE

RA

TE

(.java)

Java IDE

TopLink

Meta-Data(XML)

Java classesRelational database(schema)

TopLinkMapping

Workbench

TopLink Runtime ArchitectureData Source

TopLinkApplication

Application Server

Session

Data A

ccess

Mappings

JDB

C

J2EE Container

JTACMP/BMP

Cache

Query

TXEntitiesJava

Objects

EJB Entity Beans

JSP,Servlet,Struts,

etc.

AppLogic

Basic J2EE Persistence Checklist

O-R Mappings Runtime Components

– O-R Mapping Flexibility– Queries– Transactions– Caching– Locking– Performance Features

Data and Object Models

Rich, flexible mapping capabilities provide data and object models a degree of independence

Otherwise, business object model will force changes to the data schema or vice-versa

Often, J2EE component models are nothing more than mirror images of data model or vice versa – NOT desirable

Mapping Tools

The underlying mapping flexibility is very important

Simple Object Model

Customer

id: intname: StringcreditRating: int

Address

id: intcity: Stringzip: String

1:1 Relationship

Typical 1-1 Relationship Schema

CUST

ID NAME A_IDC_RATINGADDR

ID CITY ZIP

Other possible Schemas…

CUST

ID NAME C_RATE C_ID

ADDR

ID CITY ZIP

CUST

ID NAME C_RATING C_ID

ADDR

ID CITY ZIP

A_ID

CUST_ADDR

C_ID

CUST

ID NAME CITY ZIPC_RATING

Even More Schemas…CUST

ID NAME A_ID

ADDR

ID CITY ZIP

CUST_CREDIT

ID C_RATING

CUST

ID NAME

ADDR

ID CITY ZIP

CUST_CREDIT

ID C_RATING A_ID

CUST

ID NAME

ADDR

ID CITY ZIP

CUST_CREDIT

ID C_RATING A_IDCC_ID

CUST

ID NAME

CUST_CREDIT

ID C_RATING

ADDR

ID CITY ZIP C_ID

CUST

ID NAME

CUST_CREDIT

ID C_RATING

ADDR

ID CITY ZIP C_ID

Benefits of Good O-R Mapping

Flexible - Just showed nine valid ways a 1-1 relationship could be represented in a database (Most persistence solutions will only support one)

Without good support, designs will be forced Comprehensive support for custom types, inheritance, Simple mapping for identity management Custom type support Non-intrusive/transparent to the business model

developer

MORE than just Mapping

Querying Transactions Caching Concurrency Performance

Queries Java developers are not usually SQL experts

– Maintenance and portability become a concern when schema details hard-coded in application

Allow Java based queries that are translated to SQL and leverage database options

employee.get(“manager”).get(“address”) = someAddress

SELECT * FROM EMP t1, EMP t2, ADDR t3 WHERE t1.MGR_ID = t2.EMP_ID AND t2.ADDR_ID = t3.ADDR_ID AND t3.ADDR_ID = <someAddress.id>

Generates…

Query Features

Ability to trace, profile, and tune SQL Ad hoc SQL where necessary Must be able to leverage database abilities

– Outer joins– Nested queries– Stored Procedures– Database Specific Optimizations (Oracle Hints)

Choice of query language: SQL, Stored procedures, EJBQL, or TopLink’s Object expressions

In-Memory querying and transaction conformity

Transaction Management

J2EE apps typically support many clients sharing small number of db connections

Ideally would like to minimize length of transaction on database

Tim

e

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Support for Referential Integrity

Java developers manipulate object model in a manner logical to the business domain

May result in ordering of INSERT, UPDATE and DELETE statements that violate database constraints

Persistence layer should automatically manage this and allow options for Java developer to influence order of statements

Object Cache

Cache your business objects Improved performance by reducing reads Configurable Support for clustered caches Concurrency support for multi-client reading

and writing

Caching in the real world

Any application that caches data, now has to deal with stale data

When and how to refresh? Will constant refreshing reduce performance? Problem is compounded in a clustered environment App server may want be notified of database

changes

TopLink supports all of these cases

Caching

OO QuerySQL Query (if desired)

Results(s)

Does PK for row exist in cache?

