我有数百万个文档要索引。每个文档都有字段doc_id和doc_title几个字段doc_content。import requestsindex = 'test'JSON = { "mappings": { "properties": { "doc_id": {"type": "keyword"}, "doc_title": {"type": "text" }, "doc_content": {"type": "text" } } }}r = requests.put(f'http://127.0.0.1:9200/{index}', json=JSON)为了最小化索引的大小，我保留doc_title并doc_content分开。docs = [ {"doc_id": 1, "doc_title": "good"}, {"doc_id": 1, "doc_content": "a"}, {"doc_id": 1, "doc_content": "b"}, {"doc_id": 2, "doc_title": "good"}, {"doc_id": 2, "doc_content": "c"}, {"doc_id": 2, "doc_content": "d"}, {"doc_id": 3, "doc_title": "bad"}, {"doc_id": 3, "doc_content": "a"}, {"doc_id": 3, "doc_content": "e"}]for doc in docs: r = requests.post(f'http://127.0.0.1:9200/{index}/_doc', json=doc)查询_1：JSON = { "query": { "match": { "doc_title": "good" } }}r = requests.get(f'http://127.0.0.1:9200/{index}/_search', json=JSON)[x['_source'] for x in r.json()['hits']['hits']][{'doc_id': 1, 'doc_title': 'good'}, {'doc_id': 2, 'doc_title': 'good'}]查询_2：JSON = { "query": { "match": { "doc_content": "a" } }}r = requests.get(f'http://127.0.0.1:9200/{index}/_search', json=JSON)[x['_source'] for x in r.json()['hits']['hits']][{'doc_id': 1, 'doc_content': 'a'}, {'doc_id': 3, 'doc_content': 'a'}]如何结合 query_1 和 query_2？我需要这样的东西：JSON = { "query": { "bool": { "must": [ {"match": {"doc_title": "good"}}, {"match": {"doc_content": "a"}} ] } }}r = requests.get(f'http://127.0.0.1:9200/{index}/_search', json=JSON)[x['_source'] for x in r.json()['hits']['hits']][]期望的结果：[{'doc_id': 1, 'doc_title': 'good', 'doc_content': 'a'}]
1 回答
函数式编程
TA贡献1807条经验 获得超9个赞
分开doc_title&是不好的做法doc_content——你并没有真正减少任何东西。
跟着这个：
docs = [
{"doc_id": 1, "doc_title": "good", "doc_content": ["a", "b"]},
{"doc_id": 2, "doc_title": "good", "doc_content": ["c", "d"]},
{"doc_id": 3, "doc_title": "bad", "doc_content": ["a", "e"]}
]
for doc in docs:
r = requests.post(f'http://127.0.0.1:9200/{index}/_doc', json=doc)
并且您的查询将按预期工作。a无论如何都b应该被共享doc_id=1，不是吗？
更新——使contents语法嵌套
PUT test
{
"mappings": {
"properties": {
"contents": {
"type": "nested",
"properties": {
"doc_content": {
"type": "text"
}
}
},
"doc_id": {
"type": "keyword"
},
"doc_title": {
"type": "text"
}
}
}
}
POST test/_doc
{
"doc_id": 1,
"doc_title": "good",
"contents": [
{"doc_content": "a"},
{"doc_content": "b"}
]
}
GET test/_search
{
"_source": ["doc_title", "inner_hits"],
"query": {
"bool": {
"must": [
{
"match": {
"doc_title": "good"
}
},
{
"nested": {
"path": "contents",
"query": {
"match": {
"contents.doc_content": "a"
}
},
"inner_hits": {}
}
}
]
}
}
}
屈服
[
{
"_index":"test",
"_type":"_doc",
"_id":"sySOoXEBdiyDG0RsIq21",
"_score":0.98082924,
"_source":{
"doc_title":"good" <------
},
"inner_hits":{
"contents":{
"hits":{
"total":1,
"max_score":0.6931472,
"hits":[
{
"_index":"test",
"_type":"_doc",
"_id":"sySOoXEBdiyDG0RsIq21",
"_nested":{
"field":"contents",
"offset":0
},
"_score":0.6931472,
"_source":{
"doc_content":"a" <-----
}
}
]
}
}
}
}
]
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