Ross ROSS = Recommend OSS · open-source software intelligence for agents

killrweather/killrweather

KillrWeather is a reference application (work in progress) showing how to easily integrate streaming and batch data processing with Apache Spark Streaming, Apache Cassandra, Apache Kafka and Akka for fast, streaming computations on time series data in asynchronous event-driven environments. observed · 2026-08-28

github.com/killrweather/killrweather · Scala · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 4348
  • days_rel: n/a
  • days_push: 3527
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1178 stars · 391 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

KillrWeather is a Scala reference application demonstrating integration of Apache Spark Streaming, Apache Kafka, Apache Cassandra, and Akka for fast streaming and batch computations on time series data. It serves as an example architecture for asynchronous, event-driven big data processing.

Use cases

  • process streaming time series data with spark kafka and cassandra
  • learn how to integrate spark streaming with cassandra and akka
  • build an event-driven streaming analytics pipeline
  • run real-time computations on high-velocity time series data
  • reference architecture for lambda-style streaming and batch processing
  • query historical time series data for predictive modeling

When to choose

  • you want a worked example of Spark Streaming, Kafka, and Cassandra working together
  • you need a reference design for time series data models in Cassandra
  • you are learning Akka-based event-driven streaming architectures on the JVM

When to avoid

  • you need a production-ready, actively maintained streaming framework
  • you are not working on the JVM with Scala
  • you need up-to-date compatibility with current Spark, Kafka, or Cassandra versions

Facets

application · maturity abandoned

streaming etl data-science database message-queue big-data time-series microservices jvm apache-spark apache-kafka apache-cassandra akka time-series reference-application stream-processing data-engineering linux macos docker

1 source

Member repositories

RepositoryRoleHealth v2
killrweather/killrweathermain32

For agents

markdown · JSON · MCP: product_card(name="killrweather/killrweather")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem