# MrSuiChuan/data-warehouse-learning

【2026最新版】 大数据 数据分析 电商系统 实时数仓 离线数仓 数据湖 建设方案及实战代码，涉及组件 #flink #paimon #doris #seatunnel #dolphinscheduler #datart #dinky #hudi #iceberg。

Repository: https://github.com/MrSuiChuan/data-warehouse-learning
Canonical: https://ross.abutalabs.com/products/data-warehouse-learning
Language: Java
License: Artistic-2.0
License Family: other
Topics: datart, dinky, dolphinscheduler, doris, flink, hudi, iceberg, paimon, seatunnel
Last push: 2026-04-26T04:21:27+00:00

## Health v2 (maintenance only)
Score: 61/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 79, release rhythm 35, longevity 65
- inputs: {"age_days": 914, "days_push": 129, "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 1218, forks 221 (observed 2026-08-28T04:04:01.556460+00:00)

## What it is
A Chinese-language educational project teaching real-time and offline data warehouse construction for an e-commerce system, with hands-on code using Flink, Doris, Paimon, Hudi, Iceberg, SeaTunnel, DolphinScheduler, Dinky, and Datart. It covers the full ODS→DWD/DIM→DWS→ADS layered architecture with both batch and streaming pipelines.

## Use cases
- learn to build a real-time data warehouse with flink and doris
- ecommerce data warehouse tutorial with example code
- compare paimon hudi and iceberg for data lakehouse
- practice offline data warehouse layering ods dwd dws ads
- learn seatunnel and dolphinscheduler for data sync and scheduling
- big data analytics project for portfolio
- build streaming etl pipelines with flinksql cdc

## When to choose
- you want a complete end-to-end data warehouse project with runnable code
- you are learning modern Chinese big-data stack components like Doris, Paimon, and Dinky
- you need reference implementations of both real-time and offline warehouse patterns on the same business logic

## When to avoid
- you need production-ready warehouse code for your own business
- you want a maintained library or framework rather than a tutorial project
- you do not read Chinese documentation

## Facets
- artifact type: learning-resource
- maturity: active
- function: etl, streaming, database, data-visualization, workflow-automation
- domain: big-data, analytics, e-commerce, tutorials
- platform: jvm, cloud
- tags: data-warehouse, real-time-data-warehouse, offline-data-warehouse, data-lake, flink, doris, paimon, hudi, iceberg, seatunnel, dolphinscheduler, dinky, datart, superset, kafka, mysql, ecommerce-analytics, chinese, data-engineering, docker, linux

## Member repositories
- MrSuiChuan/data-warehouse-learning (main) score 61

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:01.556460+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 2026-08-30T06:17:01.930594+00:00, confidence not recorded.
  - readme: https://github.com/MrSuiChuan/data-warehouse-learning (fetched 2026-08-28T04:04:01.556460+00:00, sha 8df71caa1b66)
- Data as of 2026-08-30T08:39:29.467469+00:00.