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Apache flink

Implementing CDC to MaxCompute with Apache Flink: A Case Study

This article is based on the keynote speech delivered by Fajar Tontowi, Lead Data Engineer for Ingestion and Analytics at Mekari, at Flink Forward Asia in Jakarta 2024.

Paimon 1.0: Unified Lake Format for Data + AI

Explore how Apache Paimon addresses big data system challenges by offering a unified data lake storage solution.

Harnessing Streaming Data for AI-Driven Applications with Apache Flink

Discover how to harness streaming data for AI-driven applications using Apache Flink, based on insights from the Flink Forward Asia 2024 keynote by Ashish Sharma and Ganireddy Jyothi Swaroop.

Introducing Fluss: Streaming Storage for Real-Time Analytics

Today, we are excited to introduce Fluss, a cutting-edge streaming storage system designed to power real-time analytics.

Why Fluss? Top 4 Challenges of Using Kafka for Real-Time Analytics

Jark Wu Creator of Fluss project The industry is undergoing a clear and significant shift as big data computing transitions from offline to real-time processing.

The Past, Present, and Future of Apache Flink

This article is based on the keynote speech given by Feng Wang, Head of the Open Data Platform at Alibaba Cloud, at Flink Forward Asia in Jakarta 2024.

Alibaba Cloud Shares New Features of Apache Flink 2.0 at Flink Forward Asia

Alibaba Cloud highlighted the innovative features of the forthcoming Apache Flink 2.0 at Flink Forward Asia in Jakarta.

Flink Course Series (1): A General Introduction to Apache Flink

This article describes the basic concepts, importance, development, and current applications of Apache Flink.

Mixing Stream and Batch Processing in Apache Flink

This article is compiled from a presentation by Yunfeng Zhou, a Senior Development Engineer at Alibaba Cloud and an Apache Flink Contributor, during the Apache Asia CommunityOverCode 2024 event.

How Flink Batch Jobs Recover Progress during JobMaster Failover?

Authored by Aliyun's R&D engineer, Li Junrui, this article introduces the newly introduced feature of batch job progress resumption in Flink version 1.

Introduction to Unified Batch and Stream Processing of Apache Flink

Unified batch and stream processing of Flink is a well-established concept in the stream computing field.

Hands-on Labs | Get Started with Flink MySQL Connector in 5 Minutes

This step-by-step tutorial introduces how to get started with Flink MySQL Connector in 5 minutes.

Apache Paimon: Streaming Lakehouse is Coming

This article is based on the keynote speeches given by LI Jinsong, WU Xiangping, DI Xingxing, and WANG Yunpeng during Flink Forward Asia 2023.

Accelerated Integration: Unveiling Flink Connector's API Design and Latest Advances

This article is compiled from the presentation by Ren Qingsheng, committer and PMC member of Apache Flink, at the Flink Forward Asia 2023 core technology session (Part 2).

Data Lake for Stream Computing: The Evolution of Apache Paimon

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.

Understand Flink SQL: Real-Time SQL Query Execution for Stream and Batch Data

Discover Flink SQL, the high-level API for executing SQL queries across streaming and batch data sets in Apache Flink.

Complex Event Processing (CEP): A Comprehensive Guide

Discover the power of Complex Event Processing (CEP) in deciphering real-time cause-and-effect relationships from diverse data streams.

What is Change Data Capture (CDC)?

Change Data Capture (CDC) detects and captures data changes as they occur in source systems, such as databases or applications.

The Next Step of Flink CDC

This article is based on a keynote speech given by Jark Wu, head of Flink SQL and Flink CDC at Alibaba Cloud, during Flink Forward Asia 2023.

Flink CDC 3.0| A Next-generation Real-time Data Integration Framework

Flink CDC 3.0 is a cutting-edge framework for real-time data integration, offering an efficient, scalable CDC solution with Apache Flink.