Consider the following demo schema
trades:([]symbol:`$();ccy:`$();arrivalTime:`datetime$();tradeDate:`date$(); price:`float$();nominal:`float$());
marketPrices:([]sym:`$();dateTime:`datetime$();price:`float$());
usdRates:([]currency$();dateTime:`datetime$();fxRate:`float$());
I want to write a query that gets the price, translated into USD, at the soonest possible time after arrivalTime. My beginner way of doing this has been to create intermediate tables that do some filtering and translating column names to be consistent and then using aj and ajo to join them up.
In this case there would only be 2 intermediate tables. In my actual case there are necessarily 7 intermediate tables and records counts, while not large by KDB standards, are not small either.
What is considered best practice for queries like this? It seems to me that creating all these intermediate tables is resource hungry. An alternative to the intermediate tables is 2 have a very complicated looking single query. Would that actually help things? Or is this consumption of resources just the price to pay?
For joining to the next closest time after an event take a look at this question: KDB reverse asof join (aj) ie on next quote instead of previous one
Assuming that's what your looking for then you should be able to perform your price calculation either before or after the join (depending on the size of your tables it may be faster to do it after). Ultimately I think you will need two (potentially modified as per above) aj's (rates to marketdata, marketdata to trades).
If that's not what you're looking for then I could give some more specifics although some sample data would be useful.