Oracle Coherence Training with Hands On Exercises

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Oracle Coherence Training Overview and Architecture <Name> <Title>


Overview • Overview • What is Coherence? • How does it work? • Installation • Installing and Testing Coherence • Getting Started • Code Examples • Object Modelling • Integration • In-Grid Processing • Management, Monitoring and Sizing Copyright © 2011. Oracle Corporation


What is Coherence

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Oracle Coherence • Development Library • Pure Java 1.4.2+ • Pure .Net 1.1+ (client) • Pure C++ (client) for Windows, Solaris and Linux • No Third-Party Dependencies • No Open Source Dependencies • Proprietary Network Stack (Peer-To-Peer model) • Other Libraries Support9 • Database and File System Integration • Top Link and Hibernate • Http Session Management • Spring, Groovy Copyright © 2011. Oracle Corporation


Oracle Coherence • Provides9 • Container-less Clustering of Java Processes • Data Structures to manage Data (XML-free) across a Cluster • Real-Time Event Observation – Listener Pattern • Materialized Views of Data – Invariant views (no-polling) • Parallel Queries and Aggregation – Object-based Queries • Parallel Processing – Data and Processing Affinity • RemoteException Free Distributed Computing Services • Clustered JMX • MAN + WAN Data and Processing Services • Client + Data Grid Deployment Models • Point-To-Point Communication Layer Copyright © 2011. Oracle Corporation


Oracle Coherence • Uses9 • Caching Objects in the Application Tier • Relieve load on lower-tier systems • Databases, Mainframes, Web Servers, Web Services

• Managing Object state in the Application Tier • Http Session Management (scale out) • Temporary System of Record for Extreme Transaction Processing

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How Coherence

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Distributed Data Management (access) The Partitioned Topology (one of many) In-Process Data Management

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Distributed Data Management (update)

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Distributed Data Management (failover)

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Distributed Data Management • Members have logical access to all Entries • At most 2 network operations for Access • At most 4 network operations for Update • Regardless of Cluster Size • Deterministic access and update behaviour (performance can be improved with local caching) • Predictable Scalability • Cache Capacity Increases with Cluster Size • Coherence Load-Balances Partitions across Cluster • Point-to-Point Communication (peer to peer) • No multicast required (sometimes not allowed) Copyright © 2011. Oracle Corporation


Data Distribution: Clients and Servers “Clients” with storage disabled

“Servers” with storage enabled

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Near Caching (L1 + L2) Topology

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Observing Data Changes

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Parallel Queries

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Parallel Processing and Aggregation

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Data Source Integration (read-through)

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Data Source Integration (writethrough)

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Data Source Integration (write-behind)

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Configuration • Cache configuration file – client and server • Override file – version, logging, WKA, Security etc. • Command line parameters, macros and properties • POF user types configuration file • .NET configuration via App.config, C++ via

tangosol.coherence.cacheconfig and environment variables Client

Coherence (coherence.xml)

Tangosol Client Override

Application (App.config)

Server

Configuration File

Tangosol Server Override Server POF

Configuration File

Configuration File

Configuration File

Configuration File

Client POF Configuration File

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Server Cache Client Cache Configuration File

Configuration File


Cache Semantics • Client objects are copies not references to objects • Although a cache can contain any object they are

almost always of the same type • Links between objects in different caches are made using key’s • Cache nodes can be storage enabled or disabled • Cache member communications are peer-to-peer

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Coherence Editions • Coherence*Web • Standard Edition • Partitioned Caching • Read-through/write-through support • Enterprise Edition • JMX Support • HTTP Session Caching • Write-behind • Parallel operations, like queries and aggregations • Grid Edition • WAN Replication • Multi-platform Real-time events (used by Continuous Query and Near Cache)

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HTTP Session Caching Overview • No code changes required to use • Portlet state can be cached • Built into WLS and WLP How it works • Built-in to WebLogic Server • Use script to inject into WAR/EAR file • For IIS add as Benefits • Enables stateless middle tier • Better hardware utilization • Simpler network infrastructure • Scales out middle tier

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