In this session you will learn about what it takes to process joins in distributed databases and then we’ll take a deep dive into how Apache Druid does joins in each of its processing engines. Druid’s native query engine is designed for fast queries and it can do joins, we’ll talk about query design to take advantage of how it works. You will also learn its limits and when a use case is better resolved by the Multi-Stage Query engine (MSQ). We’ll review the current state of MSQ-based joins and when to use broadcast vs sortMerge join algorithms based on how each works and how they use resources.
Imply Lumi Observability Warehouse Demo
In this 30-minute session, you'll see a demo of Imply Lumi — the observability data layer built to help you store more, search faster, and reduce cost without changing your existing tools.
Watch nowLunch & Learn: Imply Lumi Observability Warehouse Demo
In this 30-minute session, you'll see a demo of Imply Lumi — the observability data layer built to help you store more, search faster, and reduce cost without changing your existing tools.
Watch nowImply Lumi: What’s New, What’s Next — and How to Unlock More Observability Value Today
Observability teams must retain more data, investigate faster, and control costs without disrupting existing tools. This live Imply Lumi update shows new ingestion, retention, search, Splunk interoperability,...
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