Learn why HBase outperforms MySQL for massive, historical data, explore key rowkey design principles such as composite keys, field ordering, length alignment, and hotspot mitigation, and see practical examples like cold‑hot data separation and transaction logs, plus a concise overview of HBase’s core architecture.
This article details Didi's use of HBase for various online and offline workloads, covering multi‑language support, data types, rowkey designs for order, trajectory and ETA scenarios, multi‑tenant resource management with DHS and RS Group, and operational best practices.
This article details the practical performance‑tuning steps applied to a large‑scale HBase deployment handling 80 billion daily log entries, covering rowkey redesign, region redistribution, HDFS write‑timeout fixes, network‑topology adjustments, and JVM parameter tweaks that together stabilized the system and dramatically improved throughput.
This article explains how Didi leverages HBase’s distributed architecture, multi‑language APIs, and custom rowkey designs to support online order queries, driver‑passenger trajectory tracking with GeoHash, real‑time ETA calculations, and a monitoring platform, while managing multi‑tenant resources through DHS and RS Group.
This article analyzes the characteristics of log data, explains why HBase is chosen for log storage, discusses the shortcomings of self‑built indexes, and presents optimization strategies such as rowKey design, filter usage, coprocessor integration, and third‑party indexing to improve query performance.
