# chrislusf/glow

Glow is an easy-to-use distributed computation system written in Go, similar to Hadoop Map Reduce, Spark, Flink, Storm, etc. I am also working on another similar pure Go system, https://github.com/chrislusf/gleam , which is more flexible and more performant.

Repository: https://github.com/chrislusf/glow
Canonical: https://ross.abutalabs.com/products/chrislusf-glow
Language: Go
License Family: other
Last push: 2018-11-02T06:09:14+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4099, "days_push": 2861, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3218, forks 248 (observed 2026-08-28T04:07:49.651417+00:00)

## What it is
Glow is a pure-Go distributed computation library providing MapReduce-style flow APIs (Map, Filter, Reduce) that can run in parallel on a single machine or across a cluster of agents coordinated by a master. It is the predecessor to the author's more performant Gleam system.

## Use cases
- run mapreduce jobs in go
- parallelize data processing across cpu cores
- build a lightweight distributed compute cluster without hadoop
- process large text files in parallel
- run data pipelines across multiple machines
- word count style batch processing in go

## When to choose
- you want a simple, single-binary MapReduce system in pure Go without Zookeeper/HDFS/YARN dependencies
- you need easy parallelism on one machine using goroutines
- you prefer a lightweight flow API over Spark's JVM stack

## When to avoid
- you need a mature, actively developed big-data framework - the author recommends Gleam instead
- you need the Spark/Flink ecosystem features like SQL, streaming windows, or rich connectors
- you require long-term support - the last release was in 2018

## Facets
- artifact type: library
- maturity: maintenance
- function: etl, streaming, concurrency, data-science
- domain: microservices, big-data, developer-tools
- platform: go, windows, cross-platform
- tags: map-reduce, dataflow, dag, cluster-computing, parallel-processing, spark-alternative, data-engineering, linux, macos

## Member repositories
- chrislusf/glow (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:49.651417+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 2026-08-29T18:44:54.118688+00:00, confidence not recorded.
  - readme: https://github.com/chrislusf/glow (fetched 2026-08-28T04:07:49.651417+00:00, sha dfa97658c0bd)
- Data as of 2026-08-30T08:39:29.467469+00:00.