[英]Postprocessing Elastic results with another search (migrating from Solr)
I'm currently migrating an application from Solr to Elastic and stumbled over an interesting Solr feature that I cannot reproduce in Elastic: The query to Solr returns a postprocessing flag that does a quality check on the result, indicating wether all tokens are found in the結果字段。
q = some_field:(the brown fox)
fl = some_field, full_match:exists(query({!edismax v='some_field:(the brown fox)' mm='100%'}))
Solr 結果如下所示:
{
"response": {
"docs": [
{
"some_field": "The Brown Bear",
"full_match": false
},
{
"some_field": "The Quick Brown Fox",
"full_match": true
}
]
}
}
客戶端使用該標志來進一步處理結果文檔,與分數無關(我在示例中省略了)。 我發現這很聰明,因為使用 Solr 的標記化和分布式計算能力,而不是在客戶端做所有事情。
現在在 Elastic 中,我假設這應該在script_fields
塊中完成,但實際上我不知道如何使用無痛腳本執行子查詢,經過兩天的調查,我懷疑這是否可能:
{
"query": {
"match": {
"some_field": "the brown fox"
}
},
"_source": [
"some_field"
],
"script_fields": {
"full_match": {
"script": "???" <-- Search with Painless script?
}
}
}
歡迎任何有創意的想法。
將 Elasticsearch 的命名查詢與minimum_should_match參數結合使用並將其設置為 100% 以僅匹配所有標記匹配的文檔怎么樣?
然后,您將能夠檢測到響應中所有標記都匹配的查詢。 您還可以設置 "boost": 0 以避免影響主查詢的分數。
這是一個示例請求:
{
"query": {
"bool": {
"should": [
{
"match": {
"message": {
"query": "the brown fox",
"_name": "main_query"
}
}
},
{
"match": {
"message": {
"query": "the brown fox",
"_name": "all_tokens_match",
"minimum_should_match": "100%",
"boost": 0
}
}
}
]
}
}
}
然后你會得到一個看起來有點像這樣的響應:
{
"hits": [
{
"_score": 0.99938476,
"_source": {
"message": "The Quick Brown Fox"
},
"matched_queries": [
"main_query",
"all_tokens_match"
]
},
{
"_score": 0.38727614,
"_source": {
"message": "The Brown Bear"
},
"matched_queries": [
"main_query"
]
}
]
}
查詢中所有標記匹配的文檔將在響應的matched_queries部分中包含all_tokens_match 。
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