# javahongxi/whatsmars

Java生态研究(Spring Boot + Redis + Dubbo + RocketMQ + Elasticsearch)🔥🔥🔥🔥🔥

Repository: https://github.com/javahongxi/whatsmars
Canonical: https://ross.abutalabs.com/products/whatsmars
Homepage: https://blog.csdn.net/javahongxi
Language: Java
License: Apache-2.0
License Family: permissive
Topics: java, dubbo, redis, rocketmq, zookeeper, spring, spring-boot, spring-mvc, rpc, elastic-job, sharding-jdbc, microservices, elasticsearch, kafka, sentinel, grpc, nacos, spring-ai, netty, langchain4j
Last push: 2026-08-24T18:06:46+00:00

## Health v2 (maintenance only)
Score: 96/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 91, longevity 100
- inputs: {"age_days": 3806, "days_push": 9, "days_rel": 60, "gap_med": 13.0, "n_releases_24m": 3}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1967, forks 603 (observed 2026-08-28T04:06:00.014117+00:00)

## What it is
A curated collection of Java ecosystem study modules and runnable samples covering Spring Boot, Redis, Dubbo, RocketMQ, Kafka, Elasticsearch, Netty, ZooKeeper, and related middleware, plus newer Java x AI modules (LangChain4j, MCP Server). It serves as a hands-on reference for learning distributed systems and microservice technologies in Java.

## Use cases
- learn spring boot with runnable examples
- study dubbo rpc and microservices architecture
- understand rocketmq and kafka messaging patterns
- explore redis caching and distributed locks
- practice elasticsearch client usage
- learn netty nio programming
- try langchain4j and mcp server in java
- reference for sharding and distributed scheduling

## When to choose
- you want curated, working sample code for mainstream Java middleware
- you are studying distributed systems concepts like RPC, message queues, and caching
- you need reference examples for Spring Boot 3.x and Java 17+
- you want to explore Java AI engineering with LangChain4j and MCP

## When to avoid
- you need a production-ready framework or library to depend on
- you want a single cohesive application rather than independent demo modules
- you work outside the JVM ecosystem

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools, rpc, caching, message-queue, search-engine, mcp, agent-framework, llm-inference
- domain: developer-tools, microservices, large-language-models, databases, tutorials
- platform: jvm, cross-platform
- tags: java-ecosystem, spring-boot, dubbo, rocketmq, elasticsearch, redis, netty, zookeeper, nacos, sentinel, shardingsphere, kafka, grpc, langchain4j, sample-code, microservices-architecture, search, messaging

## Member repositories
- javahongxi/whatsmars (main) score 96

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:00.014117+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 2026-08-30T03:05:13.605409+00:00, confidence not recorded.
  - readme: https://github.com/javahongxi/whatsmars (fetched 2026-08-28T04:06:00.014117+00:00, sha 3970ea5f83c7)
  - homepage: https://blog.csdn.net/javahongxi (fetched 2026-08-29T10:44:53.212898+00:00, sha bc0ba371fe22)
- Data as of 2026-08-30T08:39:29.467469+00:00.