This article is compiled from the presentation by Xu Yu, an internet big data expert at vivo and Apache Paimon Committer, during the Flink Forward Asia 2024 Streaming Lakehouse session (Part One).
This article introduces Flink SQL, a unified stream-batch processing engine, focusing on key concepts like Stream-Table Duality, event time/watermarks.
Apache Flink is a stream processing framework with two main interfaces: Flink SQL, which uses SQL for batch and streaming data, and the DataStream API...
This article is based on a presentation by Mr. Wang Feng (nickname: Mowen), senior director at Alibaba Cloud and head of the open source big data de.
This is Technical Insights Series by Perry Ma | Product Lead, Real-time Compute for Apache Flink at Alibaba Cloud.
This article introduces the upgrades and optimizations made to the batch processing model in RocketMQ.
This article introduces the Big Data Cloud Fighters bootcamp, which provides an intensive, hands-on experience in mastering big data principles and technologies.
This article introduces the process of building an all-in-one real-time data warehouse using AnalyticDB for PostgreSQL at the code level.
Unified batch and stream processing of Flink is a well-established concept in the stream computing field.
Explore the differences between Batch Processing vs Stream Processing and their applications in data management for better decision-making.
Uncover the advancements from Apache Hive to Hudi and Iceberg in stream computing, as our expert navigates the transformative landscape of real-time data lakes.
This article is based on a keynote speech given by WANG Feng, initiator of Apache Flink Community China and head of Open-Source Big Data Platform at Alibaba Cloud, at Flink Forward Asia 2023.
Ready to dive into real-time data processing? Learn Apache Flink basics & set up with Alibaba Cloud's Realtime Compute for Apache Flink.
Learn about stream processing, its applications, challenges, and Alibaba Cloud's Realtime Compute for Apache Flink solution for real-time data analysis.
Batch processing is a method of handling data where transactions are collected over a period and processed together as a group, or batch.
The Apache Flink PMC is pleased to announce the release of Apache Flink 1.18.0. As usual, we are looking at a packed release with a wide variety of improvements and new features.
Part 27 of this series discusses distributed systems in terms of throughput and latency.
Apache Flink, a leading stream processing standard, has released version 1.17.0, which includes new features and improvements.
The Apache Flink community has released version 0.3.0 of the Flink Table Store, which includes many new features and improvements.
Mowen discusses the future of Apache Flink regarding its core capabilities of stream computing and improving the processing standards of the entire industry.
