Wednesday, 06 March 2019

Triple cachestore release: Cloud, MongoDB and Cassandra

Today we present to you a trifecta of cache store releases which align to Infinispan 9.x

Cassandra Cache Store

The Cassandra cache store now implements the publishEntries/publishKeys methods.

Cloud Cache Store

The Cloud cache store uses the Apache jclouds library to store data on cloud storage providers such as Amazon’s S3, Rackspace’s Cloudfiles or any other such provider supported by JClouds. The store has been updated to Infinispan 9.x’s persistence SPI and uses jclouds 2.1.x

MongoDB Cache Store

This cache store has also been updated to the Infinispan 9.x persistence SPI.

You can get documentation and maven coordinates from our Cache Store page

Posted by Tristan Tarrant on 2019-03-06
Tags: release cache store

Friday, 20 October 2017

Cache Store Batch Operations

Infinispan 9.1.x introduces batch write and delete operations for cache stores. The introduction of batching should greatly improve performance when utilising write-behind cache stores, using putAll operations and committing transactions in non-transactional stores.

==

==

==

CacheWriter Interface Additions

The CacheWriter interface has been extended so that it exposes two additional methods: deleteBatch and writeBatch.  For the sake of backwards compatibility a default implementation of these methods is provided, however if your cache store is able to utilise batching we strongly recommend you create your  own implementations. The additional methods and docs are show below: 

Updated Stores

Currently the JDBC, JPA, RocksDB and Remote stores have all been modified to take advantage of these latest changes.

==

==

Configuration Changes

As each store implementations has different batching capabilities, it was necessary to introduce a max-batch-size attribute to the AbstractStoreConfiguration. This attribute defines the maximum number of entries that should be included in a single batch operation to the store. If a value less than one is provided, then the underlying store implementation should not place a upper limit on the number of entries in a batch. 

Deprecated Attributes

Both TableManipulationConfiguration#batchSize and JpaStoreConfiguration#batchSize have been deprecated, as they serve the same purpose as AbstractStoreConfiguration#maxBatchSize.

Store Benchmark

To measure the impact of batch writes on Cache.putAll, we created a simple benchmark to compare the performance of Infinispan 9.1.1.Final (with batching) and 9.0.3.Final (without).  The benchmark consisted of 20 threads inserting 100000 cache entries as fast as possible into a cache via putAll; with each putAll operation containing 20 cache entries and the max-batch-size of each store being set to 20. The table below shows the average time taken for each store type after the benchmark was executed three times.

Store Type 9.0.3.Final 9.1.1-Final Latency Decrease

JdbcStringBasedStore

29368ms

2597ms

91.12%

JPAStore

30798ms

16640ms

45.97%

RocksDBStore

1164ms

209ms

82.04%

The benchmark results above clearly show that performance is increased dramatically when utilising batch updates at the store level.

Conclusions

Infinispan 9.1.x introduces batching capabilities to the CacheWriter interface in order to improve performance. If you currently utilise a custom cache store, we strongly recommend that you provide your own implementation of the delete and write batch methods. 

If you have any feedback on the CacheWriter changes, or would like to request some new features/optimisations, let us know via the forumissue tracker or the #infinispan channel onhttp://webchat.freenode.net/?channels=%23infinispan[ Freenode].

Posted by Ryan Emerson on 2017-10-20
Tags: jdbc rocksdb jpa leveldb cache store

Monday, 05 December 2016

Composing the Infinispan Docker image

In the previous post we showed how to manipulate the Infinispan Docker container configuration at both runtime and boot time.

Before diving into multi-host Docker usage, in this post we’ll explore how to create multi-container Docker applications involving Infinispan with the help of Docker Compose.

For this we’ll look at a typical scenario of an Infinispan server backed by an Oracle database as a cache store.

All the code for this sample can be found on github.

 

Infinispan with Oracle JDBC cache store

 

In order to have a cache with persistence with Oracle, we need to do some configuration: configure the driver in the server, create the data source associated with the driver, and configure the cache itself with JDBC persistence.

Let’s take a look at each of those steps:

Obtaining and configuring the driver

The driver (ojdbc6.jar) should be downloaded and placed in the 'driver' folder of the sample project.

