1. Data Grid Patterns
Brian Oliver | Global Solutions Architect | Oracle Corporation | JBFOne 2008

2. Agenda Introduction to Data Grids Introduction to Oracle Coherence
Introduction to Data Grid Patterns
The Command Pattern
The Functor Pattern
Vorstellung der Thematik Distributed Cache
Funktionsweise anhand von Coherence wird erklärt
Die Ideen bezüglich Distributed Cache werden vorgestellt:
Ikesa cache
Verwendung Grid anstatt AQ
Die Servicewolke
Demo
The Store and Forward Messaging Pattern

3. Agenda Introduction to Data Grids Introduction to Oracle Coherence
Introduction to Data Grid Patterns
The Command Pattern
The Functor Pattern
Vorstellung der Thematik Distributed Cache
Funktionsweise anhand von Coherence wird erklärt
Die Ideen bezüglich Distributed Cache werden vorgestellt:
Ikesa cache
Verwendung Grid anstatt AQ
Die Servicewolke
Demo
The Store and Forward Messaging Pattern

4. Introduction to Data Grids
A Data Grid is a data management system for application objects
Application objects are managed across multiple servers (typically stored in memory)
Essential for Applications that require
low response time
very high throughput
predictable scalability
continuous availability
information reliability

5. Introduction to Data Grids
Data management system
Is it a Container? Can it be Embedded?
Application objects
What languages? Not necessarily relational!
Query support?
Shared across multiple servers
Architecture?
How are the servers coordinated?
How are the servers organized?
Low response time
Seconds? Milliseconds? Microseconds?

6. Introduction to Data Grids
Very high throughput?
Transactions or Operations Per Second? MB per Second?
Predictable scalability
Accurately predict future resources based on current utilization
Continuous availability
During failure, recovery, scale-out, upgrades?
Information reliability
Consistency? Isolation? Durability? Persistence?

7. Agenda Introduction to Data Grids Introduction to Oracle Coherence
Introduction to Data Grid Patterns
The Command Pattern
The Functor Pattern
Vorstellung der Thematik Distributed Cache
Funktionsweise anhand von Coherence wird erklärt
Die Ideen bezüglich Distributed Cache werden vorgestellt:
Ikesa cache
Verwendung Grid anstatt AQ
Die Servicewolke
Demo
The Store and Forward Messaging Pattern

8. Introduction to Oracle Coherence
Peer-to-Peer Clustering
No Single Points of Failure
No Single Points of Bottleneck
No Masters / Slaves / Registries etc
All members have responsibility to;
Manage Cluster Health & Data
Perform Processing and Queries
Work as a “team” in parallel
Communication is point-to-point (not TCP/IP) and/or one-to-many
Scale to limit of the back-plane
Use with commodity infrastructure
Linearly Scalable By Design

9. Introduction to Oracle Coherence
Data is automatically partitioned and load-balanced across the Server Cluster
Data is synchronously replicated for continuous availability
Servers monitor the health of each other
When in doubt, servers work together to diagnose status
Healthy servers assume responsibility for failed server (in parallel)
Continuous Operation: No interruption to service or data loss due to a server failure

10. Introduction to Oracle Coherence
Dynamically scale-out during operation
Data automatically load-balanced to new servers in the cluster
No repartitioning required
No reconfiguration required
No interruption to service during scale-out
Scale capacity and processing on-the-fly

11. Introduction to Oracle Coherence
Software Development Library
Pure Java (data grid)
Pure .Net 1.1 and 2.0 (client)
Pure C++ (client)
No Third-Party Dependencies
No Open Source Dependencies
Proprietary Network Stack (Peer-To-Peer model)
Other Libraries Support…
Database and File System Integration
Top Link and Hibernate
Http Session Management

12. Agenda Introduction to Data Grids Introduction to Oracle Coherence
Introduction to Data Grid Patterns
The Command Pattern
The Functor Pattern
Vorstellung der Thematik Distributed Cache
Funktionsweise anhand von Coherence wird erklärt
Die Ideen bezüglich Distributed Cache werden vorgestellt:
Ikesa cache
Verwendung Grid anstatt AQ
Die Servicewolke
Demo
The Store and Forward Messaging Pattern

13. Introduction to Data Grid Patterns
Implementations of traditional patterns, but on a Data Grid!
Inter-process Architectural Patterns
The Command Pattern
The Functor Pattern
The Task Executor Pattern
Intra-process Architectural Patterns
Store and Forward Messaging
Push Replication
The Coherence Incubator
Example Implementations, Source Code, Documentation

14. Agenda Introduction to Data Grids Introduction to Oracle Coherence
Introduction to Data Grid Patterns
The Command Pattern
The Functor Pattern
Vorstellung der Thematik Distributed Cache
Funktionsweise anhand von Coherence wird erklärt
Die Ideen bezüglich Distributed Cache werden vorgestellt:
Ikesa cache
Verwendung Grid anstatt AQ
Die Servicewolke
Demo
The Store and Forward Messaging Pattern

15. The Command Pattern: Definition
An action to be performed zero or more times at some point in the future should be represented as an object called a Command
All necessary parameters required to perform the said action, should be encapsulated as attributes with in the said Command object
The Command object must provide a mechanism to perform the action (typically represented an execute method defined on the said Command object)

