In this blog, two experts from Alibaba Cloud talk about the advantages that data warehouses and data lakes bring to handle large, complex architecture for businesses.
This article demonstrates how to use Flink SQL to integrate Kafka, MySQL, Elasticsearch, and Kibana to quickly build a real-time analysis application.
This article will introduce PyFlink's architecture and provide a quick demo in which PyFlink is used to analyze CDN logs.
This blog compares the performance of Flink 1.10 against Hive 3.0 using the TPC-DS Benchmark 10-TB dataset and 20 hosts to test 3 engines.
This article evaluates different duplicate data cleansing techniques while considering several technical database issues in PostgreSQL.
Read on to learn how Alibaba's Risk Control Brain works in big data applications.
This post takes a deep dive on how Taobao Mobile's recommendation system was developed from the ground up.
This article discusses what are some structured data storage requirements and presents the design used by Alibaba Cloud Tablestore to meet these requirements.
This article describes the basics of Flink state management, different state types and its use cases.
This article discusses three main parts: what is Table API, how to use Table API from a code perspective, and the latest information about the Table API.
This article shares five methods on how to submit tasks in Flink, helping you improve development skills and enhance operations and maintenance efficiency.
This article imparts knowledge to new Flink users or those who have a basic understanding of Flink, focusing on its various configuration steps and guidelines for development and debugging.
This post describes the status quo of Flink's application in the monitoring system, focusing on its impacts on eBay's monitoring system, Sherlock.IO.
This article introduces the history of Apache Flink Python API, and discusses its architecture, development environment, and key operators.
This article describes the core mechanism of running jobs in Flink Runtime. It provides an overview of the Flink Runtime architecture and basic job running process.
This article reviews the basics of distributed stream processing and explores the development of Flink with DataStream API through an example.
This article is part of the Basic Apache Flink Tutorial series, focusing on Flink SQL programming practices using five examples.
This article includes the code that I demonstrated in my speech, entitled Flink SQL 1.9.0 Technologies and Best Practices, which sparked a lot of interest from the audience.
This article describes the development path, construction methods, and architecture of a data warehouse, and compares between real-time and offline data warehouses.
This article describes Flink connectors focusing on the basic working mechanism and usage of Kafka connectors commonly used in production.