The module.xml declaration used to make it available on the server is as follows:

Configuring the Data source

The data source is configured in the "datasource" element of the server configuration file as shown below:

and inside the "datasource/drivers" element, we need to declare the driver:

Creating the cache

The last piece is to define a cache with the proper JDBC Store:

Putting all together

From now on, without using Docker we’d be ready to download and install Oracle following the specific instructions for your OS, then download the Infinispan Server, edit the configuration files, copy over the driver jar, figure out how to launch the database and server, taking care not to have any port conflicts.

If it sounds too much work, it’s because it really is. Wouldn’t it be nice to have all these wired together and launched with a simple command line? Let’s take a look at the Docker way next. 

Enter Docker Compose

Docker Compose is a tool part of the Docker stack to facilitate configuration, execution and management of related Docker containers.

By describing the application aspects in a single yaml file, it allows centralized control of the containers, including custom configuration and parameters, and it also allows runtime interactions with each of the exposed services.

Composing Infinispan

Our Docker Compose file to assemble the application is given below:

It contains two services:

  • one called oracle that uses the wnameless/oracle-xe-11g Docker image, with an environment variable to allow remote connections.

  •  another one called *infinispan* that uses version 8.2.5.Final of the Infinispan Server image. It is launched with a custom command pointing to the changed configuration file and it also mounts two volumes in the container: one for the driver and its module.xml and another for the folder holding our server xml configuration.

Launching

To start the application, just execute

To inspect the status of the containers:

To follow the Infinispan server logs, use:

Infinispan usually starts faster than the database, and since the server waits until the database is ready (more on that later), keep an eye in the log output for "Infinispan Server 8.2.5.Final (WildFly Core 2.0.10.Final) started". After that, both Infinispan and Oracle are properly initialized.

Testing it

Let’s insert a value using the Rest endpoint from Infinispan and verify it was saved to the Oracle database:

To check the Oracle database, we can attach to the container and use Sqlplus:

Other operations

It’s also possible to increase and decrease the number of containers for each of the services:

A thing or two about startup order

 

When dealing with dependent containers in Docker based environments, it’s highly recommended to make the connection obtention between parties robust enough so that the fact that one dependency is not totally initialized doesn’t cause the whole application to fail when starting.

Although Compose does have a depends_on instruction, it simply starts the containers in the declared order but it has no means to detected when a certain container is fully initialized and ready to serve requests before launching a dependent one.

One may be tempted to simply write some glue script to detect if a certain port is open, but that does not work in practice: the network socket may be opened, but the background service could still be in transient initialization state.

The recommended solution for this it to make whoever depends on a service to retry periodically until the dependency is ready. On the Infinispan + Oracle case, we specifically configured the data source with retries to avoid failing at once if the database is not ready:

When starting the application via Compose you’ll notice that Infinispan print some WARN with connection exceptions until Oracle is available: don’t panic, this is expected!

Conclusion

Docker Compose is a powerful and easy to use tool to launch applications involving multiple containers: in this post it allowed to start Infinispan plus Oracle with custom configurations with a single command. It’s also a handy tool to have during development and testing phase of a project, specially when using/evaluating Infinispan with its many possible integrations.

Be sure to check other examples of using Docker Compose involving Infinispan: the Infinispan+Spark Twitter demo, and the Infinispan+Apache Flink demo.

Posted by Gustavo on 2016-12-05
Tags: compose jdbc docker persistence server modules oracle cache store

Friday, 12 August 2016

Infinispan Cloud Cachestore 8.0.1.Final

After bringing the MongoDB up-to-date a few days ago, this time it’s the turn of the Cloud Cache Store, our JClouds-based store which allows you to use any of the JClouds BlobStore providers to persist your cache data. This includes AWS S3, Google Cloud Storage, Azure Blob Storage and Rackspace Cloud Files. In a perfect world this would have been 8.0.0.Final, but Sod’s law rules, so I give you 8.0.1.Final instead :) So head on over to our store download page and try it out.

The actual configuration of the cachestore depends on the provider, so refer to the JClouds documentation. The following is a programmatic example using the "transient" provider:  

And this is how you’d configure it declaratively:

This will work with any Infinispan 8.x release.

Enjoy !

Posted by Tristan Tarrant on 2016-08-12
Tags: release jclouds cloud storage cache store

Friday, 05 August 2016

MongoDB Cache Store 8.2.1.Final

In the storm of the persistence SPI rework that happened during Infinispan 6.0, the MongoDB cache store, among others, was left in a state of semi-abandonment for a long time.

