For anyone wanting to know an answer, I used
facet.query={!frange l=0 u=31104000000}ms(d_b,d_a)
facet.query={!frange l=31104000001 u=62208000000}ms(d_b,d_a)
facet.query={!frange l=62208000001 u=155520000000}ms(d_b,d_a)
etc ...
Not the prettiest nor most efficient but accomplishes what I need
without re-indexing TBs of data.
thanks.
On 01/08/2016 12:09 PM, Erick Erickson wrote:
I'm going to side-step your primary question and say that it's nearly
always best to do your calculations up-front during indexing to make
queries more efficient and thus serve more requests on the same
hardware. This assumes that the stat you're interested in is
predictable of course...
Best,
Erick
On Fri, Jan 8, 2016 at 2:23 AM, David Santamauro
<david.santama...@gmail.com> wrote:
Hi,
I have two date fields, d_a and d_b, both of type solr.TrieDateField, that
represent different events associated with a particular document. The
interval between these dates is relevant for corner-case statistics. The
interval is calculated as the difference: sub(d_b,d_a) and I've been able to
stats=true&stats.field={!func}sub(d_b,d_a)
What I ultimately would like to report is the interval represented as a
range, which could be seen as facet.query
(pseudo code)
facet.query=sub(d_b,d_a)[ * TO 86400000 ] // day
facet.query=sub(d_b,d_a)[ 86400001 TO 604800000 ] // week
facet.query=sub(d_b,d_a)[ 604800001 TO 2592000000 ] // month
etc.
Aside from actually indexing the difference in a separate field, is there
something obvious I'm missing? I'm on SOLR 5.2 in cloud mode.
thanks
David
