Our Redshift queries are extremely slow during their first execution. Subsequent executions are much faster (e.g., 45 seconds -> 2 seconds). After investigating this problem, the query compilation appears to be the culprit. This is a known issue and is even referenced on the AWS Query Planning And Execution Workflow and Factors Affecting Query Performance pages. Amazon itself is quite tight lipped about how the query cache works (tl;dr it's a magic black box that you shouldn't worry about).
One of the things that we tried was increasing the number of nodes we had, however we didn't expect it to solve anything seeing as how query compilation is a single-node operation anyway. It did not solve anything but it was a fun diversion for a bit.
As noted, this is a known issue, however, anywhere it is discussed online, the only takeaway is either "this is just something you have to live with using Redshift" or "here's a super kludgy workaround that only works part of the time because we don't know how the query cache works".
Is there anything we can do to speed up the compilation process or otherwise deal with this? So far about the best solution that's been found is "pre-run every query you might expect to run in a given day on a schedule" which is....not great, especially given how little we know about how the query cache works.
there are 3 things to consider
SET enable_result_cache_for_session TO OFF;.Considering your issue, you may need to run some example queries to pre compile or redesign your queries ( i guess you have some dynamic query building going on that changes the shape of the query a lot). In my experience, more nodes will increase the compile time. this process happens on the master node not the data nodes, and is made more complex by having more data nodes to consider.
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