Fortunately a few brave souls came to its rescue and have breathed new life into it so that it can be used with Infinispan 8.x

In particular I wish to thank Kurt Lehrke for doing most of the work !!!

Posted by Tristan Tarrant on 2016-08-05
Tags: release mongodb cache store

Wednesday, 03 February 2016

The return of the Cassandra CacheStore

Ever since we spruced up our Cache Store SPI in Infinispan 6.0, some of our "extra" cache stores have lied in a state of semi-abandonment, waiting for a kind soul with time and determination to bring them back to life. I’m glad to announce that such a kind soul, in the form of Jakub Markos, had the necessary qualities to accomplish the resurrection of the Cassandra Cache Store.

Apache Cassandra is a database with a distributed architecture which can be used to provide a virtually unlimited, horizontally scalable persistent store for Infinispan’s caches. The new Cassandra Cache Store leverages the Datastax Cassandra client driver instead of the old Thrift client approach, which makes it much more robust and reliable.

Configuration

In order to use this cache store you need to add the following dependency to your project:

You will also need to create an appropriate keyspace on your Cassandra database, or configure the auto-create-keyspace to create it automatically. The following CQL commands show how to configure the keyspace manually (using cqlsh for example):

You then need to add an appropriate cache declaration to your infinispan.xml (or whichever file you use to configure Infinispan):

It is important the the shared property on the cassandra-store element is set to true because all the Infinispan nodes will share the same Cassandra cluster.

Limitations

The cache store uses Cassandra’s own expiration mechanisms (time to live = TTL) to handle expiration of entries. Since TTL is specified in seconds, expiration lifespan and maxIdle values are handled only with seconds-precision.

In addition to this, when both lifespan and maxIdle are used, entries in the cache store effectively behave as if their lifespan = maxIdle, due to an existing bug https://issues.jboss.org/browse/ISPN-3202.

So, try it out and let us know about your experience !

Posted by Tristan Tarrant on 2016-02-03
Tags: persistence cassandra cache store

Monday, 14 September 2015

New Redis Cache Store Introduced in Infinispan 8

A new cache store for storage of cache data within the Redis key/value server has been introduced with Infinispan 8. This allows all storage of cache data to be stored in a centralised Redis deployment which all Infinispan clients access.

The cache store supports 3 Redis deployment topologies. They are, single server, Sentinel and cluster (Redis v3 required). Redis versions 2.8+ and 3.0+ are currently supported.

Data expiration and purging is handled via Redis itself, reducing workload from Infinispan servers to manually delete cache entries.

Topologies

Single Server

In a single server deployment, the cache store is given the location of a Redis master server with which it connects to directly to handle all data storage. Using this topology, Redis has no fault tolerance unless a custom solution is built on top of Redis. To declare a single server local cache store:

<?xml version="1.0" encoding="UTF-8"?>

<infinispan

    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"

    xsi:schemaLocation="urn:infinispan:config:8.0 http://www.infinispan.org/schemas/infinispan-config-8.0.xsd

                          urn:infinispan:config:store:redis:8.0 http://www.infinispan.org/schemas/infinispan-cachestore-redis-config-8.0.xsd"

    xmlns="urn:infinispan:config:8.0"

    xmlns:redis="urn:infinispan:config:store:redis:8.0" >

    <cache-container>

        <local-cache>

            <persistence passivation="false">

                <redis-store xmlns="urn:infinispan:config:store:redis:8.0"

                    topology="server" socket-timeout="10000" connection-timeout="10000">

                    <redis-server host="server1" />

                    <connection-pool min-idle="6" max-idle="10" max-total="20" min-evictable-idle-time="30000" time-between-eviction-runs="30000" />

                </redis-store>

            </persistence>

        </local-cache>

    </cache-container>

</infinispan>

Note the topology attribute is declared as server. This is needed to ensure a single server Redis topology is applied by the cache store. Only a single Redis server need be declared (only the first server will be used if multiple servers are declared) and the port will default to the Redis port 6379, but can be overridden using the port attribute. All connections are handled via a connection pool, which can optionally also test the validity of a connection on creation, lease, return from and when idling in the connection the pool.

Sentinel

The Sentinel topology relies on Redis Sentinel servers to connect to a Redis master server. Here, Infinispan connects to Redis Sentinel servers, requesting a master server name, then gets forwarded on to the correct location of the Redis master server. This topology gives resilience via Redis Sentinel, providing failure detection and automatic failover of Redis servers.

