Elasticsearch 按字段分组过滤文档 [英] Elasticsearch filter document group by field
本文介绍了Elasticsearch 按字段分组过滤文档的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有一些文件:
{"name": "John", "district": 1},
{"name": "Mary", "district": 2},
{"name": "Nick", "district": 1},
{"name": "Bob", "district": 3},
{"name": "Kenny", "district": 1}
如何按地区过滤/选择不同的文件?
How can I filter/select distinct documents by district?
{"name": "John", "district": 1},
{"name": "Mary", "district": 2},
{"name": "Bob", "district": 3}
在 SQL 中,我可以使用 GROUP BY.我尝试了术语聚合,但它只返回了不同的计数.
In SQL, I can use GROUP BY. I tried terms aggregation but it only returned count distinct.
"aggs": {
"distinct": {
"terms": {
"field": "district",
"size": 0
}
}
}
感谢您的帮助!:-)
推荐答案
如果您的 ElasticSearch 版本是 1.3 或更高版本,您可以使用 top_hits 它将为您提供(默认情况下)按查询分数排序的前三个匹配文档(此处为 1当您使用 match_all 查询时).
If your ElasticSearch version is 1.3 or above, you could use a subaggregation of type top_hits which will give you (by default) the top three matching documents sorted on your query score (here, 1 as you use a match_all query).
size
参数可以设置为 3 以上.
You can set the size
parameter to more than 3.
以下数据集和查询:
POST /test/districts/
{"name": "John", "district": 1}
POST /test/districts/
{"name": "Mary", "district": 2}
POST /test/districts/
{"name": "Nick", "district": 1}
POST /test/districts/
{"name": "Bob", "district": 3}
POST test/districts/_search
{
"size": 0,
"aggs":{
"by_district":{
"terms": {
"field": "district",
"size": 0
},
"aggs": {
"tops": {
"top_hits": {
"size": 10
}
}
}
}
}
}
将按照您想要的方式输出文档:
Will output the documents the way you want :
{
"took": 5,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 4,
"max_score": 0,
"hits": []
},
"aggregations": {
"by_district": {
"buckets": [
{
"key": 1,
"key_as_string": "1",
"doc_count": 2,
"tops": {
"hits": {
"total": 2,
"max_score": 1,
"hits": [
{
"_index": "test",
"_type": "districts",
"_id": "XYHu4I-JQcOfLm3iWjTiOg",
"_score": 1,
"_source": {
"name": "John",
"district": 1
}
},
{
"_index": "test",
"_type": "districts",
"_id": "5dul2XMTRC2IpV_tKRRltA",
"_score": 1,
"_source": {
"name": "Nick",
"district": 1
}
}
]
}
}
},
{
"key": 2,
"key_as_string": "2",
"doc_count": 1,
"tops": {
"hits": {
"total": 1,
"max_score": 1,
"hits": [
{
"_index": "test",
"_type": "districts",
"_id": "I-9Gd4OYSRuexhP1dCdQ-g",
"_score": 1,
"_source": {
"name": "Mary",
"district": 2
}
}
]
}
}
},
{
"key": 3,
"key_as_string": "3",
"doc_count": 1,
"tops": {
"hits": {
"total": 1,
"max_score": 1,
"hits": [
{
"_index": "test",
"_type": "districts",
"_id": "bti2y-OUT3q2mBNhhI3xeA",
"_score": 1,
"_source": {
"name": "Bob",
"district": 3
}
}
]
}
}
}
]
}
}
}
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