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

Coimbra, April 18th, 2012

Sanne GrinoveroHibernate Team, JBoss

Red Hat, Inc

About me• Hibernate

• Hibernate Search

• Hibernate OGM

• Infinispan

• Lucene Directory

• Infinispan Query

in.relation.to/Bloggers/Sanne

Twitter: @SanneGrinovero

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 cloud

Master/replicas: which master?

A single master? I was promised elasticity

Less reliable “disks”

IP in configuration files? DNS update times?

Who coordinates this? How does that failover?

¬SQL

more 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• ...

• Document based stores • Column based • Graph oriented databases• Key / value stores• Full-Text Search

NotOnlySQL

Choose one.Before starting.

Stick to it.

NotOnlySQL

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” );

It's a ConcurrentMap !

map.put( “user-34”, userInstance );

map.get( “user-34” );

map.remove( “user-34” );

map.putIfAbsent( “user-38”, another );

Other Hibernate/Infinispancollaborations

● Second level cache for Hibernate ORM

● Hibernate Search indexing backend

● Infinispan Query

Cloud-hack experiments

Let's play with Infinispan's integration for Hibernate's second level cache design:- usually configured in clustering mode INVALIDATION.

•Let's use DIST or REPL instead.- Disable expiry/timeouts.

What's the effect on your cloud-deployed database?

Cloud-hack experiments

Now introduce Hibernate Search: - full-text queries should be handled by Lucene, NOT by the database.

Hibernate Search identifies hits from the Lucene index, but loads them by PK. *by default

What's the work left to the database?

These tools are very appropriate for the job:

Load by PK ->second level cache ->

Key/Value store

FullText query ->Hibernate Search ->

Lucene Indexes

These tools are very appropriate for the job:

Load by PK ->second level cache ->

Key/Value store

FullText 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

• 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

How does it work?

Let's 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•It's 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 queries

Everything 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.htmlhttps://github.com/Sanne/tweets-ogm

Q + A