Ian,
Thanks working with Yiran on this! I think there is "good" and bad news
w.r.t these queries:
- The bad news is that they go beyond what we are likely to optimize
at all well at present,
as they go beyond what typical DB aggregate functions like
min/max/avg/count/sum do.
(I would try forming the groups and then doing these things on the
groups, but saying
them in AQL will be tricky, and may lead to queries that hit edge
cases in the optimizer.
For some of these my thought was to try using a positional variable
within a group...?)
- The "good" news (only for AsterixDB) is that this is exactly the
sort of inspiration that we
are looking for in terms of understanding how to better for
query-based analytics in real
use cases (and this is a very real one!).
To quote a short paper I reviewed just this AM on SQL queries kind of
like these: "Percentage
queries are more complex than their conventional counterparts and
introduce new challenges
for optimization." (The paper didn't have an applicable solution for
us, sadly.)
A more general facility that I wish we could offer was to do grouping in
AsterixDB but then
have the ability to pass a group to (e.g.) R and then get results back
for the group. When
groups are small-ish (like Yiran's windows) that would be pretty cool -
then one could do
all sorts of advanced things per group.
Cheers,
Mike
On 2/21/16 12:35 AM, Ian Maxon wrote:
Yiran and I came up with possible answers for these...
For 1) , a function could be used that looks something like this:
declare function minmax($x){
let $stdv := (avg(for $z in $x return $z*$z) - avg($x) * avg($x))^(0.5)
for $y in $x
where $y < (2*$stdv) + avg($x)
and $y > avg($x) - (2*$stdv)
return $y
}
And then applied to return a new copy of the list of values, removing ones
that are outside of 2 stdev.
For 2), we also did come up with a potential solution ,but the query fails
to compile (Filed as https://issues.apache.org/jira/browse/ASTERIXDB-1308 )
Any thoughts on these queries would be welcome :) 1) especially seems
inefficient to do as a function.
- Ian
On Fri, Feb 19, 2016 at 3:37 PM, Yiran Wang <[email protected]> wrote:
Hi Asterix team,
I have two queries I'm struggling with. I'm hoping you could provide a
direction for me. Thanks in advance!
Here is what the data structure looks like:
create type HRMType as closed {
row_id: int32,
sid: int32,
date: date,
day: int32,
time: time,
bpm: int32,
RR: float
};
create dataset HRM (HRMType)
primary key row_id;
Previously I have used the time bin function to calculate the standard
deviation of bpm for each time bin:
for $i in dataset HRM
group by $sid := $i.sid, $gdate := $i.date, $gday := $i.day, $timebin :=
interval-bin($i.time, time("00:00:00"), day-time-duration("PT1M")) with $i
return {
"sid": $sid,
"gdate": $gdate,
"gday": $gday,
"timebin": $timebin,
"stdv": (avg(for $ii in $i return $ii.RR * $ii.RR) - avg(for $ii in $i
return $ii.RR) * avg(for $ii in $i return $ii.RR))^(0.5)};
Now I have two things I am hoping to do but need help with:
1. For each 1-min time bin, remove the bpm values that are above the top
5% or below the bottom 5%. I thought about using the min/max function for a
few times to achieve this, but realized that it was not a good idea because
in each time bin, the number of instances are not always the same. So for
each 1-min time bin, we do need to calculate the 5% and 95% threshold, and
remove instances accordingly, which I don't know how to do.
2. After removing the outliers of bpm for each 1-min time bin, calculate a
median absolute deviation (MAD) for each 1-min time bin (as another measure
of variation besides the standard deviation). MAD =
median(abs(x-median(x)). I'm not sure how to write a query to do the median
function in Asterix.
Thank you so much in advance. Let me know if my questions are clear.
Yiran
--
Best,
Yiran
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