Friday, 02 November 2018

Infinispan 9.3.4.Final released!

This is a bug fix release and users currently on 9.3.x are encouraged to upgrade, specially when using the query functionality.

For a list of fixes, please consult the release notes.

Posted by Gustavo on 2018-11-02
Tags: release remote query

Monday, 13 January 2014

A new quick start guide for remote queries over Hot Rod

Following up on the previous post on Infinispan remote queries, we’ve prepared a quick start guide to get you up and running with remote queries in minutes.

It’s a simple Java application that places some data in a remote cache and then retrieves it using queries over Hot Rod. On top of that, the project also contains a C companion app contributed by https://github.com/isavin[Ion Savin] that uses the https://github.com/infinispan/cpp-client/[C Hot Rod client] and is able to read and write (but not query, yet) the same data, demonstrating interoperability between C and Java clients. At this point the Protobuf encoding support comes in a few C external helper classes rather than being part of the C++ client, but this is going to improve in the upcoming versions.   The code for this app is hosted on Github under the jboss-jdg-quickstarts project. Please note this tutorial was written for the JBoss Data Grid (JDG), but it applies to Infinispan as well. We welcome you to try it and let us know what you think!

Posted by Unknown on 2014-01-13
Tags: jdg hotrod quick start cpp-client remote query

Tuesday, 19 November 2013

Infinispan 6.0.0.Final is out!

Dear Infinispan community,

We’re pleased to announce the final release of Infinispan 6.0 "Infinium". As announced, this is the first Infinispan stable version to be released under the terms of Apache License v2.0.

This release brings some highly demanded features besides many stability enhancements and bug fixes:

  • Support for remote query. It is now possible for the HotRod clients to query an Infinispan grid using a new expressive query DSL. This querying functionality is built on top of Apache Lucene and Google Protobuf and lays the foundation for storing information and querying an Infinispan server in a language neutral manner. The Java HotRod client has already been enhanced to support this, the soon-to-be announced C++ HotRod client will also contain this functionality (initially for write/read, then full blown querying).

  • C HotRod client.  Allows C applications to read and write information from an Infinispan server. This is a fully fledged HotRod client that is topology (level 2) and consistent hash aware (level 3) and will be released in the following days. Some features (such as Remote Query and SSL support) will be developed during the next iteration so that it maintains feature parity with its Java counterpart.

  • Better persistence integration. We’ve revisited the entire cache loader API and we’re quite pleased with the result: the new Persistence API brought by Infinispan 6.0 supports parallel iteration of the stored entries, reduces the overall serialization overhead and also is aligned with the JSR-107 specification, which makes implementations more portable.

  • A more efficient FileCacheStore implementation. This file store is built with efficiency in mind: it outperforms the existing file store with up to 2 levels of magnitude. This comes at a cost though, as keys need to be kept  in memory. Thanks to Karsten Blees for contributing this!

  • Support for heterogeneous clusters. Up to this release, every member of the cluster owns an equal share of the cluster’s data. This doesn’t work well if one machine is more powerful than the other cluster participants. This functionality allows specifying the amount of data, compared with the average, held by a particular machine.

  • A new set of usage and performance statistics developed within the scope of the CloudTM projecthttps://issues.jboss.org/browse/ISPN-3234[].

  • JCache (JSR-107) implementation upgrade. First released in Infinispan 5.3.0, the standard caching support is now upgraded to version 1.0.0-PFD.

For a complete list of features included in this release please refer to the release notes.

The user documentation for this release has been revamped and migrated to the new website - we think it looks much better and hope you’ll like it too!

This release has spread over a period of 5 months: a sustained effort from the core development team, QE team and our growing community - a BIG thanks to everybody involved! Please visit our downloads section to find the latest release. Also if you have any questions please check our forums, our mailing lists or ping us directly on IRC.

