# apache/hadoop

Apache Hadoop

Repository: https://github.com/apache/hadoop
Canonical: https://ross.abutalabs.com/products/hadoop
Homepage: https://hadoop.apache.org/
Language: Java
License: Apache-2.0
License Family: permissive
Topics: hadoop
Last push: 2026-08-26T13:23:44+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 4388, "days_push": 7, "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 15640, forks 9242 (observed 2026-08-28T04:11:13.175707+00:00)

## What it is
Apache Hadoop is an open-source framework for reliable, scalable distributed storage (HDFS) and processing (MapReduce, YARN) of large data sets across clusters of commodity computers. It scales from single servers to thousands of machines and handles failures at the application layer.

## Use cases
- store and process petabytes of data across a cluster
- run batch MapReduce jobs on large datasets
- set up a distributed file system for a data lake
- schedule and manage cluster compute resources with YARN
- build an on-premises big data platform
- run data pipelines over cloud object storage like S3

## When to choose
- you need proven, battle-tested distributed storage and batch processing at scale
- you want a mature ecosystem with HDFS, YARN, and MapReduce under one project
- you need fault-tolerant processing on commodity hardware without external orchestration

## When to avoid
- you only need lightweight analytics that Spark, DuckDB, or a cloud warehouse handles more simply
- you want real-time low-latency stream processing as the primary workload
- you cannot operate the operational overhead of a JVM-based cluster

## Facets
- artifact type: framework
- maturity: stable
- function: etl, streaming, file-system, database, scheduling, developer-tools
- domain: big-data, microservices, analytics
- platform: jvm, cross-platform, cloud
- tags: hdfs, mapreduce, yarn, distributed-computing, data-lake, cluster-computing, apache, data-engineering, linux, docker

## Member repositories
- apache/hadoop (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:13.175707+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 2026-08-29T17:05:37.039004+00:00, confidence not recorded.
  - readme: https://github.com/apache/hadoop (fetched 2026-08-28T04:11:13.175707+00:00, sha 6a78426199ee)
  - homepage: https://hadoop.apache.org/ (fetched 2026-08-29T08:03:43.716848+00:00, sha 779c8edb7a6d)
  - site_page: https://hadoop.apache.org/docs/current (fetched 2026-08-29T08:03:43.727930+00:00, sha 898b19a79e74)
  - site_page: https://hadoop.apache.org/docs/stable (fetched 2026-08-29T08:03:43.730101+00:00, sha 8082b1e189ec)
  - site_page: https://hadoop.apache.org/docs/r3.5.0 (fetched 2026-08-29T08:03:43.731955+00:00, sha a2f4f60f9c27)
  - site_page: https://hadoop.apache.org/docs/r3.4.3 (fetched 2026-08-29T08:03:43.733679+00:00, sha 08419c3da6a3)
  - site_page: https://hadoop.apache.org/docs/r3.4.2 (fetched 2026-08-29T08:03:43.735476+00:00, sha e97c15e79920)
  - site_page: https://hadoop.apache.org/docs/r3.4.1 (fetched 2026-08-29T08:03:43.737163+00:00, sha eac39198c299)
  - site_page: https://hadoop.apache.org/docs/r3.4.0 (fetched 2026-08-29T08:03:43.738977+00:00, sha 214c6e64a180)
  - site_page: https://hadoop.apache.org/releases.html (fetched 2026-08-29T08:03:43.726027+00:00, sha 87f8d3e6025b)
- Data as of 2026-08-30T08:39:29.467469+00:00.