# 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.

Repository: https://github.com/killrweather/killrweather
Canonical: https://ross.abutalabs.com/products/killrweather
Language: Scala
License: Apache-2.0
License Family: permissive
Last push: 2017-01-05T09:43:35+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4348, "days_push": 3527, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1178, forks 391 (observed 2026-08-28T04:03:53.013085+00:00)

## What it is
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
- artifact type: application
- maturity: abandoned
- function: streaming, etl, data-science, database, message-queue
- domain: big-data, time-series, microservices
- platform: jvm
- tags: apache-spark, apache-kafka, apache-cassandra, akka, time-series, reference-application, stream-processing, data-engineering, linux, macos, docker

## Member repositories
- killrweather/killrweather (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:53.013085+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:26:06.891910+00:00, confidence not recorded.
  - readme: https://github.com/killrweather/killrweather (fetched 2026-08-28T04:03:53.013085+00:00, sha 4b6283209629)
- Data as of 2026-08-30T08:39:29.467469+00:00.