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fscrawler

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Elasticsearch 文件系统爬虫 (FS Crawler)

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工具介绍

Elasticsearch 文件系统爬虫 (FS Crawler)

File System Crawler for Elasticsearch

Welcome to FSCrawler for Elasticsearch

This crawler helps to index binary documents such as PDF, Open Office, MS Office.

Main features:

  • Local file system (or a mounted drive) crawling and index new files, update existing ones and removes old ones.
  • Remote file system over SSH/FTP crawling.
  • REST interface to let you "upload" your binary documents to elasticsearch.

Latest versions

Current versions are:

Elasticsearch FSCrawler Released Docs 6.x, 7.x 2.9 2022-03-08 2.9 7.x, 8.x, 9.x 3.0 2026-08-26 3.0 8.x, 9.x 3.1-SNAPSHOT 3.1-SNAPSHOT

Quick start

Run Elasticsearch with start-local:

# Start Elasticsearch and Kibana
curl -fsSL https://elastic.co/start-local | sh
# Get the generated API key (you will need it for FSCrawler)
source elastic-start-local/.env

Run FSCrawler with Docker:

docker pull dadoonet/fscrawler
docker run -it --rm \
  --add-host=host.docker.internal:host-gateway \
  -v ~/.fscrawler:/root/.fscrawler \
  -v $(pwd)/resumes:/tmp/es:ro \
  -e FSCRAWLER_ELASTICSEARCH_URLS=http://host.docker.internal:9200 \
  -e FSCRAWLER_ELASTICSEARCH_API_KEY="${ES_LOCAL_API_KEY}" \
  -e FS_JAVA_OPTS="-DLOG_LEVEL=debug" \
  dadoonet/fscrawler

Then open Kibana and watch for your documents coming to the fscrawler alias:

FROM fscrawler 
| STATS numDocs = COUNT(*)

Or search for some text:

FROM fscrawler
| WHERE content : "David"

Or count by file.content_type:

FROM fscrawler 
| STATS numDocs = COUNT(*) BY file.content_type

Note:

  • ~/resumes contains the documents you want to index
  • Job settings will be stored in ~/.fscrawler/fscrawler/_settings.yaml

Read the documentation for more details and specifically the tutorial page.

Need help writing your job settings? Copy a ready-made prompt from the LLM assistant guide into ChatGPT, Claude, or your favorite AI assistant.

FSCrawler also publishes an llms.txt index (mirrored in the repo) and clean Markdown versions of every docs page (*.html.md) so agents can skip HTML chrome — see the llms.txt v2 proposal.

Project information

Stats

Version in preparation

To test this SNAPSHOT with Docker, use the snapshot tag. Untagged dadoonet/fscrawler (or :latest) is the last stable release:

docker pull dadoonet/fscrawler:snapshot

For Docker Compose, set FSCRAWLER_VERSION=snapshot in .env. Use snapshot-noocr if you do not need OCR. The ZIP is published as a GitHub pre-release on every push to main.

Latest release

Build & quality

License

Read more about the Apache2 License.

Thanks

Thanks to JetBrains for the IntelliJ IDEA License! The best IDE out there!

Thanks to SonarCloud for the free analysis! You guys rock!

GitHub Issues· 85 开放

在 GitHub 查看全部
  • #2543

    File not deleted from elasticsearch

    check_for_bug更新于 2026年9月10日
  • #2530

    remove_deleted only reconciles the first 10,000 files in a directory + Orphan files

    check_for_bug更新于 2026年8月31日
  • #66

    support for child doc types

    feature_request更新于 2026年8月27日
  • #1824

    Add/document Support for OpenSearch

    feature_request更新于 2026年8月27日
  • #794

    Use External API for OCR ie amazon textract or google vision

    feature_requestcomponent:extractor更新于 2026年8月7日
  • #2475

    Add an ElasticsearchPasswordProvider

    feature_request更新于 2026年7月23日
  • #2255

    Generate a thumbnail version of the document

    feature_request更新于 2026年7月20日
  • #341

    Submit job settings via REST api

    new更新于 2026年7月17日
  • #1258

    Do not extract ALL raw metadata

    feature_requestcomponent:core更新于 2026年7月7日
  • #987

    fscrawler statistics in a monitoring stack

    feature_requestcomponent:restcomponent:monitoring更新于 2026年3月13日

核心特点

  • •Local file system (or a mounted drive) crawling and index new files, update existing ones and removes old ones.
  • •Remote file system over SSH/FTP crawling.
  • •REST interface to let you "upload" your binary documents to elasticsearch.
  • •~/resumes contains the documents you want to index
  • •Job settings will be stored in ~/.fscrawler/fscrawler/_settings.yaml

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> 工具信息

发布日期2026年8月1日
最后更新2026年9月17日
分类数据库
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