带排除OR的嵌套过滤器查询

本文介绍了带排除OR的嵌套过滤器查询的处理方法，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 我无法将结果集限制为符合 kol_tags.scored.name 和 kol_tags.scored.score 范围为或选项。 I am unable to restrict the result set to documents that match both kol_tags.scored.name and kol_tags.scored.score range for both the or options below. 我想匹配Core Grower和 kol_tags.scored.name c $ c> kol_tags.scored.score 介于1到100之间，除非它们还具有 kol_tags.scored.name 的连接，其中 kol_tags.scored.score 是不，范围为35至65。I would like to match documents that have the kol_tags.scored.name of "Core Grower" and kol_tags.scored.score between 1 and 100 unless they also have kol_tags.scored.name of "Connectivity" where kol_tags.scored.score is NOT in the range of 35 to 65.给定以下内容映射（为简洁起见省略了非嵌套字段）：Given the following mapping (non nested fields omitted for brevity): GET /production_users/user/_mapping{ "user": { "_all": { "enabled": false }, "properties": { "kol_tags": { "type": "nested", "properties": { "scored": { "type": "nested", "properties": { "name": { "type": "string", "index": "not_analyzed", "omit_norms": true, "index_options": "docs" }, "score": { "type": "integer" } } } } } } }}我正在执行以下查询： p> I am executing the following query: { "filter": { "nested": { "path": "kol_tags.scored", "filter": { "or": [ { "and": [ { "terms": { "kol_tags.scored.name": [ "Core Grower" ] } }, { "range": { "kol_tags.scored.score": { "gte": 1, "lte": 100 } } } ] }, { "and": [ { "terms": { "kol_tags.scored.name": [ "Connectivity" ] } }, { "range": { "kol_tags.scored.score": { "gte": 35, "lte": 65 } } } ] } ] } } }}使用上面的查询，我获得了符合 kol_tags.scored.name的文档Core Grower的和 kol_tags.scored.score 1到100之间， ALSO 有 kol_tags.scored.name 的连接和 kol_tags.scored.score 在任何范围内。With the query above I get documents that match kol_tags.scored.name of "Core Grower" and kol_tags.scored.score between 1 and 100 and ALSO that have kol_tags.scored.name of "Connectivity" and kol_tags.scored.score in any range.我需要的是匹配的文件：What I need is documents that match: Core Grower的kol_tags.scored.name 和 kol_tags.scored.score 1到100之间 kol_tags.scored.score 35和65之间的 kol_tags.scored.name 排除具有连接和 kol_tags.scored.score的 kol_tags.scored.name 的任何文档小于34且大于66 kol_tags.scored.name of "Core Grower" and kol_tags.scored.score between 1 and 100kol_tags.scored.name of "Connectivity" and kol_tags.scored.score between 35 and 65Exclude any documents that have kol_tags.scored.name of "Connectivity" and kol_tags.scored.score less than 34 and greater than 66推荐答案您的描述有一些歧义，但我试图制作一个可运行的例子，应该在这里工作： https://www.found.no/play/gist/8940202 （也嵌入下面）There's some ambiguity in your description, but I've tried to make a runnable example that should work here: https://www.found.no/play/gist/8940202 (also embedded below)以下是我所做的一些事情：Here's a few things I did: 将过滤器置于过滤的 -query中。只有当您想要过滤匹配时，才应使用顶级过滤器（重命名为Elasticsearch 1.0中的 post_filter ） Put the filter in a filtered-query. A top level filter (renamed to post_filter in Elasticsearch 1.0) should only be used if you want to filter hits, but not facets.使用 bool 而不是和和或，因为过滤器是可高速缓存的。更多这里： http://www.elasticsearch.org/blog/all -about-elasticsearch-filter-bitsets / Use bool instead of and and or, since the filters are cachable. More here: http://www.elasticsearch.org/blog/all-about-elasticsearch-filter-bitsets/最重要的是，将嵌套 bool ，所以逻辑正确wrt。嵌套和父文档应该匹配什么。And most importantly, put the nested inside the bool, so the logic gets right wrt. what should match on the nested vs. the parent document.添加了一个 must_not 最后一点。不确定是否可以有两个名称为连接的子文档，但如果可以的话，那应该是这样的。如果你只有一个，你可以删除 must_not 。Added a must_not to account for your last point. Not sure if you can have two sub-documents with name "Connectivity", but if you can, that should account for it. If you'll only ever have one, you can remove the must_not.您没有提供任何示例文档，所以我想一些我认为应该适合您的描述。我不认为你需要两个级别的嵌套。You didn't provide any sample documents, so I made some I think should fit your description. I don't think you need two levels of nested.#!/bin/bashexport ELASTICSEARCH_ENDPOINT="http://localhost:9200"# Create indexescurl -XPUT "$ELASTICSEARCH_ENDPOINT/play" -d '{ "mappings": { "type": { "properties": { "kol_tags": { "properties": { "scored": { "type": "nested", "properties": { "name": { "type": "string", "index": "not_analyzed" } } } } } } } }}'# Index documentscurl -XPOST "$ELASTICSEARCH_ENDPOINT/_bulk?refresh=true" -d '{"index":{"_index":"play","_type":"type"}}{"kol_tags":{"scored":[{"name":"Core Grower","score":36},{"name":"Connectivity","score":42}]}}{"index":{"_index":"play","_type":"type"}}{"kol_tags":{"scored":[{"name":"Connectivity","score":34},{"name":"Connectivity","score":42}]}}{"index":{"_index":"play","_type":"type"}}{"kol_tags":{"scored":[{"name":"Core Grower","score":36}]}}{"index":{"_index":"play","_type":"type"}}{"kol_tags":{"scored":[{"name":"Connectivity","score":36}]}}'# Do searchescurl -XPOST "$ELASTICSEARCH_ENDPOINT/_search?pretty" -d '{ "query": { "filtered": { "filter": { "bool": { "should": [ { "nested": { "path": "kol_tags.scored", "filter": { "bool": { "must": [ { "term": { "name": "Core Grower" } }, { "range": { "score": { "gte": 1, "lte": 100 } } } ] } } } }, { "nested": { "path": "kol_tags.scored", "filter": { "bool": { "must": [ { "term": { "name": "Connectivity" } }, { "range": { "score": { "gte": 35, "lte": 65 } } } ] } } } } ], "must_not": [ { "nested": { "path": "kol_tags.scored", "filter": { "bool": { "must": [ { "term": { "name": "Connectivity" } }, { "not": { "range": { "score": { "gte": 35, "lte": 65 } } } } ] } } } } ] } } } }}'curl -XPOST "$ELASTICSEARCH_ENDPOINT/_search?pretty" -d '{ "filter": { "nested": { "path": "kol_tags.scored", "filter": { "or": [ { "and": [ { "terms": { "kol_tags.scored.name": [ "Core Grower" ] } }, { "range": { "kol_tags.scored.score": { "gte": 1, "lte": 100 } } } ] }, { "and": [ { "terms": { "kol_tags.scored.name": [ "Connectivity" ] } }, { "range": { "kol_tags.scored.score": { "gte": 35, "lte": 65 } } } ] } ] } } }}' 这篇关于带排除OR的嵌套过滤器查询的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！