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When working on the internals of Citus, an open source extension to Postgres that transforms Postgres into a distributed database, we often get to talk with customers that have interesting challenges you won't find everywhere. Just a few months back, I encountered an analytics workload that was a really good fit for Citus.
But we had one problem: the percentile calculations on their data (over 300 TB of data) could not meet their SLA of 30 seconds.
To make things worse, the query performance was not even close to the target: the percentile calculations were taking about 6 minutes instead of the required 30 second SLA.
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