This article details NetEase Yanxuan’s DMP tag system, covering its platform overview, tag production workflow, storage architecture, high‑performance query techniques, and future plans, illustrating how data from multiple sources is processed through ODS, DWD, DM layers and leveraged via Spark, Hive, and Apache Doris for real‑time and offline analytics.
The article explains that HBase and Hive occupy distinct roles in big‑data systems—HBase handles real‑time random queries on massive detail data, while Hive provides batch‑oriented SQL‑based processing on HDFS—and describes how they are typically combined in a data pipeline.
This article explains how Alibaba's Jushita platform leverages Apache Solr with a wide‑table data model and a custom QParser plugin to achieve real‑time, multi‑dimensional buyer filtering that traditional relational databases cannot handle efficiently in big‑data scenarios.
This article examines a real‑world case from Alibaba’s Taobao Jushita platform, showing how traditional SQL queries struggle with multi‑dimensional, high‑volume data and how integrating Solr’s inverted‑index search engine—combined with Hive‑generated wide tables and custom QParser plugins—delivers millisecond‑level, scalable query performance for buyer analytics.
