Design and Optimization of Zhihu's Bridge Platform for DMP/CDP: Architecture, Challenges, and Solutions

This article presents a comprehensive case study of Zhihu's Bridge platform, detailing its background, five core modules, unified architecture built on Spark and Flink, bitmap‑based tagging, and performance optimizations that address query speed, write latency, and high‑QPS online checks while outlining future directions with Doris 2.0 and large language models.

CDPDMPData Platform

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Design and Optimization of Zhihu's Bridge Platform for DMP/CDP: Architecture, Challenges, and Solutions

政采云技术

Sep 19, 2023 · Big Data

Techniques for Processing Massive Data: Sorting, Querying, Top‑K, and Deduplication

This article explains core concepts and practical solutions for handling massive datasets that cannot fit into memory, covering batch processing, distributed sorting, bitmap indexing, hash‑based lookups, top‑K extraction, and deduplication techniques with code examples and multi‑machine strategies.

Big DataSortingTop‑K

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Techniques for Processing Massive Data: Sorting, Querying, Top‑K, and Deduplication

JD Retail Technology

Oct 15, 2021 · Big Data

How JD’s Activity Cockpit Supercharges Mega‑Sale Performance with Optimize Table, BitMap, and Materialized Views

The article explains how JD’s Activity Cockpit tackles mega‑sale challenges by monitoring the consumer golden‑link, applying Optimize Table, BitMap, and materialized view techniques to reduce data volume, accelerate queries, and enable precise real‑time marketing for brands.

Big Databitmap indexinge-commerce analytics

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How JD’s Activity Cockpit Supercharges Mega‑Sale Performance with Optimize Table, BitMap, and Materialized Views

DataFunTalk

May 9, 2021 · Big Data

User Segmentation and Growth Practices for Mini‑Programs Based on Doris

This article presents a comprehensive case study of how Baidu’s senior R&D engineer Zhao Yuyang built a Doris‑based user‑segmentation system for mini‑programs, detailing the product’s private‑domain fine‑grained operation capabilities, the four technical challenges, the architecture and solutions—including global dictionaries, bitmap storage, partitioning, tag optimization, dynamic‑static query handling, and rapid user‑package generation—along with future roadmap plans.

User Segmentationbitmap indexingdoris

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User Segmentation and Growth Practices for Mini‑Programs Based on Doris