Migrating JEE Apps to GigaSpaces Case Analysis – Spring PetClinic Uri Cohen, Product Manager Sept. 24 th , 2008

Agenda Background & Motivation What’s In an App Server Migration in Practice Messaging Data Access Web front end Architectural Considerations Live Demo

Background & Motivation

What’s In an App Server

Migration in Practice

Messaging

Data Access

Web front end

Architectural Considerations

Live Demo

Background GigaSpaces as an application server Previous projects to map the migration efforts and gaps

GigaSpaces as an application server

Previous projects to map the migration efforts and gaps

Motivation Feasibility study, learn about: User experience (migration complexity) Gaps between JEE & GigaSpaces Use that as input for next releases planning Share outcome with user community Provide a common basis for compatison “ Here’s how it should be done with GigaSpaces”

Feasibility study, learn about:

User experience (migration complexity)

Gaps between JEE & GigaSpaces

Use that as input for next releases planning

Share outcome with user community

Provide a common basis for compatison

“ Here’s how it should be done with GigaSpaces”

What’s In an App Server? Data access Messaging / event processing Remoting TX management Web

Data access

Messaging / event processing

Remoting

TX management

Web

Migration in Practice Messaging / event processing Replace MDBs with GigaSpaces event listeners Remoting Replace SLSBs with GigaSpaces SVF (Remoting/Executors) Data access Use GigaSpaces 2 nd cache for Hibernate Convert your DAOs to use GigaSpaces, use mirror to persist TX management Use Spring… Web Use GigaSpaces web processing unit Use GS HTTP session replication

Messaging / event processing

Replace MDBs with GigaSpaces event listeners

Remoting

Replace SLSBs with GigaSpaces SVF (Remoting/Executors)

Data access

Use GigaSpaces 2 nd cache for Hibernate

Convert your DAOs to use GigaSpaces, use mirror to persist

TX management

Use Spring…

Web

Use GigaSpaces web processing unit

Use GS HTTP session replication

Migration in Practice 1 No No Web (Http Session) 2-3 1 1 Effort (3 is biggest) Yes ORM 2 nd level cache: No DAO: Yes Data Access Yes No Remoting Yes Minor to none Messaging Config change Code change Converted Layer

ORM 2 nd level cache: No

DAO: Yes

Converting Your Messaging Layer Convert you MDBs to GigaSpaces event containers You can use IMessageConverter on the client side You can use annotations / XML Considerable performance boost Without affinity: up to 3 times faster With affinity: up to 6 times faster

Convert you MDBs to GigaSpaces event containers

You can use IMessageConverter on the client side

You can use annotations / XML

Considerable performance boost

Without affinity: up to 3 times faster

With affinity: up to 6 times faster

Converting Your Messaging Layer

Converting Your Messaging Layer

Converting Your Remoting Layer Usually implemented by SLSBs with JEE No or minor code changes needed You get: Location transparency Dynamic service discovery Synchronous or asynchronous invocation Cluster wide invocations (Map/Reduce) Data affinity Automatic failover

Usually implemented by SLSBs with JEE

No or minor code changes needed

You get:

Location transparency

Dynamic service discovery

Synchronous or asynchronous invocation

Cluster wide invocations (Map/Reduce)

Data affinity

Automatic failover

Service Interface Client: Server: Converting Your Remoting Layer

Service Interface

Client:

Server:

Converting Your Data Access Layer Currently this is not effortless 1 st step: Domain model Dealing with relationships Need to change domain model Add foreign key fields, update setter, O/R mappings (if you use mirror) No lazy loading Load on a per case basis, might mean you should change the DAO No object navigation and aggregations in queries Need to query the space multiple times and aggregate

Currently this is not effortless

1 st step: Domain model

Dealing with relationships

Need to change domain model

Add foreign key fields, update setter, O/R mappings (if you use mirror)

No lazy loading

Load on a per case basis, might mean you should change the DAO

No object navigation and aggregations in queries

Need to query the space multiple times and aggregate

Converting Your Data Access Layer 2 nd Step: Partitioning You should determine how objects will be partitioned May involve duplicating parent routing fields to nested objects 3 rd Step: Changing the DAO Naive approach: Convert all JDBC/Hibernate calls to space calls Better approach: Use Remoting/Executors, take advantage of data affinity and collocation

2 nd Step: Partitioning

You should determine how objects will be partitioned

May involve duplicating parent routing fields to nested objects

3 rd Step: Changing the DAO

Naive approach: Convert all JDBC/Hibernate calls to space calls

Better approach: Use Remoting/Executors, take advantage of data affinity and collocation

Converting Your Data Access Layer Other issues: Non String IDs: need to create cluster-wide ID generator No dirty checks: similar to lazy loading, need to persist on a case-by-case basis Semantics: When saving with Hibernate/JPA, generated ID is injected into the object Solve at the DAO level

Other issues:

Non String IDs: need to create cluster-wide ID generator

No dirty checks: similar to lazy loading, need to persist on a case-by-case basis

Semantics:

When saving with Hibernate/JPA, generated ID is injected into the object

Solve at the DAO level

Architectural Considerations Web app & space in the same PU Partitioned or replicated? Is it really collocation? No dynamic scaling Web app & space in separate PUs Separate scaling models – more flexible No collocation Local cache can help

Web app & space in the same PU

Partitioned or replicated?

Is it really collocation?

No dynamic scaling

Web app & space in separate PUs

Separate scaling models – more flexible

No collocation

Local cache can help

Let’s See It in Action

Future Roadmap (Suggestions) Object navigation in queries user.address.street=’Oxford’ Native aggregate functions max, min, avg, std, custom Relationships JPA support Embedded EJB container?

Object navigation in queries

user.address.street=’Oxford’

Native aggregate functions

max, min, avg, std, custom

Relationships

JPA support

Embedded EJB container?

Q&A