<?xml version="1.0" encoding="UTF-8"?>

<infinispan

    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"

    xsi:schemaLocation="urn:infinispan:config:8.0 http://www.infinispan.org/schemas/infinispan-config-8.0.xsd

                          urn:infinispan:config:store:redis:8.0 http://www.infinispan.org/schemas/infinispan-cachestore-redis-config-8.0.xsd"

    xmlns="urn:infinispan:config:8.0"

    xmlns:redis="urn:infinispan:config:store:redis:8.0" >

    <cache-container>

        <local-cache>

            <persistence passivation="false">

                <redis-store xmlns="urn:infinispan:config:store:redis:8.0"

                    topology="sentinel" master-name="mymaster" socket-timeout="10000" connection-timeout="10000">

                    <sentinel-server host="server1" />

                    <sentinel-server host="server2" />

                    <sentinel-server host="server3" />

                    <connection-pool min-idle="6" max-idle="10" max-total="20" min-evictable-idle-time="30000" time-between-eviction-runs="30000" />

                </redis-store>

            </persistence>

        </local-cache>

    </cache-container>

</infinispan>

For a Sentinel deployment, the topology attribute changes to sentinel. A master name must also be specified to select the correct Redis master required as Sentinel can monitor multiple Redis master servers. The Sentinel server is declared using a sentinel-server XML tag, which you’ll notice is different to the main Redis servers used in single server and cluster topologies. This is to allow defaulting of the Sentinel port to 26379 if not declared. At least one Sentinel server must be declared, though if you run more Sentinel servers, they should all be declared too for the benefit of failure detection of the Sentinel servers themselves.

Cluster

A cluster topology gives Infinispan the ability to connect to a Redis cluster. One or more cluster nodes are declared to infinispan (the more the better) which are then used to store all data. Redis cluster supports failure detection so if a master node in the cluster fails, a slave takes over. Redis v3 is required to run a Redis cluster.

<?xml version="1.0" encoding="UTF-8"?>

<infinispan

    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"

    xsi:schemaLocation="urn:infinispan:config:8.0 http://www.infinispan.org/schemas/infinispan-config-8.0.xsd

                          urn:infinispan:config:store:redis:8.0 http://www.infinispan.org/schemas/infinispan-cachestore-redis-config-8.0.xsd"

    xmlns="urn:infinispan:config:8.0"

    xmlns:redis="urn:infinispan:config:store:redis:8.0" >

    <cache-container>

        <local-cache>

            <persistence passivation="false">

                <redis-store xmlns="urn:infinispan:config:store:redis:8.0"

                    topology="cluster" socket-timeout="10000" connection-timeout="10000">

                    <redis-server host="server1" port="6379" />

                    <redis-server host="server2" port="6379" />

                    <redis-server host="server3" port="6379" />

                    <connection-pool min-idle="6" max-idle="10" max-total="20" min-evictable-idle-time="30000" time-between-eviction-runs="30000" />

                </redis-store>

            </persistence>

        </local-cache>

    </cache-container>

</infinispan>

For cluster deployments, the topology attribute must change to cluster. One or more Redis cluster nodes must be declared to access the cluster which uses the redis-server XML tag. Note that when operating a cluster, database IDs are not supported.

Multiple Cache Stores, Single Redis Deployment

Redis single server and Sentinel deployments support the option of database IDs. A database ID allows a single Redis server to host multiple individual databases, referenced via an integer ID number. This allows Infinispan to support multiple cache stores on the same Redis deployment, isolating the data between the stores. Redis cluster does not support the database ID. A database ID is defined using the database attribute on the redis-store XML tag.

<?xml version="1.0" encoding="UTF-8"?>

<infinispan

    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"

    xsi:schemaLocation="urn:infinispan:config:8.0 http://www.infinispan.org/schemas/infinispan-config-8.0.xsd

                          urn:infinispan:config:store:redis:8.0 http://www.infinispan.org/schemas/infinispan-cachestore-redis-config-8.0.xsd"

    xmlns="urn:infinispan:config:8.0"

    xmlns:redis="urn:infinispan:config:store:redis:8.0" >

    <cache-container>

        <local-cache>

            <persistence passivation="false">

                <redis-store xmlns="urn:infinispan:config:store:redis:8.0"

                    topology="sentinel" master-name="mymaster" socket-timeout="10000" connection-timeout="10000" database="5">

                    <sentinel-server host="server1" />

                    <sentinel-server host="server2" />

                    <sentinel-server host="server3" />

                    <connection-pool min-idle="6" max-idle="10" max-total="20" min-evictable-idle-time="30000" time-between-eviction-runs="30000" />

                </redis-store>

            </persistence>

        </local-cache>

    </cache-container>

</infinispan>

Redis Password Authentication

In order to secure access to a Redis server, a password can optionally be used in Redis. This then requires the cache store to declare the password when connecting. The password is added via a password attribute on the redis-store XML tag.

