Author: Zen and the Art of Computer Programming
1 Introduction
With the development of Internet companies, the need to collect, store and process massive amounts of data is becoming more and more urgent. However, relying solely on big data technology cannot solve the current challenges, such as the pressure of business development brought about by the rapid growth of data, the impact of continuous improvement of data quality on business, and the participation of multiple parties in data analysis to generate value. These all need to be iterated quickly at the moment At the same time, adjust the data management strategy in line with the changes in the industry. Data incremental update technology is becoming one of the effective ways to solve the above challenges. Data incremental update refers to updating historical data to obtain the latest and more comprehensive information and enhance the effect of data analysis and mining. Although great progress has been made in the fields of data analysis and mining in recent years, due to the huge amount of data, the complexity of processing and the limitation of distributed computing scale, the traditional incremental data update method is inefficient. Therefore, the industry proposes a distributed data processing framework based on the cloud platform. By integrating data from different periods of time, the method of incrementally updating data is widely adopted. However, there are still many challenges in the data processing framework of the cloud platform, such as high latency, poor disaster tolerance, and lack of model training. To solve the challenges in actual scenarios, this article will introduce how to use the Kubernetes platform to deploy a high-performance distributed data processing framework Flink CDC (Change Data Capture). Flink CDC is a distributed framework developed based on the distributed data flow engine Apache Flink. It can read and integrate incremental data in real time by monitoring the data change logs of the MySQL database, and supports incremental data output in various forms, including Kafka. , HBase, ClickHouse, etc. This article will elaborate on the concepts, principles and applications of data incremental update technology, Flink CDC, and Kubernetes from the following aspects.
2. Explanation of basic concepts and terms
2.1 Data incremental update
Data incremental update refers to updating historical data to obtain the latest and more comprehensive information and enhance the effect of data analysis and mining. its