As a follow on to last year’s Load, Drop & Kill session, we’ll do a recap on how retention rules are defined and how they are used by the Coordinator to oversee segment cacheing in a multi-tiered Apache Druid deployment. We’ll also cover some exciting new features. We’ll touch on how retention rules enable the new “Query from Deep Storage” feature. We’ll do another pass at the Coordinator cycle and how it has evolved including how it can now dynamically reconfigure itself. Finally we’ll do another pass at the lifecycle of a segment in a Druid cluster and highlight how this has changed since last year.
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....
Watch now