Practice Experience of Dada Group's Real-Time Computation SQLization Using Dada Flink SQL

This article details Dada Group's development of the Dada Flink SQL engine, describing its background, architecture, parser design, dimension‑table join strategies, numerous enhancements such as HA support, Kafka keyword handling, metadata integration, Redis and ClickHouse sinks, BINLOG simplification, and future migration plans toward Flink 1.10.

FlinkReal‑Time ComputingSQL Engine

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Practice Experience of Dada Group's Real-Time Computation SQLization Using Dada Flink SQL

dbaplus Community

Jan 6, 2020 · Big Data

How 58.com Built a Scalable Flink‑Based Real‑Time Data Platform (Wstream)

The article details how 58.com designed and evolved its one‑stop real‑time computation platform Wstream, migrating from Storm and Spark Streaming to Apache Flink, and describes the architecture, task isolation, stream‑SQL features, monitoring, and ongoing optimizations that enable processing of over 600 billion records daily.

Big DataFlinkReal-time Streaming

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How 58.com Built a Scalable Flink‑Based Real‑Time Data Platform (Wstream)

Big Data Technology & Architecture

Jul 22, 2019 · Big Data

Deep Dive into Stream SQL Principles and Incremental Query Execution in Apache Flink

This article provides an in‑depth analysis of Stream SQL theory, incremental query algorithms, materialized view maintenance, optimizer cost models, time handling, windowing, and the practical capabilities and limitations of Apache Flink’s streaming SQL engine.

Apache FlinkIncremental QuerySQL Optimization

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Deep Dive into Stream SQL Principles and Incremental Query Execution in Apache Flink