Using JPA applications in the era of NoSQL: Introducing Hibernate OGM
Upcoming SlideShare
Loading in...5
×
 

Using JPA applications in the era of NoSQL: Introducing Hibernate OGM

on

  • 5,091 views

Apresentação de Sanne Grinovero - 8º encontro PT.JUG.

Apresentação de Sanne Grinovero - 8º encontro PT.JUG.

Statistics

Views

Total Views
5,091
Views on SlideShare
3,491
Embed Views
1,600

Actions

Likes
1
Downloads
25
Comments
0

6 Embeds 1,600

http://jug.pt 1417
http://ptjug.wordpress.com 109
http://lanyrd.com 54
http://www.java.pt 15
http://blog-ptjug.rhcloud.com 3
http://translate.googleusercontent.com 2

Accessibility

Categories

Upload Details

Uploaded via as Adobe PDF

Usage Rights

CC Attribution-NonCommercial-NoDerivs LicenseCC Attribution-NonCommercial-NoDerivs LicenseCC Attribution-NonCommercial-NoDerivs License

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

    Using JPA applications in the era of NoSQL: Introducing Hibernate OGM Using JPA applications in the era of NoSQL: Introducing Hibernate OGM Presentation Transcript

    • Coimbra, April 18th, 2012 Sanne Grinovero Hibernate Team, JBoss Red Hat, Inc
    • About me• Hibernate in.relation.to/Bloggers/Sanne • Hibernate Search • Hibernate OGM Twitter: @SanneGrinovero• Infinispan • Lucene Directory • Infinispan Query Studied at FEUP (Porto)!
    • Hibernate Object/Grid Mapper ? JPA for NoSQL • initially Key/Value store • we started with Infinispan
    • Relational Databases • Transactions • Referential integrity • Simple Types • Well understood - tuning, backup, resilience
    • Relational Databases But scaling is hard! -Replication -Multiple instances w/ shared disk -Sharding
    • Relational Databases on a cloudMaster/replicas: which master?A single master? I was promised elasticityLess reliable “disks”IP in configuration files? DNS update times?Who coordinates this? How does that failover?
    • ¬SQLmore meaning NotOnlySQL ¬SQL U SQL = anything
    • No-SQL goalsVery heterogeneus• Large datasets• High availability• Low latency / higher throughput• Specific data access pattern• Specific data structures• ...
    • NotOnlySQL• Document based stores• Column based• Graph oriented databases• Key / value stores• Full-Text Search
    • NotOnlySQLChoose one. Before starting. Stick to it.
    • Flexibility at a cost• Programming model • one per product :-( • Often very thight code coupling • No standard drivers / stable APIs• no schema => app driven schema• query (Map Reduce, specific DSL, ...)• data structure transpires• Transactions ?• durability / consistency puzzles
    • Where does Infinispan fit?Distributed Key/Value store • (or Replicated, local only efficient cache, invalidating cache) Each node is equal • Just start more nodes, or kill some No bottlenecks • by design Cloud-network friendly • JGroups • And “cloud storage” friendly too!
    • But how to use it?map.put( “user-34”, userInstance );map.get( “user-34” );map.remove( “user-34” );
    • Its a ConcurrentMap !map.put( “user-34”, userInstance );map.get( “user-34” );map.remove( “user-34” );map.putIfAbsent( “user-38”, another );
    • Other Hibernate/Infinispan collaborations● Second level cache for Hibernate ORM● Hibernate Search indexing backend● Infinispan Query
    • Cloud-hack experimentsLets play with Infinispans integration forHibernates second level cache design: - usually configured in clustering mode INVALIDATION. •Lets use DIST or REPL instead. - Disable expiry/timeouts. Whats the effect on your cloud-deployed database?
    • Cloud-hack experimentsNow introduce Hibernate Search: - full-text queries should be handled byLucene, NOT by the database.Hibernate Search identifies hits from theLucene index, but loads them by PK. *by default
    • Whats the work left to the database?
    • These tools are very appropriate for the job:Load by PK -> second level cache -> Key/Value storeFullText query -> Hibernate Search -> Lucene Indexes
    • These tools are very appropriate for the job:Load by PK -> second level cache -> Key/Value storeFullText query -> Hibernate Search -> Lucene Indexes What if we now shut down the database?
    • Goals• Encourage new data usage patterns• Familiar environment• Ease of use• Easy to jump in• Easy to jump out• Push NoSQL exploration in enterprises• “PaaS for existing API” initiative
    • What it does• JPA front end to key/value stores • Object CRUD (incl polymorphism and associations) • OO queries (JP-QL)• Reuses • Hibernate Core • Hibernate Search (and Lucene) • Infinispan• Is not a silver bullet • not for all NoSQL use cases
    • Concepts
    • Schema or no schema?• Schema-less • move to new schema very easy • app deal with old and new structure or migrate all data • need strict development guidelines• Schema • reduce likelihood of rogue developer corruption • share with other apps • “didn’t think about that” bugs reduced
    • Entities as serialized blobs?• Serialize objects into the (key) value • store the whole graph?• maintain consistency with duplicated objects • guaranteed identity a == b • concurrency / latency • structure change and (de)serialization, class definition changes
    • OGM’s approach to schema• Keep what’s best from relational model • as much as possible • tables / columns / pks• Decorrelate object structure from data structure• Data stored as (self-described) tuples• Core types limited • portability
    • OGM’s approach to schema• Store metadata for queries • Lucene index• CRUD operations are key lookups
    • How does it work?• Entities are stored as tuples (Map<String,Object>) • Or Documents?• The key is composed of • table name • entity id• Collections are represented as a list of tuples- The key is composed of: • table name hosting the collection information • column names representing the FK • column values representing the FK
    • Lets see some code...
    • Queries / Infinispan• Hibernate Search indexes entities• Store Lucene indexes in Infinispan• JP-QL to Lucene query transformation• Works for simple queries • Lucene is not a relational SQL engine
    • select a from Animal a where a.size > 20> animalQueryBuilder.range().onField(“size”).above(20).excludeLimit().createQuery();select u from Order o join o.user u where o.price > 100 and u.city =“Paris”> orderQB.bool() .must( orderQB.range() .onField(“price”).above(100).excludeLimit().createQuery() ) .must( orderQB.keyword(“user.city”).matching(“Paris”) .createQuery()).createQuery();
    • Why Infinispan?• We know it well• Supports transactions• Supports distribution of Lucene indexes• Designed for clouds• Its a key/value store with support for Map/Reduce • Simple • Likely a common point for many other “databases”
    • Why Infinispan?•Map/Reduce as an alternative to indexed queries •Might be chosen by a clever JP-QL engine•Potential for additional query types
    • Why ?Nothing new to learn for most common operations:• JPA models• JP-QL queriesEverything else is performance tuning, including:• Move to/from different NoSQL implementations• Move to/from a SQL implementation• Move to/from clouds/laptops• JPA is a well known standard: move to/from Hibernate :-)
    • Development state: • Query via Hibernate Search • Smart JP-QL parser is on github • Available in master: • EHCache • Infinispan • In development branches: • MongoDB • Voldemort
    • Summary• Performance / scalability is different• Isolation is different
    • http://ogm.hibernate.org
    • http://www.jboss.org/jbw2011keynote.html https://github.com/Sanne/tweets-ogm
    • Q+A