How can I find the minimum value for a field each day over a timespan using RethinkDb? - rethinkdb

Question

I have a database of readings from weather sensors. One of the items measured is 'sky temperature'. I want to find the minimum sky temperature each day over a period of a month or two.
The first thing I tried was this:
r.db('Weather').table('TAO_SkyNet', {readMode:'outdated'})
.group(r.row('time').dayOfYear(),{index:'time'})
.min('sky')
I think that might work, except that it is a large database and the query times out after 300 seconds. Fair enough, I really don't want the data back to the beginning of time. A few weeks will do. So I tried to restrict the records examined like this:
r.db('Weather').table('TAO_SkyNet', {readMode:'outdated'})
.between(r.time(2018,3,1,'Z'), r.now())
.group(r.row('time').dayOfYear(),{index:'time'})
.min('sky')
..and I get...
e: Expected type TABLE but found TABLE_SLICE:
SELECTION ON table(TAO_SkyNet) in:
r.db("Weather").table("TAO_SkyNet", {"readMode": "outdated"}).between(r.time(2018, 3, 1, "Z"), r.now()).group(r.row("time").dayOfYear(), {"index": "time"}).min("sky")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
So, I'm stuck here. How do I group on a subset of the table?

Answer 1

between returns a table slice, and table slices don't support indexes.
table.between(lowerKey, upperKey[, options]) → table_slice
By the way, between operates over indexes itself.
Once you remove {index:'time'} from your group clause (if TAO_SkyNet has time as its primary key):
r.db('Weather')
.table('TAO_SkyNet', {readMode: 'outdated'})
.between(r.time(2018, 3, 1, 'Z'), r.now())
.group(r.row('time').dayOfYear())
.min('sky')
or move the index option to the between clause (if TAO_SkyNet has time as its secondary key)
r.db('Weather')
.table('TAO_SkyNet', {readMode: 'outdated'})
.between(r.time(2018, 3, 1, 'Z'), r.now(), {index: 'time'})
.group(r.row('time').dayOfYear())
.min('sky')
it should work fine.
Test dataset:
r.db('Weather').table('TAO_SkyNet').insert([
// day 1
{time: r.time(2018, 3, 1, 0, 0, 0, 'Z'), sky: 10},
{time: r.time(2018, 3, 1, 8, 0, 0, 'Z'), sky: 4}, // min
{time: r.time(2018, 3, 1, 16, 0, 0, 'Z'), sky: 7},
// day 2
{time: r.time(2018, 3, 2, 0, 0, 0, 'Z'), sky: 2}, // min
{time: r.time(2018, 3, 2, 8, 0, 0, 'Z'), sky: 4},
{time: r.time(2018, 3, 2, 16, 0, 0, 'Z'), sky: 9},
// day 3
{time: r.time(2018, 3, 3, 0, 0, 0, 'Z'), sky: 7},
{time: r.time(2018, 3, 3, 8, 0, 0, 'Z'), sky: 7},
{time: r.time(2018, 3, 3, 16, 0, 0, 'Z'), sky: 1} // min
]);
Query result:
[{
"group": 60,
"reduction": {"sky": 4, "time": Thu Mar 01 2018 08:00:00 GMT+00:00}
},
{
"group": 61,
"reduction": {"sky": 2, "time": Fri Mar 02 2018 00:00:00 GMT+00:00}
},
{
"group": 62,
"reduction": {"sky": 1, "time": Sat Mar 03 2018 16:00:00 GMT+00:00}
}]