harshini-raja/kafka-inspired-distributedmessagequeue

Purpose and Entry Points

A Kafka-inspired distributed message queue with a Java/Maven backend and React monitoring dashboard. The backend starts from src/main/java/com/distributedQueue/MainClass.java; the browser app starts at DistributedMessageQueue/src/index.js and composes its UI in DistributedMessageQueue/src/App.js. Deployment is container-oriented through Docker-compose.yml.

Core Queue Domain

The queue model is organized around topics, partitions, messages, and in-memory/message-queue coordination. src/main/java/com/distributedQueue/Core/TopicManager.java owns topic-level management, while src/main/java/com/distributedQueue/Core/Topic.java and src/main/java/com/distributedQueue/Core/Partition.java represent routing/storage boundaries. src/main/java/com/distributedQueue/Core/Message.java defines the message payload model and src/main/java/com/distributedQueue/Core/MessageQueue.java coordinates queue behavior.

Controller and REST Boundary

src/main/java/com/distributedQueue/Controllers/Controller.java is the backend control/API boundary used to expose queue operations and operational state. JSON-facing type conversion is separated in src/main/java/com/distributedQueue/Adapters/MessageAdapter.java and src/main/java/com/distributedQueue/Adapters/InstantTypeAdapter.java, insulating core models from wire serialization concerns.

Distributed Roles and Message Flow

Producers publish messages through src/main/java/com/distributedQueue/Producers/Producer.java; messages are assigned to topics/partitions managed by the core layer. Brokers in src/main/java/com/distributedQueue/Brokers/Broker.java host or coordinate partition work. Consumers pull/process messages through src/main/java/com/distributedQueue/Consumers/Consumer.java, with src/main/java/com/distributedQueue/Consumers/ConsumerThread.java providing concurrent consumption execution.

Cluster Metadata and Coordination

Partition ownership/leader-related state is represented by src/main/java/com/distributedQueue/Metadata/PartitionMetadata.java. Broker-to-broker coordination is modeled in src/main/java/com/distributedQueue/Protocols/GossipProtocol.java, making metadata propagation and broker health a distinct distributed-systems boundary rather than part of producer/consumer code.

Observability and Dashboard

Operational events are captured through src/main/java/com/distributedQueue/Logging/LogMessage.java and persisted/accessed via src/main/java/com/distributedQueue/Logging/LogRepository.java. The React dashboard uses DistributedMessageQueue/src/services/Api.js for backend access and presents cluster state in DistributedMessageQueue/src/components/Dashboard.js, broker status in DistributedMessageQueue/src/components/Broker.js, topic/leader information in DistributedMessageQueue/src/components/Topics.js, and producer/consumer logs in their respective components.

Runtime and Infrastructure

The backend runs on Java with Maven (pom.xml); the frontend is a separate Node/React package (DistributedMessageQueue/package.json) using Axios. Docker defines separate controller, broker, producer, and consumer images in Dockerfile.controller, Dockerfile.broker, Dockerfile.producer, and Dockerfile.consumer, orchestrated by Docker-compose.yml. This indicates the distributed roles are intended to run as independently containerized processes.