Part 2 of this 5-part series explains how to realize Flink MongoDB CDC Connector through MongoDB Change Streams features based on Flink CDC.
Part 1 of this 5-part series explains how to use Flink CDC to simplify the entry of real-time data into the database.
This article is compiled from the topic "Exploration of Advanced Functions in Pravega Flink Connector Table API," shared by Zhou Yumin in Flink Forward Asia 2021.
Mowen discusses the future of Apache Flink regarding its core capabilities of stream computing and improving the processing standards of the entire industry.
This article discusses the new partnership between OpenYurt and eKuiper.
This article introduces the research and development background and the design and use of Flink Remote Shuffle.
This tutorial explains how to quickly build streaming ETL for MySQL and Postgres with Flink CDC.
This article explains thoroughly how iQiyi (a Chinese online video platform) utilizes Apache Flink.
This article offers helpful tips for large-scale real-time data warehouse construction.
This article explains how to write real-time streaming data based on BinLog, Flink, and Spark Streaming into MaxCompute.
This article introduces the real-time data warehouse architecture built by Kwai based on Flink and offers solutions to some difficult problems.
In this article, Alibaba technical expert Aohai introduces the basic concepts and architecture of an enterprise-level recommender system.
This article describes Alibaba's Blink real-time stream computing technology, which is used to implement real-time product selection
Read on to learn how Alibaba's Risk Control Brain works in big data applications.
Alibaba Blink is a real-time computing framework built based on Apache's Flink, aimed at simplifying the complexity of real-time computing on Alibaba's ecosystem.
This article is an overview of the best practices for Flink on Zeppelin stream computing processing taken from a recent lecture.
This article introduces a PyFlink development environment tool that can help users solve various problems.
This article introduces the optimization and evolution of Flink Hudi's original mini-batch-based incremental computing model through stream computing.
This article gives a detailed interpretation of Flink Connector from the four aspects: connectors, Source API, Sink API, and the future development of collectors.
This article describes how Flink SQL connects to external systems and introduces commonly used Flink SQL Connectors.
