# Combining aggregations
**URL:** https://discuss.elastic.co/t/combining-aggregations/47816
**Category:** Elasticsearch
**Created:** [April 19, 2016, 5:01pm UTC](https://discuss.elastic.co/t/combining-aggregations/47816 "2016-04-19T17:01:41Z")
**Posts on this page:** 4
**Page:** 1
### Author:  [@stephan2](https://discuss.elastic.co/u/stephan2)
#### Post date: [April 19, 2016, 5:01pm UTC](https://discuss.elastic.co/t/combining-aggregations/47816/1 "2016-04-19T17:01:41Z")
Hi community,
I try to combine query aggregations. For example, if I have one main query (title:bike) and 3 aggregation filters (brand:giant, color:red and size:M), I want to get all the possible combinations:
number of bike that are giant and red and M
number of bike that are red and not giant,and not M
and so on...
I tried to generate a query with all the combinations, but it is quite a big query and I am not sure it is optimal from a performance point of view. Do you think there is a better way to do that with ES?
Thank you,
FYI, the generated query is :
"query" : {
"query\_string" : {
"query" : "title:bike"
}
},
"aggregations" : {
"0" : {
"filter" : {
"bool" : {
"must\_not" : [ {
"query\_string" : {
"query" : "color:red"
}
}, {
"query\_string" : {
"query" : "size:M"
}
}, {
"query\_string" : {
"query" : "brand:giant"
}
} ]
}
}
},
"1" : {
"filter" : {
"bool" : {
"must" : {
"query\_string" : {
"query" : "color:red"
}
},
"must\_not" : [ {
"query\_string" : {
"query" : "size:M"
}
}, {
"query\_string" : {
"query" : "brand:giant"
}
} ]
}
}
},
"2" : {
"filter" : {
"bool" : {
"must" : {
"query\_string" : {
"query" : "size:M"
}
},
"must\_not" : [ {
"query\_string" : {
"query" : "color:red"
}
}, {
"query\_string" : {
"query" : "brand:giant"
}
} ]
}
}
},
"3" : {
"filter" : {
"bool" : {
"must" : [ {
"query\_string" : {
"query" : "color:red"
}
}, {
"query\_string" : {
"query" : "size:M"
}
} ],
"must\_not" : {
"query\_string" : {
"query" : "brand:giant"
}
}
}
}
},
"4" : {
"filter" : {
"bool" : {
"must" : {
"query\_string" : {
"query" : "brand:giant"
}
},
"must\_not" : [ {
"query\_string" : {
"query" : "color:red"
}
}, {
"query\_string" : {
"query" : "size:M"
}
} ]
}
}
},
"5" : {
"filter" : {
"bool" : {
"must" : [ {
"query\_string" : {
"query" : "color:red"
}
}, {
"query\_string" : {
"query" : "brand:giant"
}
} ],
"must\_not" : {
"query\_string" : {
"query" : "size:M"
}
}
}
}
},
"6" : {
"filter" : {
"bool" : {
"must" : [ {
"query\_string" : {
"query" : "size:M"
}
}, {
"query\_string" : {
"query" : "brand:giant"
}
} ],
"must\_not" : {
"query\_string" : {
"query" : "color:red"
}
}
}
}
},
"7" : {
"filter" : {
"bool" : {
"must" : [ {
"query\_string" : {
"query" : "color:red"
}
}, {
"query\_string" : {
"query" : "size:M"
}
}, {
"query\_string" : {
"query" : "brand:giant"
}
} ]
}
}
}
}
}
---
### Author:  [@stephan2](https://discuss.elastic.co/u/stephan2)
#### Post date: [April 21, 2016, 7:20am UTC](https://discuss.elastic.co/t/combining-aggregations/47816/2 "2016-04-21T07:20:46Z")
Hi all,
The solution does't 'look' very optimal. But after some test, it seems that it is not too bad. I think Elasticsearch uses the cache quite well and avoid recalculating the filter each time it need it.
But another solution (less verbose) would be welcomed if someone has a better idea 🙂
Thanks,
---
### Author:  [@Mark\_Harwood](https://discuss.elastic.co/u/Mark_Harwood)
#### Post date: [April 21, 2016, 8:34am UTC](https://discuss.elastic.co/t/combining-aggregations/47816/3 "2016-04-21T08:34:51Z")
See [https://github.com/elastic/elasticsearch/pull/7020#issuecomment-53087546](https://github.com/elastic/elasticsearch/pull/7020#issuecomment-53087546)
Cheers
Mark
---
### Author:  [@system](https://discuss.elastic.co/u/system)
#### Post date: [July 5, 2017, 10:57pm UTC](https://discuss.elastic.co/t/combining-aggregations/47816/4 "2017-07-05T22:57:25Z")