# medcl/elasticsearch-rtf

elasticsearch中文发行版，针对中文集成了相关插件，方便新手学习测试.

Repository: https://github.com/medcl/elasticsearch-rtf
Canonical: https://ross.abutalabs.com/products/elasticsearch-rtf
Language: JavaScript
License: Apache-2.0
License Family: permissive
Archived: true
Last push: 2018-04-02T02:16:55+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 5201, "days_push": 3076, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2647, forks 702 (observed 2026-08-28T04:07:06.792119+00:00)

## What it is
Elasticsearch-RTF is a ready-to-fly Chinese distribution of Elasticsearch bundling pre-tested plugins such as the IK Chinese analyzer, so beginners can download and run it immediately. It packages a stable Elasticsearch release with analysis, ingest, discovery, and repository plugins pre-installed.

## Use cases
- set up elasticsearch with chinese tokenization quickly
- learn and test elasticsearch as a beginner
- run a preconfigured full-text search engine for chinese text
- try elasticsearch plugins without manual installation
- evaluate ik analyzer for chinese word segmentation

## When to choose
- you want a zero-setup elasticsearch with chinese analysis plugins for learning or testing
- you are new to elasticsearch and want a working instance out of the box

## When to avoid
- you need a current or production-supported elasticsearch version (last release 2018, based on ES 5.1.1)
- you want a minimal custom cluster - install official elasticsearch and pick plugins yourself

## Facets
- artifact type: application
- maturity: abandoned
- function: search-engine, nlp, developer-tools
- domain: developer-tools
- platform: windows, jvm, cross-platform
- tags: elasticsearch, chinese, distribution, ik-analyzer, full-text-search, beginner-friendly, search, natural-language-processing, linux, macos

## Member repositories
- medcl/elasticsearch-rtf (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:06.792119+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 2026-08-30T02:18:57.432949+00:00, confidence not recorded.
  - readme: https://github.com/medcl/elasticsearch-rtf (fetched 2026-08-28T04:07:06.792119+00:00, sha ba09048e9226)
- Data as of 2026-08-30T08:39:29.467469+00:00.