我有一个 Elasticsearch 索引，其中有一个用于精确匹配的字段，以某种方式，我得到了很多相似的结果(我不介意)，并且那些相似的结果在精确匹配之前被排序了(我确实介意)。
有人可以解释发生了什么以及如何解决吗？
我的映射是这样的
"exact":{
"type":"string",
"boost":10.0,
"analyzer":"keyword"
},
我搜索“AAPL P JAN 2014 885,00”的查询是这样的:
{
"size" : 21,
"query" : {
"field" : {
"exact" : "AAPL P JAN 2014 885,00"
}
},
"explain" : true,
"sort" : [ {
"_score" : {
"order" : "desc"
}
} ],
"facets" : {
"category" : {
"terms" : {
"field" : "category",
"size" : 10
}
}
}
}
返回的文档按此顺序结束:
等等，并精确匹配一堆结果。
有人可以向我解释为什么精确匹配没有排在最前面吗？
下面的搜索结果有完整的解释，如果它有助于您理解事物。
"hits" : [ {
"_shard" : 0,
"_node" : "1",
"_index" : "instruments",
"_type" : "instrument",
"_id" : "AAPL",
"_score" : 1306.8339, "_source" : {"exact":["APPLE INC","US0378331005","AAPL","73773"],"id-compound":"AAPL"},
"_explanation" : {
"value" : 1306.8339,
"description" : "product of:",
"details" : [ {
"value" : 6534.169,
"description" : "sum of:",
"details" : [ {
"value" : 6534.169,
"description" : "weight(exact:AAPL in 9096), product of:",
"details" : [ {
"value" : 0.25854474,
"description" : "queryWeight(exact:AAPL), product of:",
"details" : [ {
"value" : 6.1701355,
"description" : "idf(docFreq=211, maxDocs=37299)"
}, {
"value" : 0.0419026,
"description" : "queryNorm"
} ]
}, {
"value" : 25272.875,
"description" : "fieldWeight(exact:AAPL in 9096), product of:",
"details" : [ {
"value" : 1.0,
"description" : "tf(termFreq(exact:AAPL)=1)"
}, {
"value" : 6.1701355,
"description" : "idf(docFreq=211, maxDocs=37299)"
}, {
"value" : 4096.0,
"description" : "fieldNorm(field=exact, doc=9096)"
} ]
} ]
} ]
}, {
"value" : 0.2,
"description" : "coord(1/5)"
} ]
}
}, {
"_shard" : 0,
"_node" : "1",
"_index" : "instruments",
"_type" : "instrument",
"_id" : "AAPL*PUT*20140118*675",
"_score" : 163.35423, "_source" : {"exact":["AAPL","73773","AAPL P JAN 2014 675,00"],"id-compound":"AAPL*PUT*20140118*675"},
"_explanation" : {
"value" : 163.35423,
"description" : "product of:",
"details" : [ {
"value" : 816.7711,
"description" : "sum of:",
"details" : [ {
"value" : 816.7711,
"description" : "weight(exact:AAPL in 18), product of:",
"details" : [ {
"value" : 0.25854474,
"description" : "queryWeight(exact:AAPL), product of:",
"details" : [ {
"value" : 6.1701355,
"description" : "idf(docFreq=211, maxDocs=37299)"
}, {
"value" : 0.0419026,
"description" : "queryNorm"
} ]
}, {
"value" : 3159.1094,
"description" : "fieldWeight(exact:AAPL in 18), product of:",
"details" : [ {
"value" : 1.0,
"description" : "tf(termFreq(exact:AAPL)=1)"
}, {
"value" : 6.1701355,
"description" : "idf(docFreq=211, maxDocs=37299)"
}, {
"value" : 512.0,
"description" : "fieldNorm(field=exact, doc=18)"
} ]
} ]
} ]
}, {
"value" : 0.2,
"description" : "coord(1/5)"
} ]
}
}, {
"_shard" : 0,
"_node" : "1",
