我正在尝试使用Elasticsearch for Chinese实现一个简单的演示。 但是搜索结果的相关性存在一些问题。
我使用映射创建了一个新索引：
{
"tag": {
"mappings": {
"tag": {
"properties": {
"name": {
"type": "text",
"analyzer": "standard"
},
"note": {
"type": "text",
"analyzer": "standard"
},
"status": {
"type": "integer"
},
"synonyms": {
"type": "text",
"analyzer": "standard"
}
}
}
}
}
}
请求正文和查询＆＃34;美国＆＃34;：
{
"query" : {
"bool" : {
"must" : {
"multi_match" : {
"query" : "美国",
"fields" : [ "name", "synonyms" ]
}
},
"filter" : {
"term" : {
"status" : 2
}
}
}
}
}
有两个记录＆＃34;中国＆＃34;和＆＃34;美国＆＃34;匹配查询。但记录＆＃34;中国＆＃34;获得了更高的分数。响应JSON如下：
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 0.7373906,
"hits": [ {
"_index": "tag",
"_type": "tag",
"_id": "5482361185636870",
"_score": 0.7373906,
"_source": {
"status": 2,
"name": "中国",
"note": "",
"synonyms": []
}
}, {
"_index": "tag",
"_type": "tag",
"_id": "5474649504748034",
"_score": 0.53484553,
"_source": {
"status": 2,
"name": "美国",
"note": "",
"synonyms": []
}
} ]
}
}
＆＃34;中国＆＃34;的记录获得了0.7373906，但记录了＃34;美国＆＃34;只有0.53484553。
结果解释：
{
"hits": [
{
"_shard": "[tag][0]",
"_node": "Wh9qH0bcTAaVNrsP1Aiyxg",
"_index": "tag",
"_type": "tag",
"_id": "5482361185636870",
"_score": 0.7373906,
"_source": {
"status": 2,
"name": "中国",
"note": "",
"synonyms": []
},
"_explanation": {
"value": 0.73739064,
"description": "sum of:",
"details": [
{
"value": 0.73739064,
"description": "sum of:",
"details": [
{
"value": 0.73739064,
"description": "max of:",
"details": [
{
"value": 0.73739064,
"description": "sum of:",
"details": [
{
"value": 0.73739064,
"description": "weight(name:国 in 0) [PerFieldSimilarity], result of:",
"details": [
{
"value": 0.73739064,
"description": "score(doc=0,freq=1.0 = termFreq=1.0\n), product of:",
"details": [
{
"value": 0.6931472,
"description": "idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details": [
{
"value": 1,
"description": "docFreq",
"details": []
},
{
"value": 2,
"description": "docCount",
"details": []
}
]
},
{
"value": 1.0638298,
"description": "tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
"details": [
{
"value": 1,
"description": "termFreq=1.0",
"details": []
},
{
"value": 1.2,
"description": "parameter k1",
"details": []
},
{
"value": 0.75,
"description": "parameter b",
"details": []
},
{
"value": 3,
"description": "avgFieldLength",
"details": []
},
{
"value": 2.56,
"description": "fieldLength",
"details": []
}
]
}
]
}
]
}
]
}
]
},
{
"value": 0,
"description": "match on required clause, product of:",
"details": [
{
"value": 0,
"description": "# clause",
"details": []
},
{
"value": 1,
"description": "status:[2 TO 2], product of:",
"details": [
{
"value": 1,
"description": "boost",
"details": []
},
{
"value": 1,
"description": "queryNorm",
"details": []
}
]
}
]
}
]
},
{
"value": 0,
"description": "match on required clause, product of:",
"details": [
{
"value": 0,
"description": "# clause",
"details": []
},
{
"value": 1,
"description": "*:*, product of:",
"details": [
{
"value": 1,
"description": "boost",
"details": []
},
{
"value": 1,
"description": "queryNorm",
"details": []
}
]
}
]
}
]
}
},
{
"_shard": "[tag][4]",
"_node": "Wh9qH0bcTAaVNrsP1Aiyxg",
"_index": "tag",
"_type": "tag",
"_id": "5474649504748034",
"_score": 0.51623213,
