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A few months ago i was tasked with replacing declarative lookup rollup summaries dlrs in an org suffering from frequent deadlocks. You can use aggregations in the ingestion spec during ingestion to summarize data before it enters apache druid. Aggregations with spark groupby, cube, rollup spark has a variety of aggregate functions to group, cube, and rollup dataframes. Introduction i have been having a bit of hands on with ssas tabular just lately and one the aspects that i think is extremely powerful is that it provides users with the ability to mash up their own data in various adhoc data sources with data from a structured sql server database, More specifically allowing users to create a control how granular attributes of a dimension might rollup up into.

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