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stream computing

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DataFunSummit
DataFunSummit
Jan 30, 2024 · Big Data

CVTE’s Journey of Stream Computing Adoption: Architecture, Applications, and Lessons Learned

This article details CVTE’s adoption of stream computing, describing the company background, the challenges of traditional data pipelines, the design of a CDC‑Kafka integration platform, evaluations of PipelineDB, ksqlDB, Materialize and RisingWave, and the overall impact on real‑time analytics and operational efficiency.

Big DataCVTERisingWave
0 likes · 9 min read
CVTE’s Journey of Stream Computing Adoption: Architecture, Applications, and Lessons Learned
Baidu Geek Talk
Baidu Geek Talk
Apr 6, 2022 · Big Data

Baidu Log Platform: Ensuring Data Accuracy with No-Duplication and No-Loss Architecture

Baidu’s logging platform centralizes data collection, transmission, management, and analysis for billions of daily logs, employing a layered architecture with priority persistence, service decomposition, stream computing, and client‑side optimizations to guarantee no duplication, no loss, and 99.99%+ stability.

Architecture DesignBaidudata accuracy
0 likes · 11 min read
Baidu Log Platform: Ensuring Data Accuracy with No-Duplication and No-Loss Architecture
Tencent Cloud Developer
Tencent Cloud Developer
May 21, 2021 · Big Data

Tencent Cloud Oceanus: Flink SQL Optimization and Extension Practices

Tencent Cloud Oceanus, a computing service powering internal apps like WeChat and external partners such as Bilibili, scales to over 30,000 cores handling 5 PB daily and 500,000 jobs, and tackles Flink SQL’s syntax, function and operational limits with table‑valued functions, incremental and enhanced tumble windows, and caching‑based retraction optimization that cuts downstream data volume up to 30× and improves join performance by about 20 %.

Big DataFlink SQLOceanus
0 likes · 19 min read
Tencent Cloud Oceanus: Flink SQL Optimization and Extension Practices
Xianyu Technology
Xianyu Technology
Jan 9, 2020 · Mobile Development

BehaviR: Mobile‑Side Real‑Time Stream Processing Framework

BehaviR is a mobile‑side real‑time stream processing framework that gathers page actions, network requests, and storage events via JSON configuration, runs stateful computations on a lightweight Python‑based engine using a DSL, and instantly triggers decisions and routes results with millisecond latency and no server load.

BehaviRPythonReal-time Processing
0 likes · 9 min read
BehaviR: Mobile‑Side Real‑Time Stream Processing Framework
Tencent Cloud Developer
Tencent Cloud Developer
Sep 6, 2018 · Big Data

Real-Time Stream Computing: Concepts, Challenges, and Tencent Cloud Solutions

As mobile and IoT data surge, real-time stream computing—especially Flink’s low-latency, high-throughput, exactly-once engine—addresses challenges of latency, accuracy, and usability, and Tencent Cloud’s managed Flink service provides elastic, secure, integrated pipelines for applications ranging from online status monitoring to fraud detection and smart transportation.

Apache StormBig DataCloud Services
0 likes · 30 min read
Real-Time Stream Computing: Concepts, Challenges, and Tencent Cloud Solutions
Architect
Architect
Mar 18, 2016 · Backend Development

Sogou Business Platform Infrastructure Evolution: From Horizontal Scaling to Stream Computing

This article outlines Sogou's infrastructure evolution under rapid business iteration, detailing stages of compute and storage horizontal scaling, serviceization, and stream computing, while sharing the practices, principles, lessons learned, and reflections that guided the platform's architectural transformation.

Sogouinfrastructurescalability
0 likes · 4 min read
Sogou Business Platform Infrastructure Evolution: From Horizontal Scaling to Stream Computing