kandi X-RAY | hazelcast-jet Summary
kandi X-RAY | hazelcast-jet Summary
Jet is an open-source, in-memory, distributed batch and stream processing engine. You can use it to process large volumes of real-time events or huge batches of static datasets. To give a sense of scale, a single node of Jet has been proven to aggregate 10 million events per second with latency under 10 milliseconds. It provides a Java API to build stream and batch processing applications through the use of a dataflow programming model. After you deploy your application to a Jet cluster, Jet will automatically use all the computational resources on the cluster to run your application. If you add more nodes to the cluster while your application is running, Jet automatically scales up your application to run on the new nodes. If you remove nodes from the cluster, it scales it down seamlessly without losing the current computational state, providing exactly-once processing guarantees.
Top functions reviewed by kandi - BETA
- Creates a generic record from a class definition .
- Handles snapshot phase 1 .
- Creates an aggregate operation .
- State check for non - whitespace characters .
- Initialize this instance .
- Submits a job to the coordinator thread .
- Resolves the class definition .
- Configures the Jetty service .
- Finalize a job .
- Offers an item to the outbox .
hazelcast-jet Key Features
hazelcast-jet Examples and Code Snippets
Trending Discussions on hazelcast-jet
Getting this error for "mvn clean validate". Is this issue the same as https://github.com/googleapis/java-storage/issues/133? Can someone please help to resolve this? I haven't changed pom.xml....
ANSWERAnswered 2021-Jun-01 at 10:41
You either need to disable the dependencyConvergence check in the POM, or you need to add an entry to the
section of your POM which contains the version of
error_prone_annotations that you want to use.
I want to use hazelcast-jet-kafka in my app, because in my case the number of kafka partitions is limited. How I understand jet-kafka parallelism doesn't depend on kafka partitions, it would be nice to find explanations of how jet-kafka achieve independence of the number of kafka partitions.
But my question is how I can handle events in jet when my event handler could not be serializable. For example, I've found a solution - use map sink and add local event listener to this map, but for me, it seems like a crutch, because I don't need to store these events in map. It is possible to set map size to zero in such scheme?
Also, I see in docs new type of sink - observable, it seems what I want, but observable listener could not get only local entries and for me, it is not suitable.
Could you help find the right solution? Or hazelcast-jet-kafka is not a good choice in that case?...
ANSWERAnswered 2020-Nov-22 at 13:33
it would be nice to find explanations of how jet-kafka achieve independence of the number of kafka partitions.
One Jet thread can handle any number of partitions, so it's easy to achieve this independence. Jet just distributes all the partitions fairly among all the Kafka connector threads.
But my question is how I can handle events in jet when my event handler could not be serializable.
Hazelcast Jet doesn't require your event handler to be serializable. If you need a stateful handler, you have to supply a function that creates the state object. The function must be serializable, but the state doesn't have to be. If you just want a stateless mapping function, it must be serializable, but usually there's no problem with that.
If you are getting an error that says a function is non-serializable, this can be due to a common pitfall of capturing more state than you actually need in the lambda. You should show your code in that case.
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