Cheers,

Adrian

Posted by Unknown on 2013-11-19
Tags: hotrod persistence jsr 107 jcache Protobuf remote query query

Thursday, 26 September 2013

Embedded and remote queries in Infinispan 6.0.0.Beta1

If you’re following Infinispan’s mailing lists you’ve probably caught a glimpse of the new developments in the Query land: a new DSL, remote querying via Hot Rod client, a new marshaller based on Google’s Protobuf. Time to unveil these properly!

==== The new Query DSL

Starting with version 6.0 Infinispan offers a new (experimental) way of running queries against your cached entities based on a simple filtering DSL. The aim of the new DSL is to simplify the way you write queries and to be agnostic of the underlying query mechanism(s) making it possible to provide alternative query engines in the future besides Lucene and still being able to use the same query language/API. The previous Hibernate Search & Lucene based approach is still in place and will continue to be supported and in fact the new DSL is currently implemented right on top of it. The future will surely bring index-less searching based on map-reduce and possibly other new cool search technologies.

Running DSL-based queries in embedded mode is almost identical to running the existing Lucene-based queries. All you need to do is have infinispan-query-dsl.jar and infinispan-query.jar in your classpath (besides Infinispan and its dependecies), enable indexing for your caches, annotate your POJO cache values and your’re ready.

__

ConfigurationBuilder cfg = new ConfigurationBuilder();
cfg.indexing().enable();

DefaultCacheManager cacheManager = new DefaultCacheManager(cfg.build());

Cache cache = cacheManager.getCache();

____Alternatively, indexing (and everything else) can also be configured via XML configuration, as already described in the user guide, so we’ll not delve into details here.

Your Hibernate Search annotated entity might look like this.

__

import org.hibernate.search.annotations.*;
...

@Indexed
public class User {

    @Field(store = Store.YES, analyze = Analyze.NO)
    private String name;

    @Field(store = Store.YES, analyze = Analyze.NO, indexNullAs = Field.DEFAULT_NULL_TOKEN)
    private String surname;

    @IndexedEmbedded(indexNullAs = Field.DEFAULT_NULL_TOKEN)
    private List addresses;

    // .. the rest omitted for brevity
}

___Running a DSL based query involves obtaining a _https://github.com/infinispan/infinispan/blob/6.0.0.Beta1/query-dsl/src/main/java/org/infinispan/query/dsl/QueryFactory.java[QueryFactory] from the (cache scoped) SearchManager and then constructing the query as follows:

__

import org.infinispan.query.Search;
import org.infinispan.query.dsl.QueryFactory;
import org.infinispan.query.dsl.Query;
...

QueryFactory qf = Search.getSearchManager(cache).getQueryFactory();

Query q = qf.from(User.class)
    .having("name").eq("John")
    .toBuilder().build();

List list = q.list();

assertEquals(1, list.size());
assertEquals("John", list.get(0).getName());
assertEquals("Doe", list.get(0).getSurname());

___That’s it! I’m sure this raised your curiosity as to what the DSL is actually capable of so you might want to look at the list of supported filter operators in _https://github.com/infinispan/infinispan/blob/6.0.0.Beta1/query-dsl/src/main/java/org/infinispan/query/dsl/FilterConditionEndContext.java[FilterConditionEndContext]. Combining multiple conditions with boolean operators, including sub-conditions, is also possible:

Query q = qf.from(User.class)
    .having("name").eq("John")
    .and().having("surname").eq("Doe")
    .and().not(qf.having("address.street").like("%Tanzania%").or().having("address.postCode").in("TZ13", "TZ22"))
    .toBuilder().build();

The DSL is pretty nifty right now and will surely be expanded in the future based on your feedback. It also provides support for result pagination, sorting, projections, embedded objects, all demonstrated in QueryDslConditionsTest which I encourage you to look at until the proper user guide is published. Still, this is not a relational database, so keep in mind that all queries are written in the scope of the single targeted entity (and its embedded entities). There are no joins (yet), no correlated subqueries, no grouping or aggregations.

