Hi Alexander,
yes warmers is exactly what I'm looking into right now.
Seems like a good solution, but I still have a problem there.
As shown below, I have a facet_filter with changing dates, so I'm having a
hard time understanding what my warmer should look like if I want all the
range possibilities to work fast.
I tried running the next warmer for loading both time and productCode
fields, but I'm still not sure this is the best I can get here.
Any suggestions?
warmer:
{
"query" : {
"match_all" : {}
},
"facets": {
"tags": {
"terms": {
"fields": ["productCode", "time"]
},
"nested": "products"
}
}
}
query:
{
"query": {
"match_all": {}
},
"size": 0,
"facets": {
"tags": {
"terms": {
"field": "productCode",
"size": 230,
"regex": "GGG\\d+",
"order": "term"
},
"nested": "products",
"facet_filter": {
"range": {
"products.time": {
"from": "2014-01-07",
"to": "2014-01-10",
"include_lower": true,
"include_upper": true
}
}
}
}
}
}
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