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Kafka Stream Processing library for Node

A Node.js interpretation of the Kafka Streams Processor API.

Frolyk provides a minimal layer over Kafka, to effectively write, test and run stream processing applications. It follows a task based concept, where sources (kafka topics) flow through user-defined processors to generate results, either back to Kafka or some other store. It aims to enable both stateless and stateful processing, leveraging Kafka ConsumerGroups to spread these tasks between workers.

import createTask from "../src/task";

const task = createTask();

const locationEvents = task.source("location-events");

task.processor(locationEvents, async (assignment) => {
  // Called when Consumer receives assignment through a rebalance, or manual assignment.__dirname

  // Do any setup work here.

  const countsPerTimeWindow = {}; // connect to Postgres? Fetch a store from somewhere else for local use?

  return async (message, context) => {
    const location = parseLocation(message.value);

    const win = getWindow(location.timestamp);

    const existingCount = countsPerTimeWindow[win] || 0;
    const newCount = existingCount + 1;

    countsPerTimeWindow[win] = newCount;

    // Process a single message
    context.send("location-counts", newCount);
    context.commit();
  };
});

// either start processing by connecting to Kafka
await task.start();

// or inject test messages into the processor to verify your logic
const testInterface = await task.inject([
  { topic: "location-events", partition: 0 },
]);

const testLocation = {
  latitude: 4,
  longitude: 10,
  timestamp: Date.now(),
};
testInterface.inject({
  topic: "location-events",
  partition: 0,
  key: null,
  testLocation,
});

console.log(testInterface.committedMessages); // should contain offset of message

Initial goals

  • Kafka Stream Processor API for Node.js
  • Task construct to describe processor topologies and processing logic
  • Testing of processing logic without requiring a Kafka Cluster
  • Propagation of errors
  • Simple logging
  • Very few dependencies: KafkaJS, Long?, Highland
  • Idiomatic Node, no straight up copy of Java Processor API.
  • 100% Test coverage

Later goals

  • Simple Worker / App construct to run multiple tasks in a single process
  • Basic message parsing
  • Support long-running processing jobs (> session timeout through heartbeating / pause & resume)
  • Replace Highland streams with custom Node Streams
  • Very very few dependencies: KafkaJS, Long?
  • Basic store support
  • Basic scheduling / windowing

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Stream processing library for Kafka in Node

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