Moving further, probably the most exciting thing about the new DSL is using it remotely via the Hot Rod client. But to make this leap we first had to adopt a common format for storing our cache entries and marshalling them over the wire that would also be cross-language and robust enough to support evolving object schemas. But probably most of all, this format had to have a schema rather than just being an opaque blob otherwise indexing and searching are meaningless. Enter Protocol Buffers.

The Protobuf marshaller

Configuring the RemoteCacheManager of the Java Hot Rod client to use it is straight forward: __

import org.infinispan.client.hotrod.configuration.ConfigurationBuilder;
...

ConfigurationBuilder clientBuilder = new ConfigurationBuilder();
clientBuilder.addServer()
    .host("127.0.0.1").port(11234)
    .marshaller(new ProtoStreamMarshaller());

___Now you’ll be able to store and get from the remote cache your _User instaces encoded in protobuf format provided that:

  1. a Protobuf type was declared for your entity in a .proto file which was then compiled into a .protobin binary descriptor

  2. the binary descriptor was registered with your RemoteCacheManager's ProtoStreamMarshaller instance like this: __

ProtoStreamMarshaller.getSerializationContext(remoteCacheManager)
    .registerProtofile("my-test-schema.protobin");

__3. a per-entity marshaller was registered:

ProtoStreamMarshaller.getSerializationContext(remoteCacheManager)
    .registerMarshaller(User.class, new UserMarshaller());

___Steps 2 and 3 are closely tied to the way Protosteam library works, which is pretty straight forward but cannot be detailed here. Having a look at our _UserMarshaller sample should clear this up.

Keeping your objects stored in protobuf format has the benefit of being able to consume them with compatible clients written in other languages. But if this does not sound enticing enough probably the fact they can now be easily indexed should be more appealing.

Remote querying via the Hot Rod client

Given a RemoteCacheManager configured as previously described the next steps to enable remote query over its caches are:

  1. add the DSL jar to client’s classpath, infinispan-remote-query-server.jar to server’s classpath and infinispan-remote-query-client.jar to both

  2. enable indexing in your cache configuration - same as for embedded mode

  3. register your protobuf binary descriptor by invoking the 'registerProtofile' method of the server’s ProtobufMetadataManager MBean (one instance per EmbeddedCacheManager)

All data placed in cache now is being indexed without the need to annotate your entities for Hibernate Search. In fact these classes are only meaningful to the Java client and do not even exist on the server.

Running the queries over the Hot Rod client is now very similar to embedded mode. The DSL is in fact the same. The only part that is slightly different is how you obtain the QueryFactory:

__

import org.infinispan.client.hotrod.Search;
import org.infinispan.query.dsl.QueryFactory;
import org.infinispan.query.dsl.Query;
...

remoteCache.put(2, new User("John", "Doe", 33));

QueryFactory qf = Search.getQueryFactory(remoteCache);

Query query = qf.from(User.class)
    .having("name").eq("John")
    .toBuilder().build();

List list = query.list();
assertEquals(1, list.size());
assertEquals("John", list.get(0).getName());
assertEquals("Doe", list.get(0).getSurname());

__

  

Voila! The end of our journey for today! Stay tuned, keep an eye on Infinispan Query and please share your comments with us.

Posted by Unknown on 2013-09-26
Tags: protostream hotrod lucene Protobuf remote query hibernate search embedded query Infinispan Query DSL

Thursday, 19 September 2013

Infinispan 6.0.0.Beta1 is out!

Dear Infinispan community,

We are proud to announce the first Beta release of Infinispan 6.0.0. This is an important milestone in the 6.0.0 lifecycle: it is feature and API complete.

Included in this release, you can find:

  • a complete implementation of the remote-query functionality, including index management through JMX .  Adrian Nistor will blog on this in the following days

  • allow configuring the number of segments per node allows one to configure an uneven load of data between the nodes int the cluster. Dan Berindei will add a blog on this shortly

Together with this release we’re also launching our new website:

  •  Built with Awestruct.  Yes, it really is awesome and fun to use

  •  Hosted on GitHub Pages.  Quick and easy.

