Your SlideShare is downloading. ×
  • Like
인피니스팬 데이터그리드 플랫폼
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×

Now you can save presentations on your phone or tablet

Available for both IPhone and Android

Text the download link to your phone

Standard text messaging rates apply

인피니스팬 데이터그리드 플랫폼

  • 352 views
Published

Infinispan Data Grid Platform …

Infinispan Data Grid Platform
JBUG 2013 10th Anniversary Conference, 9 Nov 2013

Published in Technology , Education
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
No Downloads

Views

Total Views
352
On SlideShare
0
From Embeds
0
Number of Embeds
0

Actions

Shares
Downloads
7
Comments
0
Likes
3

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. Data Grid Platform 인피니스팬 소개와 사용 사례 전 재 홍 / Jaehong Cheon 9 Nov 2013
  • 2. Agenda     Data Grid Infinispan Case Study References
  • 3. Data Grid
  • 4. Data Grid  Distributed Cache with persistence – – – – – Performance Boost Dynamic provisioning Fast access to data (in memory) - optionally write-through Elasticity Fault tolerance  Data Grid – Evolution of distributed caches – Well-known pattern to boost data access performance and scalability – Clustered by nature
  • 5. Cache vs. Data Grid  JSR 107 - Temporary Caching for the Java Platform – read, write, expiry, write-through, distributed-manner – JBoss Cache  JSR 347 - Data Grids for the Java Platform – query, consistency, map-reducing standard way – Infinispan
  • 6. Infinispan
  • 7. Infinispan        Distributed In-memory key/value Data Grid/ Cache org.infinispan.Cache Interface Distributed as Library and Server (from 5.3) High availability Elastic Manageable Open source DefaultCacheManager manager = new DefaultCacheManager(); // Cache<Integer, Ticket> cache = manager.getCache(); Cache<Integer, Ticket> cache = manager.getCache(“myCache”);
  • 8. Architecture: Library Library Mode - standalone Infinispan App JVM JCP-107 Style Cache just cache with advantages: expiry, j2ee transaction
  • 9. Architecture: Library (Clustered)  Use as library Library Mode - clustered Infinispan – More features – Richer APIs – Programmatic/ Declarative configuration – Extendable/ embeddable – Faster (API call) App JVM Infinispan App Cluster JVM Infinispan App JVM Application doesn’t know it’s on cluster
  • 10. Architecture: Server Server Mode - clustered  Use as server Infinispan JVM App App Infinispan Cluster JVM Infinispan App JVM – Remote  Memcached, R EST, Hot Rod, WebSocket – Data tier shared by multi-apps – App doesn’t affe ct cluster – Non-java clients  C++, .NET, Rub y, Python, Java
  • 11. Architecture: Durability Durability  Durability Infinispan JVM Cluster Infinispan JVM Infinispan JVM Infinispan JVM Cluster persistence – By replication – By persistence – By replication to other cluster (topology aware)
  • 12. Infinispan: Key Features     Transactions Persistence Querying Map/Reduce
  • 13. Clustering  Peer-to-Peer – No central master, no single point of failure, no single bottle neck  JGroups – Reliable multicast communication library, nodes discovery, sharing data, performing cluster scaling  Consistent Hash – Hash based data distribution – How it finds where data locates  Linear in nature: throughput, capacity  Cluster Mode
  • 14. Cluster Mode: Replication(복제) Replication Mode cache.put(K,V) Cache on Server 2 K,V Cache on Server 1 K,V Cache on Server 3 K,V Cache on Server 4 K,V
  • 15. Cluster Mode: Distribution(분산) Distribution Mode(numOwners=2) cache.put(K,V) Cache on Server 1 K,V cache.get(K,V) Cache on Server 2 K,V Cache on Server 3 Cache on Server 4
  • 16. Cluster Mode: Invalidation(무효화) Invalidation Mode cache.put(K,V2) Cache on Server 1 K,V2 Cache on Server 2 K,V Cache on Server 3 Cache on Server 4 DB
  • 17. Configuration: Declarative <global> <transport clusterName="OperationsCacheCluster"> <properties> <property name="configurationFile“ value="jgroups-tcp.xml" /> </properties> </transport> <globalJmxStatistics enabled="true" /> </global> <default> <clustering mode="replication"> <sync /> </clustering> </default> <namedCache name="secureLayerContextCache"> <eviction strategy="LIRS" maxEntries="2000" /> <expiration lifespan="600000" /> <loaders passivation="true" shared="false" preload="false"> <fileStore fetchPersistentState="true" purgerThreads="3" purgeSynchronously="true" ignoreModifications="false" purgeOnStartup="false" location="${java.io.tmpdir}"> <async /> </fileStore> </loaders> </namedCache>  Eviction(제거)  Expiration(만료) – on cache – on key
  • 18. Configuration: Programmatic  Configuration Based on XML DefaultCacheManager manager = new DefaultCacheManager("infinispan-config.xml"); Configuration baseConf = manager.getDefaultCacheConfiguration(); Configuration config =new ConfigurationBuilder(). read(baseConf).expiration().lifespan(50000).build(); manager.defineConfiguration(programmaticCache, config); Cache<String, String> cache = manager.getCache("secureLayerContextCache");  Programmatic configuration DefaultCacheManager manager = new DefaultCacheManager(); Configuration config = new ConfigurationBuilder() .loaders() .shared(false).passivation(false).preload(false) .addCacheLoader() .cacheLoader(new JdbcStringBasedCacheStore()) .addProperty("connectionFactoryClass","org.infinispan.loaders.jdbc .connectionfactory.ManagedConnectionFactory") .addProperty("datasourceJndiLocation", "java:jboss/datasources/MySQLDS") .addProperty("userName", "root") .addProperty("password", "admin") .async().threadPoolSize(10).build(); manager.defineConfiguration(programmaticCache, config); Cache<String, String> cache = manager.getCache("secureLayerContextCache");