"_index" : "instruments",
"_type" : "instrument",
"_id" : "AAPL*CALL*20140118*500",
"_score" : 163.35423, "_source" : {"exact":["AAPL","73773","AAPL C JAN 2014 500,00"],"id-compound":"AAPL*CALL*20140118*500"},
"_explanation" : {
"value" : 163.35423,
"description" : "product of:",
"details" : [ {
"value" : 816.7711,
"description" : "sum of:",
"details" : [ {
"value" : 816.7711,
"description" : "weight(exact:AAPL in 383), product of:",
"details" : [ {
"value" : 0.25854474,
"description" : "queryWeight(exact:AAPL), product of:",
"details" : [ {
"value" : 6.1701355,
"description" : "idf(docFreq=211, maxDocs=37299)"
}, {
"value" : 0.0419026,
"description" : "queryNorm"
} ]
}, {
"value" : 3159.1094,
"description" : "fieldWeight(exact:AAPL in 383), product of:",
"details" : [ {
"value" : 1.0,
"description" : "tf(termFreq(exact:AAPL)=1)"
}, {
"value" : 6.1701355,
"description" : "idf(docFreq=211, maxDocs=37299)"
}, {
"value" : 512.0,
"description" : "fieldNorm(field=exact, doc=383)"
} ]
} ]
} ]
}, {
"value" : 0.2,
"description" : "coord(1/5)"
} ]
}
}, {
"_id" : "AAPL*PUT*20140118*940",
"_score" : 163.35423, "_source" : {"exact":["AAPL","73773","AAPL P JAN 2014 940,00"],"id-compound":"AAPL*PUT*20140118*940"},
"_explanation" : {
"value" : 163.35423,
"description" : "product of:",
"details" : [ {
"value" : 816.7711,
"description" : "sum of:",
"details" : [ {
"value" : 816.7711,
"description" : "weight(exact:AAPL in 794), product of:",
"details" : [ {
"value" : 0.25854474,
"description" : "queryWeight(exact:AAPL), product of:",
"details" : [ {
"value" : 6.1701355,
"description" : "idf(docFreq=211, maxDocs=37299)"
}, {
"value" : 0.0419026,
"description" : "queryNorm"
} ]
}, {
"value" : 3159.1094,
"description" : "fieldWeight(exact:AAPL in 794), product of:",
"details" : [ {
"value" : 1.0,
"description" : "tf(termFreq(exact:AAPL)=1)"
}, {
"value" : 6.1701355,
"description" : "idf(docFreq=211, maxDocs=37299)"
}, {
"value" : 512.0,
"description" : "fieldNorm(field=exact, doc=794)"
} ]
} ]
} ]
}, {
"value" : 0.2,
"description" : "coord(1/5)"
} ]
}
}
万一我分析要存储的数据会发生什么情况:
curl -XGET 'localhost:9200/instruments/_analyze?field=exact&pretty=true' -d 'ING P JUN 2013 6.00'
{
"tokens" : [ {
"token" : "ING P JUN 2013 6.00",
"start_offset" : 0,
"end_offset" : 20,
"type" : "word",
"position" : 1
} ]
最佳答案
正如您从说明输出中看到的那样，所有这三个文档的得分均完全相同，它们均在“AAPL”上匹配。该术语在文档(tf = 1)中始终出现一次，并且在37299文档(idf = 6.1701355)中的211中出现。由于您使用索引时间增强(映射中的增强部分10)，因此字段规范要高得多，因为匹配始终位于同一字段上，所以没什么大不了的。仅仅是如果您在其他领域有一场比赛，确切的情况下总会赢，这在您的情况下可能是有道理的。
但是问题是，如果我查看您的文档，AAPL P JAN 2014 885,00并不完全匹配。我看到的是查询中的5个词中只有一个匹配，这在您的说明输出中也由coord确认:coord(1/5)`。
似乎应用了keyword分析器，但是从返回的文档中可以看到，您不是将exact字段的内容作为单个值发送，而是作为值的数组发送。由于您使用的是keyword分析器，因此不会对每个项目进行标记，但仍然有多个标记。我猜您必须检查如何索引文档。