16. The Command Pattern: Extended Semantics (for Data Grids)
A Command may only be executed within the scope of a target object, called a Context
To execute a Command it must be submitted to a Context
Once submitted, Commands are executed asynchronously
Commands are executed one-at-a-time, in the order in which they are submitted
A Command may not return a value to the application that submitted the said Command (for this use the Functor Pattern)

17. Command Pattern Demonstration

18. The Command Pattern: How it works! Step 1: The Initial Environment

19. The Command Pattern: How it works! Step 2: Creating a Context

20. The Command Pattern: How it works! Step 3: Registering a Context

21. The Command Pattern: How it works
The Command Pattern: How it works! Step 4: Command Executor Established (automatic)

22. The Command Pattern: How it works! Step 5: Creating a Command

23. The Command Pattern: How it works! Step 6: Submitting a Command

24. The Command Pattern: How it works
The Command Pattern: How it works! Step 7: Submitted Commands are Queued (automatic)

25. The Command Pattern: How it works
The Command Pattern: How it works! Step 8: Submitted Commands are Executed (automatic)

26. The Command Pattern: How it works
The Command Pattern: How it works! Step 9: Executed Commands are Removed (automatic)

27. Agenda Introduction to Data Grids Introduction to Oracle Coherence
Introduction to Data Grid Patterns
The Command Pattern
The Functor Pattern
Vorstellung der Thematik Distributed Cache
Funktionsweise anhand von Coherence wird erklärt
Die Ideen bezüglich Distributed Cache werden vorgestellt:
Ikesa cache
Verwendung Grid anstatt AQ
Die Servicewolke
Demo
The Store and Forward Messaging Pattern

28. The Functor Pattern: Definition
Just like the Command Pattern …
An action to be performed zero or more times at some point in the future should be represented as an object called a Functor
All necessary parameters required to perform the said action, should be encapsulated as attributes within the said Functor object
The Functor object must provide a mechanism to perform the action (typically represented an execute method defined on the said Functor object)
The result of a Functor execution is returned to the submitter using a Java 5+ Future<?>

29. Functor Pattern Demonstration

30. The Functor Pattern: Definition
Just like the Command Pattern …
An action to be performed zero or more times at some point in the future should be represented as an object called a Functor
All necessary parameters required to perform the said action, should be encapsulated as attributes with in the said Functor object
The Functor object must provide a mechanism to perform the action (typically represented an execute method defined on the said Functor object)
Additional Requirement
The result of a Functor execution is returned to the submitter using a Java 5+ Future<?>

31. Agenda Introduction to Data Grids Introduction to Oracle Coherence
Introduction to Data Grid Patterns
The Command Pattern
The Functor Pattern
Vorstellung der Thematik Distributed Cache
Funktionsweise anhand von Coherence wird erklärt
Die Ideen bezüglich Distributed Cache werden vorgestellt:
Ikesa cache
Verwendung Grid anstatt AQ
Die Servicewolke
Demo
The Store and Forward Messaging Pattern

32. The Messaging Pattern: Definition
Payload, typically represented as a Message object, may be sent to a Destination from a Sender (also commonly known as a Publisher)
It is the responsibility of the infrastructure managing the Destination to ensure that Messages (arriving at the said Destination)
are then stored (in some manner) and
consequently forwarded (in the order in which they were sent) to one or more Receivers (also commonly known as Subscribers)

33. The Messaging Pattern: Definition
Subscribers consume (receive and acknowledge receipt) Messages from the Destination in the order in which they were sent from the Publishers
The infrastructure managing the Messages appropriately cleans-up (remove and garbage collect) the Messages that have been consumed by Subscribers
The type of the Destination determines the method of delivery to the Subscribers on that Destination

34. The Messaging Pattern: Definition
A Topic Destination (or Topic) will store and forward Messages to all of the Subscribers of the said Topic Destination This form of Message delivery is often called "publish-and-subscribe messaging", "one- to-many messaging" or "the observer pattern"
A Queue Destination (or Queue) will store and forward Messages to at most one of the Subscribers of the said Queue Destination For each Message a different Subscriber may be used, but this is implementation and runtime dependent. This form of Message delivery is often called "point-to-point messaging" or "one-to-one messaging"

35. The Messaging Pattern: Definition
A Message may be Persistent or Non-Persistent In the case of Persistent Messages, the infrastructure managing the Destination must safely store the said Messages to a persistent (and recoverable) storage device so that in the case of infrastructure failure, Messages may be recovered (not lost)
A Subscriber to a Topic is either Durable or Non-Durable Durable Subscriptions allow the system implementing the Subscriber to terminate and return without losing Messages that may have been delivered during the outage (or disconnection)

36. Messaging Pattern Demonstration

37. Conclusions Data Grids provide more than just “caching” capabilities
Events
Queries
Processing
Analytics
Data Grids (like Coherence) provide reliable (but transaction-free) infrastructure for implementing all kinds of advanced architectural patterns
Data Grids help solve the scalability and performance challenges we have traditionally faced, using pure Java

38. Ihr IT-Partner
Thanks!