"_source": {
"status": 2,
"name": "美国",
"note": "",
"synonyms": []
},
"_explanation": {
"value": 0.51623213,
"description": "sum of:",
"details": [
{
"value": 0.51623213,
"description": "sum of:",
"details": [
{
"value": 0.51623213,
"description": "max of:",
"details": [
{
"value": 0.51623213,
"description": "sum of:",
"details": [
{
"value": 0.25811607,
"description": "weight(name:美 in 0) [PerFieldSimilarity], result of:",
"details": [
{
"value": 0.25811607,
"description": "score(doc=0,freq=1.0 = termFreq=1.0\n), product of:",
"details": [
{
"value": 0.2876821,
"description": "idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details": [
{
"value": 1,
"description": "docFreq",
"details": []
},
{
"value": 1,
"description": "docCount",
"details": []
}
]
},
{
"value": 0.89722675,
"description": "tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
"details": [
{
"value": 1,
"description": "termFreq=1.0",
"details": []
},
{
"value": 1.2,
"description": "parameter k1",
"details": []
},
{
"value": 0.75,
"description": "parameter b",
"details": []
},
{
"value": 2,
"description": "avgFieldLength",
"details": []
},
{
"value": 2.56,
"description": "fieldLength",
"details": []
}
]
}
]
}
]
},
{
"value": 0.25811607,
"description": "weight(name:国 in 0) [PerFieldSimilarity], result of:",
"details": [
{
"value": 0.25811607,
"description": "score(doc=0,freq=1.0 = termFreq=1.0\n), product of:",
"details": [
{
"value": 0.2876821,
"description": "idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details": [
{
"value": 1,
"description": "docFreq",
"details": []
},
{
"value": 1,
"description": "docCount",
"details": []
}
]
},
{
"value": 0.89722675,
"description": "tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
"details": [
{
"value": 1,
"description": "termFreq=1.0",
"details": []
},
{
"value": 1.2,
"description": "parameter k1",
"details": []
},
{
"value": 0.75,
"description": "parameter b",
"details": []
},
{
"value": 2,
"description": "avgFieldLength",
"details": []
},
{
"value": 2.56,
"description": "fieldLength",
"details": []
}
]
}
]
}
]
}
]
}
]
},
{
"value": 0,
"description": "match on required clause, product of:",
"details": [
{
"value": 0,
"description": "# clause",
"details": []
},
{
"value": 1,
"description": "status:[2 TO 2], product of:",
"details": [
{
"value": 1,
"description": "boost",
"details": []
},
{
"value": 1,
"description": "queryNorm",
"details": []
}
]
}
]
}
]
},
{
"value": 0,
"description": "match on required clause, product of:",
"details": [
{
"value": 0,
"description": "# clause",
"details": []
},
{
"value": 1,
"description": "*:*, product of:",
"details": [
{
"value": 1,
"description": "boost",
"details": []
},
{
"value": 1,
"description": "queryNorm",
"details": []
}
]
}
]
}
]
}
}
]
}
答案 0 :(得分：3)
您的索引似乎只包含少量文档，但它们属于不同的分片。每个shrad都有自己的术语频率。默认情况下，ElasticSearch使用这些本地值。但是您可以通过指定search_type=dfs_query_then_fetch querystring参数或添加相应的正文字段来更改此行为
{
"search_type": "dfs_query_then_fetch",
"query": {
"bool": {
"must": {
"multi_match": {
"query": "美国",
"fields": [
"name",
"synonyms"
]
}
},
"filter": {
"term": {
"status": 2
}
}
}
}
}
看一下这篇文章https://www.elastic.co/blog/understanding-query-then-fetch-vs-dfs-query-then-fetch