  •  Styled with JBoss.org Community’s flavour of Twitter Bootstrap 

  •  Documentation reformatted/moved from Confluence to AsciiDoc 

Among other things, the new site reflects some changes in the way Infinispan is distributed - including several cache stores and Hot Rod clients being moved out to separate GitHub repositories and following their own release cycles. 

We think it’s pretty slick and pretty sure you wouldn’t guess its written by a hardcore backed developer! Kudos to Manik Surtani for such a nice job!

Last but certainly not least,  a BIG thanks to our colleagues from the Hibernate team for their support (that is enhancements, fixes and releases and unreasonable hours) in getting the support needed for Infinispan’s remote query functionality in time!

For a complete list of features and fixes included in this release please refer to the release notes[#goog_1579863184]http://www.blogger.com/. Visit our downloads section to find the latest release and if you have any questions please check our forums, our mailing lists or ping us directly on IRC.

Thanks to everyone for their involvement and contribution!

Cheers, Mircea

Posted by Mircea Markus on 2013-09-19
Tags: site remote query uneven load

News

Tags

JUGs alpha as7 asymmetric clusters asynchronous beta c++ cdi chat clustering community conference configuration console data grids data-as-a-service database devoxx distributed executors docker event functional grouping and aggregation hotrod infinispan java 8 jboss cache jcache jclouds jcp jdg jpa judcon kubernetes listeners meetup minor release off-heap openshift performance presentations product protostream radargun radegast recruit release release 8.2 9.0 final release candidate remote query replication queue rest query security spring streams transactions vert.x workshop 8.1.0 API DSL Hibernate-Search Ickle Infinispan Query JP-QL JSON JUGs JavaOne LGPL License NoSQL Open Source Protobuf SCM administration affinity algorithms alpha amazon annotations announcement archetype archetypes as5 as7 asl2 asynchronous atomic maps atomic objects availability aws beer benchmark benchmarks berkeleydb beta beta release blogger book breizh camp buddy replication bugfix c# c++ c3p0 cache benchmark framework cache store cache stores cachestore cassandra cdi cep certification cli cloud storage clustered cache configuration clustered counters clustered locks codemotion codename colocation command line interface community comparison compose concurrency conference conferences configuration console counter cpp-client cpu creative cross site replication csharp custom commands daas data container data entry data grids data structures data-as-a-service deadlock detection demo deployment dev-preview devnation devoxx distributed executors distributed queries distribution docker documentation domain mode dotnet-client dzone refcard ec2 ehcache embedded query equivalence event eviction example externalizers failover faq final fine grained flags flink full-text functional future garbage collection geecon getAll gigaspaces git github gke google graalvm greach conf gsoc hackergarten hadoop hbase health hibernate hibernate ogm hibernate search hot rod hotrod hql http/2 ide index indexing india infinispan infinispan 8 infoq internationalization interoperability interview introduction iteration javascript jboss as 5 jboss asylum jboss cache jbossworld jbug jcache jclouds jcp jdbc jdg jgroups jopr jpa js-client jsr 107 jsr 347 jta judcon kafka kubernetes lambda language leveldb license listeners loader local mode lock striping locking logging lucene mac management map reduce marshalling maven memcached memory migration minikube minishift minor release modules mongodb monitoring multi-tenancy nashorn native near caching netty node.js nodejs nosqlunit off-heap openshift operator oracle osgi overhead paas paid support partition handling partitioning performance persistence podcast presentations protostream public speaking push api putAll python quarkus query quick start radargun radegast react reactive red hat redis rehashing releaase release release candidate remote remote events remote query replication rest rest query roadmap rocksdb ruby s3 scattered cache scripting second level cache provider security segmented server shell site snowcamp spark split brain spring spring boot spring-session stable standards state transfer statistics storage store store by reference store by value streams substratevm synchronization syntax highlighting testing tomcat transactions uneven load user groups user guide vagrant versioning vert.x video videos virtual nodes vote voxxed voxxed days milano wallpaper websocket websockets wildfly workshop xsd xsite yarn zulip

back to top