Dear all, I want to share with you some results. I implemented a query in
two different ways. Given the following common code:
start = db.record.with_alias('start_point')
end = db.record.with_alias('end_point')
elapsed_time = end.gathered_on.epoch() - start.gathered_on.epoch()
The first query is (the constrain is in the query):
rows = db( query & (elapsed_time < 86400) ).select(
start.ALL,
end.ALL,
start.gathered_on.epoch(),
end.gathered_on.epoch(),
elapsed_time,
orderby=start.gathered_on.epoch(),
left=start.on( (start.mac == end.mac) & (start.gathered_on <
end.gathered_on)),
cache=(cache.memcache, 3600),
cacheable = True
)
The second one is (the constrain is explicitly tested latter):
rows = db( query ).select(
start.ALL,
end.ALL,
start.gathered_on.epoch(),
end.gathered_on.epoch(),
elapsed_time,
orderby=start.gathered_on.epoch(),
left=start.on( (start.mac == end.mac) & (start.gathered_on <
end.gathered_on)),
cache=(cache.memcache, 3600),
cacheable = True
)
rows2 = [r for r in rows if (r.end_point.gathered_on -
r.start_point.gathered_on < datetime.timedelta(days=1)) ]
>From the timing results I got that the second query is always faster, with
or without cache:
Q_1: 0.273243904114
Q_1 with cache: 0.0182011127472
Q_2: 0.250607967377
Q_2 with cache: 0.0158171653748
Beside the fact that they are just a few milliseconds of difference and
that all the rows satisfy the constrain, what is not clear to me is why
even when the cache is enabled the first query is taking longer. The
question that came to my mind is about computed columns, are they cached?
Paolo
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