  • 19. Listener  Listener on CacheManager – Node join/ leave, Cache start/ stop  Cache – CRUD, Eviction/ Passivation – Rehashing/ Transaction completion @Listener public class SimpleListener { @CacheEntryCreated public void dataAdded(CacheEntryCreatedEvent event) { if (event.isPre()) { System.out.println("Before creating the entry:" + event.getKey()); } else { System.out.println("After creating the entry:" + event.getKey()); } … } DefaultCacheManager manager = new DefaultCacheManager(); manager.addListener(listener); Cache<Integer, Ticket> cache = manager.getCache(); cache.addListener(listener);
  • 20. Asynchronous APIs  put() and get() and remove() are synchronous – They wait for RPC and Locks (and maybe cache stores)  The asynchronous API returns NotifyingFuture – Events are fired on completion of the operation NotifyingFuture<String> future = c.removeAsync(key); future.attachListener(new FutureListener<String>() { @Override public void futureDone(Future<String> future) { try { future.get(); System.out.printf ("The entry stored under key %s has been removed.", key); } catch (ExecutionException e) { System.out.printf("Failed to remove %s!", key); } } });
  • 21. Key Features: Persistence  Used for durability  Cache Store - Persistence Storage – File System, Cloud, Remote, JDBC, JPA, LevelDB, Cassandra, – HBase, MongoDB, BerkeleyDB, JDBM, REST      CacheLoader, CacheStore(CacheWriter from 6.0) Write-through, write-behind Passivation, activation Store chain Shared store
  • 22. Persistence: Passivation/Activation  Passivation – write to persistence when evicted from memory (default)  Activation – read to memory and remove from persistence
  • 23. Key Features: Transactons  JTA Transaction Support  Support MVCC (Multi-Versioned Concurrency Control)  Isolation Level – READ_COMMITTED (default) – REPEATABLE_READ  Locking Mode – Optimistic Lock (default) – Pessimistic Lock
  • 24. Key Features: Query  JBoss Hibernate Search + Apache Lucene  Query on values  Index Directory – Lucene Directory: in-memory, file system, JDBC – Infinispan Directory  Distributed queries
  • 25. Distributed Execution  Executes codes on distributed nodes  Through a standard JDK ExecutorService interface  Use DistributedCallable extends java.util.concurrent.Callable
  • 26. Key Features: Map/Reduce  Based on Distributed Execution Framework  Mapper, Reducer, Collator, MapReduceTask public interface Mapper<KIn, VIn, KOut, VOut> extends Serializable { void map(KIn key, VIn value, Collector<KOut, VOut> collector); } public interface Reducer<KOut, VOut> extends Serializable { VOut reduce(KOut reducedKey, Iterator<VOut> iter); } public interface Callator<KOut, Vout, R> { R collate(Map<KOut, VOut>); }
  • 27. Client
  • 28. Monitoring/Management  Mbeans on CacheManager, Cache  RHQ (JON, JBoss Operations Network)
  • 29. Spring Integration  Infinispan provider for Spring cache abstraction  infinispan-spring.jar <cache:annotation-driven cache-manager="operationCacheManager"/> <bean id="operationCacheManager" class="org.infinispan.spring.provider.SpringEmbeddedCacheManagerFactoryBean" p:configurationFileLocation="classpath:infinispan-config.xml" /> @Cacheable(value = "secureLayerContextCache", key="#contextId") public SecureLayerContext getSecureLayerContext(String contextId) { return null; } @CachePut(value = "secureLayerContextCache", key="#contextId") public SecureLayerContext setSecureLayerContext(String contextId, SecureLayerContext secureLayerContext) { return secureLayerContext; } @CacheEvict(value = "secureLayerContextCache", key="#contextId") public void removeSecureLayerContext(String contextId) { // Intentionally blank }
  • 30. Infinispan on Jboss AS 7  Used for session clustering, Hibernate L2 cache  Application gets cache with JNDI name using @Resource  XML Configuration in server configuration file <cache-container name="web" aliases="standard-session-cache" default-cache="repl"> <transport lock-timeout="60000" /> <replicated-cache name="repl" mode="ASYNC" batching="true"> <file-store /> </replicated-cache> </cache-container>
  • 31. JDG     Red Hat JBoss Data Grid Infinispan-based JON All the benefits of subscription, including Red Hat world class support and services
  • 32. Radar Gun  Data grid and distributed cache benchmarking framework  Built to test Infinispan and other distributed data grid platforms  https://github.com/radargun/radargun
  • 33. Case Study
  • 34. Case Study: Session Clustering  Store session information into cache in Spring MVC Interceptor
  • 35. Case Study: Session Clustering Store session information into cache in Spring Security Filter - - SecurityContextRepository를 구현한 CacheSecurityContextRepository 작성 loadContext, saveContext를 오버라이드하여 인피니스팬 사용 Spring cache abstraction 사용
  • 36. Use Cases: Storm Processing State Store Infinispan Data Grid
  • 37. References www.acornpub.co.kr/book/infinispan infinispan.org blog.infinispan.org infinispan-ko.blogspot.com facebook.com/groups/infinispan red.ht/data-grid tedwon.com/display /dev/Infinispan+Data+Grid  cbcpascal.blogspot.kr       
  • 38. jbugkorea.org