# douban/dpark

Python clone of Spark,  a MapReduce alike framework in Python

Repository: https://github.com/douban/dpark
Canonical: https://ross.abutalabs.com/products/dpark
Language: Python
License: BSD-3-Clause
License Family: permissive
Topics: bigdata, mapreduce, dpark, stream-processing, spark, python
Archived: true
Last push: 2020-12-25T10:36:06+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 5257, "days_push": 2077, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2663, forks 518 (observed 2026-08-28T04:07:08.892375+00:00)

## What it is
DPark is a Python clone of Apache Spark, providing a MapReduce-like distributed computing framework that supports iterative computation. Jobs written with DparkContext can run locally or on a Mesos cluster without code changes.

## Use cases
- run mapreduce word count jobs in python
- process large datasets on a mesos cluster
- run iterative algorithms like pagerank in python
- batch etl over text files without learning scala spark
- debug distributed jobs via a web ui with stage graphs

## When to choose
- you want Spark-style RDD programming in pure Python
- your cluster runs Mesos and you prefer Python over Scala/Java
- you need lightweight MapReduce with iterative computation support

## When to avoid
- you need modern Spark features like DataFrames, SQL, or MLlib
- you want an actively developed project - the last release was 2020
- your infrastructure uses Kubernetes or YARN instead of Mesos

## Facets
- artifact type: framework
- maturity: maintenance
- function: etl, streaming, data-science, workflow-automation
- domain: big-data, microservices, data-science
- platform: python, cli
- tags: mapreduce, spark-clone, rdd, mesos, batch-processing, iterative-computation, data-engineering, linux

## Member repositories
- douban/dpark (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:08.892375+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 2026-08-30T02:18:20.115247+00:00, confidence not recorded.
  - readme: https://github.com/douban/dpark (fetched 2026-08-28T04:07:08.892375+00:00, sha 829601821a02)
  - registry_pypi: https://pypi.org/pypi/dpark/json (fetched 2026-08-29T10:01:02.807629+00:00, sha 3ae26260e880)
- Data as of 2026-08-30T08:39:29.467469+00:00.