问题
I want to do a quite involved query/aggregation. I can't see how because I've just started working with ES. The documents I have look something like this:
{
"keyword": "some keyword",
"items": [
{
"name":"my first item",
"item_property_1":"A",
( other properties here )
},
{
"name":"my second item",
"item_property_1":"B",
( other properties here )
},
{
"name":"my third item",
"item_property_1":"A",
( other properties here )
}
]
( other properties... )
},
{
"keyword": "different keyword",
"items": [
{
"name":"cool item",
"item_property_1":"A",
( other properties here )
},
{
"name":"awesome item",
"item_property_1":"C",
( other properties here )
},
]
( other properties... )
},
( other documents... )
Now, what I would like to do is to, for each keyword, count how many items there are for which of the several possible values that property_1 can have. That is, I want a bucket aggregation that would have the following response:
{
"keyword": "some keyword",
"item_property_1_aggretation": [
{
"key":"A",
"count": 2,
},
{
"key":"B",
"count": 1,
}
]
},
{
"keyword": "different keyword",
"item_property_1_aggretation": [
{
"key":"A",
"count": 1,
},
{
"key":"C",
"count": 1,
}
]
},
( other keywords... )
If mappings are necessary, could you also specificy which? I don't have any non-default mappings, I just dumped everything in there.
EDIT: Saving you the trouble by posting here the bulk PUT for the previous example
PUT /test/test/_bulk
{ "index": {}}
{ "keyword": "some keyword", "items": [ { "name":"my first item", "item_property_1":"A" }, { "name":"my second item", "item_property_1":"B" }, { "name":"my third item", "item_property_1":"A" } ]}
{ "index": {}}
{ "keyword": "different keyword", "items": [ { "name":"cool item", "item_property_1":"A" }, { "name":"awesome item", "item_property_1":"C" } ]}
EDIT2:
I just tried this:
POST /test/test/_search
{
"size":2,
"aggregations": {
"property_1_count": {
"terms":{
"field":"item_property_1"
}
}
}
}
and got this:
"aggregations": {
"property_1_count": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "a",
"doc_count": 2
},
{
"key": "b",
"doc_count": 1
},
{
"key": "c",
"doc_count": 1
}
]
}
}
close but no cigar. You can see what's happening, it's bucketing over each item_property_1 irrespectively of the keyword it belongs to. I'm sure the solution involves adding some mapping correctly, but I can't put my finger on it. Suggestions?
EDIT3:
Based on this:
https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-nested-type.html
I want to try adding a nested type to property items. To do that, I tried:
PUT /test/_mapping/test
{
"test":{
"properties": {
"items": {
"type": "nested",
"properties": {
"item_property_1":{"type":"string"}
}
}
}
}
}
However, this returns an error:
{
"error": "MergeMappingException[Merge failed with failures {[object mapping [items] can't be changed from non-nested to nested]}]",
"status": 400
}
This might have to do with the warning on that url: "changing an object type to nested type requires reindexing."
So, how do I do that?
回答1:
Nice tries, you were almost there! Here is what I came up with. Based on your mapping proposal, the mapping I'm using is the following:
curl -XPUT localhost:9200/test/_mapping/test -d '{
"test": {
"properties": {
"keyword": {
"type": "string",
"index": "not_analyzed"
},
"items": {
"type": "nested",
"properties": {
"name": {
"type": "string"
},
"item_property_1": {
"type": "string",
"index": "not_analyzed"
}
}
}
}
}
}'
Note: you need to wipe and reindex your data, since you cannot change a field type from being not nested to nested.
Then I created some data with the bulk query you shared:
curl -XPOST localhost:9200/test/test/_bulk -d '
{ "index": {}}
{ "keyword": "some keyword", "items": [ { "name":"my first item", "item_property_1":"A" }, { "name":"my second item", "item_property_1":"B" }, { "name":"my third item", "item_property_1":"A" } ]}
{ "index": {}}
{ "keyword": "different keyword", "items": [ { "name":"cool item", "item_property_1":"A" }, { "name":"awesome item", "item_property_1":"C" } ]}
'
Finally, here is the aggregation query you can use to get the results you expect. We first bucket by keyword using a terms aggregation and then for each keyword, we bucket by the nested item_property_1 field. Since items is now a nested type, the key is to use a nested aggregation for items and then a terms sub-aggregation for the item_property_1 field.
{
"size": 0,
"aggregations": {
"by_keyword": {
"terms": {
"field": "keyword"
},
"aggs": {
"prop_1_count": {
"nested": {
"path": "items"
},
"aggs": {
"prop_1": {
"terms": {
"field": "items.item_property_1"
}
}
}
}
}
}
}
}
Running that query on your data set will yield this:
{
...
"aggregations" : {
"by_keyword" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [ {
"key" : "different keyword", <---- keyword 1
"doc_count" : 1,
"prop_1_count" : {
"doc_count" : 2,
"prop_1" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [ { <---- buckets for item_property_1
"key" : "A",
"doc_count" : 1
}, {
"key" : "C",
"doc_count" : 1
} ]
}
}
}, {
"key" : "some keyword", <---- keyword 2
"doc_count" : 1,
"prop_1_count" : {
"doc_count" : 3,
"prop_1" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [ { <---- buckets for item_property_1
"key" : "A",
"doc_count" : 2
}, {
"key" : "B",
"doc_count" : 1
} ]
}
}
} ]
}
}
}
来源：https://stackoverflow.com/questions/31841542/elasticsearch-metric-aggregation-number-of-elements-in-array