Real-time Analytics with HBase
summary
Claims an append-only writes pattern that turns HBase from batch-limited into real-time by replacing Get+Put updates with append records placed next to target rows. Uses a Java library HBaseHUT, runs periodic MapReduce compaction jobs to merge updates, and leverages server-side Coprocessors for on-the-fly merging. Enables higher update throughput, idempotent MapReduce-safe writes, hour-granularity rollbacks, and graceful peak handling; implemented in production by Sematext and usable as a drop-in HBase client wrapper.
AI-written summary · about
chapters (21)
- 0:00Introduction
- 0:57Plan
- 1:28Use case
- 2:04Statistics
- 2:24Requirements
- 2:59Reading speed
- 3:49Update throughput
- 4:16Counters
- 4:42Processing
- 5:22Updates approach
- 7:29Processing approach
- 7:53Merge records
- 8:49Benefits
- 10:44Updates
- 11:41MapReduce Job
- 14:20Database Hut
- 14:32Integration
- 15:14Implementation
- 15:38Examples
- 16:42Next steps
- 17:37Questions
