Compaction in the Druid database has been evolving into use cases beyond improving query performance and reducing storage. This talk will first go over what is compaction, current use cases for compaction, a beginner’s guide on setting up compaction (and automatic compaction), and common pitfalls when setting up auto-compaction. The talk will then drive into short and long term plans for compaction in Druid. Future features include creating derived datasources / materialized views and automatically changing or maintaining different schemas for the same datasource based on the age of data.
Keynote: Powering Event-Driven Data with Apache Druid
The distinction between OLTP and OLAP is becoming less relevant as data architectures shift toward entities and events. In this session, we’ll delve into how Apache Druid’s event-first approach synthesizes...
Watch nowClosing Keynote: Charting the Future of Druid
What lies ahead for Apache Druid? Join us as we explore the evolving landscape of Druid’s query and storage engines, and how they are positioned to address the biggest challenges in event data for the future. Speaker: Gian...
Watch nowSalesforce: Tracing Service Dependencies at Scale with Druid and Flink
At Salesforce, we manage approximately 300 million distributed spans to infer service dependencies. We have successfully utilized a combination of Druid and Flink to handle this scale with high availability....
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