geekyouth/SZT-bigdata

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

2475 stars · 613 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A big data passenger flow analysis system for the Shenzhen Metro, built on Shenzhen Tong smart-card swipe data. It demonstrates ETL and analytics pipelines using Flink, Spark, Kafka, Hadoop, Hive, HBase, Elasticsearch, ClickHouse, Redis, and related CDH components.

Use cases

• analyze metro passenger flow from smart card data
• learn big data ETL pipelines with flink and spark
• practice hadoop hive hbase elasticsearch integration
• build realtime streaming analytics with kafka and flink
• study big data technology stack comparison and selection
• process transit card swipe data at scale

When to choose

• you want a realistic end-to-end big data learning project covering many popular frameworks
• you need reference code for ETL from kafka/redis into hbase, elasticsearch, hive, or clickhouse
• you are exploring transit or passenger flow analytics

When to avoid

• you need a production-ready transit analytics product with support
• you want a minimal stack rather than a deliberately broad multi-framework demo
• you require a permissive license for commercial use (license is non-standard)

Facets

application · maturity maintenance

etl streaming data-science analytics search-engine caching database message-queue data-visualization big-data analytics developer-tools tutorials jvm cloud self-hosted big-data flink spark hadoop clickhouse elasticsearch hbase hive kafka smart-card-data transit-analytics learning-project scala cdh data-engineering transportation docker linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="geekyouth/SZT-bigdata")