YES – Get from Cache

NO – Build bean/object from results

Return object results

Concurrency: Locking

J2EE Developers want to think of locking at the object level

Databases may need to manage locking across many applications

Persistence layer or application server must be able to respect and participate in locks at database level

Optimistic Locking

DBA may wish to use version, timestamp and/or last update field to represent optimistic lock

– Java developer may not want this in their business model

– Persistence layer must be able to abstract this

Must be able to support using any fields including business domain

Pessimistic Locking Requires careful attention as a JDBC connection is

required for duration of pessimistic lock Should support SELECT FOR UPDATE [NOWAIT]

semantics Consider Application level pessimistic locking

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e

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Pess Lock

Performance: Lazy Reads

J2EE Applications work on the scale of a few hundreds of megabytes

Relational databases routinely manage gigabytes and terabytes of data

Persistence layer must be able to transparently fetch data “just in time”

Just in Time Reading – Faulting Process

Customer

Orders

Proxy

Accessing relationship for first time

Get related object based on FK

SQL if not cached

Check Cache

Plug result into Proxy

OrdersOrders

Object Traversals

Even with lazy reads, object traversal is not always ideal

– To find a phone number for the manufacturer of a product that a particular customer bought, may do several queries: Get customer in question Get orders for customer Get parts for order Get manufacturer for part Get address for manufacturer

– Very natural object traversal results in 5 queries to get data that can be done in 1

N+1 Reads Problem

Many persistence layers and application servers have an N+1 reads problem

Causes N subsequent queries to fetch related data when a collection is queried for

A side effect of the impedance mismatch and poor mapping and querying support in persistence layers

N+1 Reads Problem

Pool of Created Objects or Beans

PersistenceLayer or EJB

Container

findByCity()

1findByCity()

2

For each CustomerFetch their Address

Address

46

4

n

5 5

3 Returns collection

n

If Address had related objects, they too may be

fetched 2n+1 Reads!

Container returns results

C C C C

N+1 Reads

Must have solution to minimize queries Need flexibility to reduce to 1 query, 1+1

query or N+1 query where appropriate– 1 Query when displaying list of customers and

addresses – known as a “Join Read”– 1+1 Query when displaying list of customers and

user may click button to see addresses – known as a “Batch Read”

– N+1 Query when displaying list of customers but only want to see address for selected customer

Performance and Tuning Options Minimal Writes, Updates Batch Reading, Writing SQL ordering Transformation support Existence checks Stored procedures Read Lock Support Statement Caching Scrolling cursors Partial Attribute Queries “Just in Time” reading

AND MUCH MORE!

Automatic change detection Caching policies and sizes Parameterized SQL Pre-allocation of sequence numbers Cache synchronization support Optimistic, Pessimistic locking Joining object retrieval optimization In memory querying Dynamic queries Query optimization

Why is TopLink the O-R leader?

Productive development tools Extremely flexible O-R mappings Choice and performance in querying Scalable cache and transaction framework Powerful performance tuning options Strong J2EE support and integrations Complete architecture and database flexibility

Award winning product based on years of real world application development and backed by world’s leading enterprise software company.

What’s Next: TopLink Roadmap

Maintain leadership in O-R persistence

Expand data source support:– EIS through J2EE Connector Architecture– Object-to-XML

Maintain current with standards and provide functionality demanded by our customers

TopLink & XML

XML documents can be represented at different levels of abstractions in J2EE applications:

– Parsed document (DOM, SAX …) - parser– Unmanaged Java objects from non-transactional

data source – data converter– Managed Java objects from a transactional data

source – persistence manager

3 Levels of XML Representation

XML Parser

O-X Data Converter

XMLDocument

UnmanagedObject

Persistence Manager

XDB EIS

JDBC J2C

DOM ManagedObject/EJB

File

WebService

BPM JMS

Impact on J2EE Integration Solutions

This technology will be critical for many J2EE applications accessing EIS systems via JCA resource adapters

– XML based adapters will outgrow proprietary data formats

– “80% of the worldwide data resides on mainframes.” Gartner

Without it, developers will have to work with low level XML documents and manually code persistence manager functionality

Benefits of XML/JCA Support Easier to adopt and integrate web services, disparate

data and legacy applications. Abstracting data details provides flexibility and

portability. Increased developer productivity as they focus on

building applications not infrastructure. Single abstraction layer to access heterogeneous data

sources. Optimized performance and scalability. Leverage existing architecture and developer skills

base

Summary

TopLink is clearly leader in O-R mapping Many exciting directions for the future

If You Only Remember One Thing…

When choosing a persistence layer, Pick one that maximizes your flexibility across all the issues outlined here today!

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