Backfilling materialized views in ClickHouse: A practical guide
Mark Needham
Learn how to properly backfill historical data when adding materialized views to existing ClickHouse tables.
This tutorial walks you through a common challenge when working with large datasets and shows you how to maintain data consistency across your analytics pipeline.
In this video, you'll discover:
- How to create efficient materialized views for aggregating data
- Why backfilling is necessary when adding views to tables with existing data
- A step-by-step approach using temporary tables for backfilling large datasets
- Practical techniques to avoid memory issues with large backfill operations

User stories, Meetups
ClickHouse at DoorDash
How DoorDash monitors TCP and DNS traffic helping their observability team take care of their kubernetes infrastructure.

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Building the Future Data Lakehouse: Iceberg & ClickHouse
Erlebe, wie du Performance, Offenheit und Governance in deiner Datenplattform vereinst

ClickHouse, ClickHouse Cloud, ClickStack
Introducing ClickStack: The Future of Observability on ClickHouse
Tristan Ahmadi, Solution Architect, ClickHouse