Big Data

Flink实时数据计算引入大模型 Introducing Large Models into Flink Real-Time Data Processing

2025-08-12 18:00:00

使用代码测试通过在Flink数据清洗中引入大模型，能够借助外部能力进一步完成复杂的功能 Using code to test the integration of large models into Flink data cleansing, enabling the use of external capabilities to accomplish more complex tasks.

Flink Fluss的概念和测试 Concepts and Testing of Flink Fluss

2025-08-08 00:00:00

Flink Fluss是一个正在孵化中的专为实时分析打造的流式存储系统，本文介绍其概念并进行简单使用和测试 Flink Fluss is an incubating streaming storage system purpose-built for real-time analytics. This article introduces its core concepts and demonstrates a basic usage and testing scenario.

利用Docker部署大数据环境 Deploying a Real-Time Lakehouse Big Data Environment Using Docker

2025-03-02 15:00:00

使用Docker搭建HDFS+Flink+Paimon流批一体环境，进行数据查询，并加入StarRocks查询 Using Docker to Set Up an HDFS + Flink + Paimon Unified Streaming and Batch Environment for Data Querying, Adding StarRocks For Data Querying

大数据组件整理与总结 Organizing and Summarizing Big Data Components

2024-11-06 14:00:00

整理与总结目前了解到的大数据生态下的各类组件，进行生态位的划分和优缺点对比 This involves organizing and summarizing the various components within the big data ecosystem that are currently understood, categorizing them by their niches, and comparing their strengths and weaknesses.

Java&FlinkML实现在线线性回归 OnlineLinear Regression Implementation in Java and FlinkML

2024-09-24 16:00:00

Java和FlinkML线性回归的梯度下降实现，并自己实现一个支持在线学习的模型 Implementation of gradient descent in Java and FlinkML linear regression, along with a self-implemented model that supports online learning.

FlinkML实时流数据机器学习 FlinkML Real-time Stream Data Machine Learning

2024-09-20 16:00:00

通过FlinkML可实现”实时大数据+机器学习“的结合，本节给出一个实时流数据机器学习的例子 FlinkML enables the combination of "real-time big data + machine learning." This section provides an example of real-time stream data machine learning.