Event Listener with C++

Dear Infinispan community,

as announced in a previous post, starting from version 8.1.0 also the C++/C# clients can receive and process Infinispan events.

Here’s an example of usage of C++ event listeners that, with a good dose of imagination, pretends to be a customer behavior tracking system for our store chain (don’t take this too seriously, we’re just trying to add some fiction).

As a first requirement our tracking system will record every single purchase made in our stores. How many stores we have? 1, 100, millions? It doesn’t matter: we’re backed with an Infinispan data grid. This is version 0.x and hence the checker must use the keyboard to enter all the needed information.

As you can see our entry key is a concatenation of the product name and the timestamp and the entry value is an unstructured string, maybe too simply but it could work for now. Seems we are at a good point: we have the data and we can do analytics on it, so far so good but now our boss makes a new request: he wants a runtime monitor on how’s the sales performance. That’s a perfect request to be fulfilled with event listener: the monitor application will be an Hotrod C++ client that registers a client listener on the server and receives and show on the boss’s laptop the data flow. A client listener, once registered on the server, can receive events related to: creation, modification, deletion, expiration of cache entries; in our example only the creation and expiration events are processed (expired events can be useful to do some moving average statistics?). Following a snip of code that creates and registers a listener that writes the events key on the stdout.

You can git this quickstart here [1]. On startup a multiple choice menu is shown with all the available operations. Running several instances you can act as the checker (data entry) or the boss (installing the listener and seeing the events flow).

Filters

Again so far so good, but then the marketing department ask support to do targeted advertising like: soliciting customers that bought product Y to buy product X. Let’s suppose that X="harmonica" and Y="hiking boots" (it’s a well known fact of life that in the high mountains you feel the desire to play an harmonica).

To do that we register on the server another listener, but this time we’re not interested in the whole flow of purchase data: to run our marketing campaign, we only interested in cache entries having the key starting with "hiking". The Infinispan server can filter out events for us, if we pass in the AddClientListener operation the name of the wanted filter along with any configuration arguments.

Filter are java classes that must be deployed into the Infinispan server (more here [2])

and converters

Predefined events contain very few information: basically the event type and the entry key, this to prevent to flood the network spreading around very long entry values. Users can override this limitation using a converter, that is a java class deployed into the server, that can create custom events containing every data needed by the application.

As in the previous case, we pass into the add operation the name of the converter and the configuration arguments, any.

That’s all guys, let us know your feedback: do you like it? Could be better? Tell us how it can be improved creating an issue [3], or fork and improve it yourself [4]!

Thanks for reading and enjoy! The Infinispan Team

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 anchored keys 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 development devnation devoxx distributed executors distributed queries distribution docker documentation domain mode dotnet-client dzone refcard ec2 ehcache embedded 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 learning 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 non-blocking nosqlunit off-heap openshift operator oracle osgi overhead paas paid support partition handling partitioning performance persistence podcast presentation 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 tdc testing tomcat transactions tutorial 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
Posted by rigazilla on 2017-03-17
Tags: c++ example quick start remote events
back to top