jpy211987605-cmd/finance-realtime-analysis

This project is a real-time big data platform for tracking financial market prices, specifically gold, silver, crude oil, and copper. It is built to collect price data as it comes in, move it through a pipeline, store it, run calculations on it, and then display the results visually, all in close to real time rather than as an occasional batch report. The README lays out the technical pieces that make this work, though it does not go into how they connect or how to run the project yourself. Kafka handles collecting the incoming data and passing messages between the different parts of the system. PySpark does the real-time stream processing, meaning it performs calculations on the data as it flows through rather than waiting for it to be fully collected first. Hadoop HDFS provides distributed storage, spreading the stored data across multiple machines. Hive is used for offline analysis of a data warehouse built from the historical data. Elasticsearch handles real-time search over the data. FastAPI serves as the backend, providing the interface other parts of the system use to request data. A Vue and HTML based dashboard displays the results as charts or visualizations for a person to look at. The project is organized into a handful of top level folders: backend, consumer, frontend, config, deploy, dataBase, and docs, matching a typical layout for a system with a separate data pipeline, a backend service, and a frontend dashboard. The README itself is short. It does not include setup instructions, usage examples, a license, or details on how the components are wired together, so this description covers only what the README states about the project's purpose and its technology choices.