<?xml version="1.0" encoding="UTF-8"?>

<infinispan

    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"

    xsi:schemaLocation="urn:infinispan:config:8.0 http://www.infinispan.org/schemas/infinispan-config-8.0.xsd

                          urn:infinispan:config:store:redis:8.0 http://www.infinispan.org/schemas/infinispan-cachestore-redis-config-8.0.xsd"

    xmlns="urn:infinispan:config:8.0"

    xmlns:redis="urn:infinispan:config:store:redis:8.0" >

    <cache-container>

        <local-cache>

            <persistence passivation="false">

                <redis-store xmlns="urn:infinispan:config:store:redis:8.0"

                    topology="sentinel" master-name="mymaster" socket-timeout="10000" connection-timeout="10000" password="mysecret">

                    <sentinel-server host="server1" />

                    <sentinel-server host="server2" />

                    <sentinel-server host="server3" />

                    <connection-pool min-idle="6" max-idle="10" max-total="20" min-evictable-idle-time="30000" time-between-eviction-runs="30000" />

                </redis-store>

            </persistence>

        </local-cache>

    </cache-container>

</infinispan>

What about SSL support?

Redis does not provide protocol encryption, instead leaving this to other specialist software. At this time, the Redis client used to integrate Infinispan with Redis servers (Jedis) does not yet support SSL connection negotiation natively.

**

Posted by Unknown on 2015-09-14
Tags: release redis cache store

Tuesday, 11 August 2015

Infinispan 7.2.4.Final out including fixes for async store, Hot Rod...etc

Infinispan 7.2.4.Final is just out containing some important fixes in areas such as Hot Rod client and server, async cache store, key set iteration, as well as a Hibernate HQL parser upgrade. You can find more details about the issues fixed in our detailed release notes.

Happy hacking :)

Galder

Posted by Galder Zamarreño on 2015-08-11
Tags: release hotrod hql cache store

Monday, 09 September 2013

Infinispan 6.0.0.Alpha4 out with new CacheLoader/CacheWriter API!

Infinispan 6.0.0.Alpha4 is now with a few very important changes, particularly around cache stores. We’ve completely revamped the cache store/loader API to align it a bit better with JSR-107 (old CacheStore has become CacheWriter) and to simplify creation of new implementations. The new CacheLoader and CacheWriter should help implementors focus on the important operations and reduce the coding time. We’ve also created AdvancedCacheLoader and AdvancedCacheWriter in order to separate for bulk operations or purging for those implementations that wish optionally implement them. Expect a blog post from Mircea in the next few days providing many more details on this topic.

This new Infinispan version comes with other important goodies:

  • Rolling upgrades of a Infinsipan REST cluster

  • Support for Cache-Control headers for REST operations

  • Remote querying server modules and Hot Rod client update

  • REST and LevelDB stores added to Infinispan Server

  • KeyFilters can now be applied to Cache listeners

  • Allow Cache listener events to be invoked only on the primary data owner

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

Cheers,

Galder

Posted by Galder Zamarreño on 2013-09-09
Tags: release leveldb listeners alpha rest cache store query

Tuesday, 04 June 2013

Using MongoDB as a cache store

With the 5.3 release, there is a brand new feature. I’m glad to announce that you will be able to use MongoDB as a cache store.

For those who don’t know MongoDB, it’s an open-source document oriented NoSQL database developped by 10Gen. You can more information about it on http://www.mongodb.org/.

The question you have right now, it probably, how to use it cool cache store ? Simple, as for the other cache store you have to add a loader in your Infinispan configuration file.

Here is an exemple:

If you prefer the programmatic API:

For more information about the configuration possibilities (default values, options, etc) , you can refer to the documentation page

Cheers, Guillaume Hibernate OGM & Infinispan contributor Blog / @g_scheibel

Posted by Unknown on 2013-06-04
Tags: mongodb cache store

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