New Tips and Tricks that Every ClickHouse Developer Should Know | ClickHouse Webinar
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Are you building analytic applications on #ClickHouse? Great choice!
In this talk, Robert Hodges (Altinity CEO) shows 7 tricks to develop analytic apps that are fast, cost-efficient, and easy to maintain, such as loading data from S3, using aggregation instead of joins, applying materialized views, using compression effectively, and many more.
You also gain insight into how column storage, parallel processing, and distributed algorithms make ClickHouse the fastest analytic database on the planet. Stick around to witness the power of real-time data!
Want the slide deck? Get it here: altinity.com/New-Tips-and-Tri...
#Altinity #datanalytics #opensource #datawarehouse #database #devops #realtime #datanalytics #datamanagement #dbms #dbmstutorials
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08:10 - Read S3 data fast with wildcards and named collections 15:25 - Reduce storage size using codecs and compression 24:30 - Repeat time column in ORDER BY to speed up time-based queries 32:55 - Handle mutable data with ReplacingMergeTree 41:40 - Store RBAC model in zookepper ( or clickhouse keepper ) 48:10 - Use aggregation to simulate joins
The order for the table (around 30:00): Wouldn’t it be even more optimal if we put the toStartIfDay at first place? If we had a where condition in our select that limits the results to user_id, the given sort order would be best. But we don’t