I want to do something like this.
select date_trunc('month', time_stamp), sum(distinct_count) from (
select date_trunc('week', time_stamp) as time_stamp, count(distinct
field_name) as distinct_count
from blah
group by date_trun('week', time_stamp)
)
group by date_trunc('month', time_stamp)
So basically I want to break up the data into weekly chunks and count the
distinct appearances of a value and then sum those up on a per monthly
basis.
In preparation for that I tried to do the subquery for that which looks
like this
aggregations: {
by_month: {
date_histogram: {
field: "time_stamp",
interval: "1M",
format: "yyyy-MM-dd HH:mm"
},
aggregations: {
by_node_mac: {
terms: {
field: "node_mac"
},
aggregations: {
cardinality: {field: 'device_mac'}
}
}
}
}
}
}
but I seem to be getting the wrong answers. I am using fake data which
should give me very low numbers for the cardinality but it actually seems
to be counting the number of rows not the number of distinct items. The
numbers are outrageously high.
I tried a precision threshold of 1000 and 100 but it seems to make no
difference.
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